Article - - Bidgely UtilityAI™ - Energy Analytics

As energy providers around the world strive to achieve aggressive carbon reduction goals, it is often new distributed energy resource (DER) technologies like solar energy, battery storage and electric vehicles that dominate the conversation.

And while renewable energy and beneficial electrification are an essential part of the solution, smarter energy usage in the form of energy efficiency, demand response and other demand side management (DSM) programs are just as integral to achieving decarbonization.

In fact, while adding more clean energy to the grid and electrifying all vehicles will take decades, next generation DSM can make substantial progress today. Utilities – and society – need the full range of DSM programs to achieve meaningful net zero progress now while we continue to transition our energy supply, electrify transportation, and update essential infrastructure.

Energy efficiency programs are by far the largest DSM effort, and the energy savings accrued from improvements in energy efficiency is the simplest and least expensive path to reducing greenhouse gas emissions. Engaging consumers through next-generation energy efficiency programs delivers immediate carbon impact with lower start-up thresholds.

Utilities worldwide turn to Bidgely to facilitate their DSM program evolutions, upgrading existing programs to deliver more timely, personalized, and relevant energy experiences to every customer, which in turn improve energy efficiency savings realization rates, boost customer satisfaction and increase program/service uptake.

In fact, in 2023, Bidgely’s global customer base of electric utilities and energy retailers surpassed one terawatt-hour (TWh) of energy savings through Bidgely’s UtilityAI energy efficiency programs, which has offset nearly 709,000 metric tons of CO₂ emissions. Those gains continue to accelerate. By 2028, Bidgely and our utility partners will have more than doubled energy efficiency returns, achieving an anticipated 2.6 TWh of savings.

Together, we’re achieving emission offsets that would require thousands of solar panels, hundreds of wind turbines, millions of dollars and many years of project development by instead enabling smarter usage and deployment of the grid today. And it’s all made possible through the power of data.

Detailed analysis of real-time usage directly leads to smarter consumption and deployment, creating a cleaner environment for all...

“For years we have expected the energy transition to be built largely with increased renewable energy production. The reality is our greatest weapon rests with smarter energy,” said Jen Szaro, President and CEO, AESP (Association of Energy Services Professionals). “Bidgely’s milestone is proof that having detailed analysis of real-time usage directly leads to smarter consumption and deployment, creating a cleaner environment for all.”

The Advanced Data Science Driving Efficiency Amplification

Every customer has their own unique DSM value. Understanding how to optimize each customer’s maximum savings potential is the key to achieving targets. Bidgely’s Analytics Workbench tool provides utilities with an in-depth understanding of every household’s unique load fingerprint -– i.e. what appliances are in use, the size and time of their consumption and/or demand, and how customers should be best targeted and incentivized to take savings actions.

Applying AI-powered analytics to meter data empowers utilities to target each customer with programs best suited to achieve behavior change to achieve the energy savings that the grid needs. Using these insights, utilities can meet customers where they are by providing personalized messaging based on that customer’s needs — treating customers as individuals, with individual energy savings and load shift opportunities.

For example, Analytics Workbench reveals whether a customer has an inefficient appliance, such as an AC unit that should be repaired or replaced, or an appliance that is healthy but being used inefficiently, and a smart thermostat could assist. Similarly, Analytics Workbench pinpoints pool pump usage, including both time of use and speed of the pump, enabling utilities to target specific customers with programs to replace single speed units with more efficient variable speed models, and/or run the pump in off-peak hours.

Maximizing efficiency savings also requires extending efficiency programs to all customers – not only those in the highest consuming homes. Using Bidgely’s patented disaggregation technology, Analytics Workbench identifies variables beyond high consumption to create superior treatment groups with the highest propensity to save. Maximum savings is determined by a combination of consumption, appliance usage, energy lifestyle, and behaviors — a customer profile that Bidgely’s advanced data science is better able to define.

The difference between legacy DSM approaches and Bidgely’s AI-informed practical, simple and personally relevant efficiency recommendation approach is significant, with an average 3% energy savings per household. With millions of households, this adds up.

Insights informed by granular household energy use data can empower utilities to make essential and immediate progress toward their ambitious energy efficiency goals.

As Krystal Maxwell, Research Director, Guidehouse asserts, “Machine learning, AI, and smart meter data enable highly targeted, strategic implementation of energy efficiency programs. This approach provides distributed energy resources (DER) integration, grid optimization, and increased energy efficiency to provide relief to a utility’s energy grid, while simultaneously providing bill savings to utility customers.”

Bidgely’s UtilityAI is EmPOWERing Collective Action

The proof of the power that lies in Bidgely’s advanced data science, is in the results industry leaders are seeing today.

Rocky Mountain Power, a Berkshire Hathaway Energy Company, achieved over 228 GWh energy savings at a cost savings of 25 percent compared to traditional energy efficiency programs by partnering with Bidgely.

Vice President, Customer Experience & Innovation for Rocky Mountain Power William Comeau commented, “The transition to a sustainable future is a partnership with our customers, and it’s data that helps us target offerings specifically to them from an energy efficiency standpoint. Having that partnership with our customers helps them reduce their load during peak times, helps us keep costs low overall for our customers, and long term, bring on more sustainable solutions.”

Adam Grant, Director of Electrification & Energy Services for NV Energy, another Bidgely partner that yielded 13 GWh energy savings in the first year and 40 GWh in its first three years of its energy efficiency program, reflected, “We work extremely hard to be partners with our customers; to teach them ways to use and ways to save energy. Because of the data and targeted aspect of what we’re doing, this is not blanket marketing: we take what we know about precisely where and why customers were inefficient and help them become more efficient.”

Boost Your Own DSM Gains

If you’re interested in maximizing the contribution your DSM programs make toward achieving your energy efficiency and decarbonization goals, learn more about how Analytics Workbench and Bidgely’s intelligent, next-generation energy efficiency programs can deliver measurable results today while also helping you build the grid of the future.

As consumers, we constantly receive targeted ads in our inboxes, social media platforms, search results and more that offer suggestions as to what we should watch, listen to, buy or attend. Those ads are typically very relevant to us and in line with our preferences, because advertisers know that this behavioral science based approach makes it more likely that we will 1) pay attention and 2) respond to their call to action.

This type of data-driven personalized outreach has transformed every aspect of the consumer marketplace. We’ve all come to expect that companies understand our wants and needs and will meet us where we are with tailored recommendations, and their energy providers are not immune to this expectation.

Recognizing that this mindset is driving consumer behavior is particularly important as the utility industry increasingly needs the partnership of their consumers to participate in peak events and otherwise help alleviate peaks on the grid. Today, behavioral demand response programs must be framed around data-driven personalization, especially when it comes to calling peak events. Meeting customers where they are with an understanding of their energy use needs and habits will translate into messaging that is more impactful and, by extension, ensure greater peak event participation.

Avoiding Peak Event Fatigue

For example, when extreme heat impacted much of the United States and the world during the summer and fall of 2022, utilities and government officials in California, Texas and elsewhere not only broke generation records, they also made headlines for asking their customers to curtail their usage to prevent outages. Their peak event outreach campaigns included mass text alerts, emails, and social media posts asking every customer to conserve. In essence, the messages said “we’re all using a lot of energy. Please use less.”

The good news is that, for the most part, it worked. Over the course of a few days, customers made what amounted to educated guesses as to how they could reduce their load, and utilities were able to avert mass blackouts.

But as extreme weather becomes more common and beneficial electrification continues to grow, consumers are going to be called upon to participate in peak events much more frequently and for longer periods. As those peak events become a more regular occurrence, blanket calls for non-specific actions will be less effective.

Without personalization and relevance, utilities risk creating a sense of “peak event fatigue” in which consumers become less interested in participating over time because calls to action are vague and don’t show consumers what behaviors they need to change.

Engaging consumers in the sorts of numbers that will be required to ensure grid resiliency without direct load control requires precise requests for specific and relevant actions. Utilities need to educate each customer about their energy use on a per-appliance and day-and-time-of-use basis so that they understand exactly how they can make a meaningful contribution to reducing grid load. It comes down to targeted messages with recommendations about specific behaviors sent at the right time to the right person.

Educate customers about energy use on a per-appliance and time-of-use basis so they can meaningfully contribute to reducing grid load...

Personalizing Peak Events

When it comes to providing consumers with energy insights that drive peak event participation, there are a variety of tools that can make a meaningful impact.

For example, when it comes to utility outreach, the goal is to evolve messaging from non-specific asks like “turn off or reduce nonessential power” to hyper-personalized and data-driven recommendations like “70% of your energy use is attributed to cooling during afternoon peak periods. Adjusting your air conditioning use during tomorrow’s peak event will help the grid. Pre-cool your home between 11 a.m. and 1 p.m. and then set the thermostat to 78 degrees until 6 p.m.”

On the self-service front, energy use activity maps allow customers to research their load profiles and learn which of their appliances use the most energy, and what days and times of day they use the most energy. With this personal level of detail, consumers are empowered with what choices they have at their disposal to make the greatest impact on the shift of their overall load. In the context of peak events in particular, an activity map empowers consumers to identify which of their energy use behaviors typically occur during the peak event time, and how they can change those behaviors to do their part to ensure grid resiliency. If the peak event is from 4 to 6 p.m. that day, and they typically charge their electric vehicle during that time, they know they can make a difference by shifting their charging to overnight instead of post-commute.

The guiding principle for all personalized outreach is that coaching consumers to change specific behaviors to outside the peak window will yield greater grid gains.

Leveraging AI-Powered Data Science

Establishing the one-to-one consumer understanding that serves as the foundation for this personalized approach requires sophisticated machine learning and statistical solutions to analyze raw energy consumption AMI data. Bidgely’s advanced Time of Use (TOU) disaggregation breaks down household consumption to previously indiscernible granularity. This breakthrough level of precision opens up a new world of customer engagement possibilities for energy providers.

Granular energy use insights allow every step of a customer’s energy use journey to be both hyper-personalized with a clear explanation of the benefits they’ll realize for taking specific action based on how they use energy. Optimizing customers for success in this way is not only essential for peak event participation, but also to more effectively guide customers through billing, time-based rates, ongoing energy efficiency and more.

Learn more about how Bidgely’s Flex Demand and Analytics Workbench solutions empowers utilities and their customers with relevant, actionable energy insights to more effectively engage consumers in managing peak load.

Effective load-shaping tools are becoming increasingly important as utilities continue to innovate their operations to maintain system-wide resiliency in response to evolving supply and increasing demand.

This urgent need to shift load is one of the major factors driving the transition from flat, volumetric rates to time-based residential rate structures that incentivize consumers to align their energy use with times of greatest supply and lowest cost generation.

When executed well, time-of-use (TOU) rates improve system utilization, reduce peak demand, and boost customer experience (CX) by empowering consumers to take charge of their energy costs and save money.

Though the promise is great, at the same time, the transition to time-based rates is complicated.

Consumers have paid a flat rate per kilowatt hour for electricity for decades. Changing to new rate structures can inadvertently lead to confusion and bill increases — which undermine CX and consumer trust in the utility.

With so much at stake, future-ready utilities are leveraging household energy use data analytics to inform their time-based rate design, rollouts, and ongoing management to avoid potential pitfalls and realize greater grid and CX benefits.

AMI-Informed TOU Rate Programs in Practice: Electric Vehicles

In an era of accelerating beneficial electrification, electric vehicle TOU rates are one of the most compelling emerging time-based rate use cases.

For many electric vehicle drivers, the ability to save money on fuel was one of the most significant drivers in their decision to buy an EV.

EV TOU rates provide EV owners with a way to amplify their fuel savings by charging their vehicles during off-peak hours when energy is the least expensive. In this way, utilities are in a position to offer EV-driving customers TOU rates that maximize fuel savings, which can translate into a big CX boost. And, at the same time, enthusiastic driver participation in EV TOU rates enables utilities to effectively shift load to avoid EV-related grid strain.

Bidgely’s advanced AI technology and AMI analytics provide utilities with the customer-specific vehicle insights they need to personalize each consumer’s TOU rate journey, making it a positive experience from initial enrollment through long-term participation:

1) Leverage Disaggregation as a Strategic EV TOU Input

As with any TOU rate, AI-powered disaggregation detection and insights should be the foundation for time-based EV rate design.

Bidgely’s smart meter energy intelligence reveals which customers have purchased an EV, when they are charging their vehicle, and what equipment they’re using to do so.

Leveraging these insights enables essential granularity of customer segmentation and price-differentiated periods, with rate structures tailored to a wider variety of EV-driving customers with distinct demand profiles.

2) Personalize Recruiting and Onboarding

As a fundamental customer engagement strategy, Bidgely’s EV Solution provides EV drivers with personalized monthly summaries of their EV charging habits and spending, including personalized tips to optimize their charging.

This ongoing collaborative engagement serves as an ideal time to promote TOU rate plans to those EV users who are not already enrolled.

Promoting and recommending the adoption of EV TOU rates requires that customers 1) understand the mechanics of a TOU rate and how it works; 2) understand how, based on their unique historical load and consumption habits, they could save money compared with their current rate; and 3) understand whether achieving the forecasted savings will require changes in current EV charging behaviors. Customers are more likely to opt into a time-varying EV rate plan when the advantages of doing so are explained in specific and relevant terms – with personalized targeting rather than mass marketing — including calls to action that are customized with personalized savings potential based on each customer’s vehicle, charging equipment, and charging requirements.

Customers who receive this type of rate education are most likely to want to participate in TOU rates and remain engaged, ultimately contributing more significant peak-time reductions immediately and over time.

Customers are more likely to opt into a time-varying EV rate plan when the advantages of doing so are explained in specific and relevant terms...

3) Provide Ongoing Personalized Coaching

The more EV customers embrace time-varying rates, the greater the gains in grid management, costs to serve, customer savings, and customer experience outcomes. But as with any new experience, EV drivers need coaching to make sure they are using their EV TOU rate effectively to achieve maximum load shifting and savings. As with program recruitment, one-on-one engagement makes coaching more effective.

Bidgely’s EV solution includes a wide range of continuous coaching tools, such as monthly bill projections, budget alerts, and weekly reports to track usage trends and avoid high bill surprises.

In addition, Bidgely’s peak alerts provide EV drivers with immediate corrective feedback on negative charging behavior, letting customers know in the moment exactly how much more they paid for the on-peak charge versus an off-peak charge. These specific dollar figures are useful to both prevent high bills as well as encourage the customer to shift charging in the future.

Bidgely’s self-service TOU rate research tools provide another essential means for customers to better understand how to optimize their EV charging behaviors. Energy activity maps provide easy-to-interpret graphs that track energy usage during peak and off-peak hours by time of use and duration. This visual representation of energy usage is a powerful way to build customer understanding as to how their charging habits equate to energy costs, and what steps they can take to achieve the greatest TOU benefit.

Precise, accurate, and timely engagement empowers drivers to optimize their TOU plan fully and derive the most advantage, while simultaneously delivering the greatest grid benefit.

4) Evaluate and Optimize

New rate designs can sometimes have unintended outcomes, highlighting the importance of real-time monitoring of their impact.

Conducting AMI-data-based analyses of existing EV rate plan outcomes can serve as an essential tool to understand how customers are responding to the new prices and to evaluate the need to change or modify EV rate designs.

Understanding how user behavior is changing compared to a control group or even compared to a customer’s baseline can build a powerful understanding of what strategies are working.

Analyzing EV charging patterns on an ongoing basis enables utilities to responsively refine rate design to maximize energy savings for both the utility and the customer.

Realize TOU Benefits Today and Over the Long Term

The promise of TOU rates to improve system utilization, reduce peak demand, and lower consumer costs is significant, but the transition necessary to achieve and continue to realize that promise is complex and requires a solid data foundation.

Bidgely’s patented data science for electric vehicles and other appliance-level grid insights enables personalized customer engagement and understanding that improves the long-term success of TOU rate programs.

To help utilities maximize the value of their AMI data to achieve TOU transitions, we’ve developed a Leveraging AMI Data for Successful Time-Based Rate Implementation playbook that outlines how to put energy intelligence to work to improve new rate structure development and implementation, including:

Phase 1: Rate Design
Phase 2: Recruiting and Onboarding
Phase 3: Ongoing Personalized Coaching
Phase 4: Program Evaluation and Optimization

To explore more best practices for EV TOU and other time-based rate implementation, download your copy today.

When it comes to selecting or upgrading a CX platform, many stand-alone point solutions claim the value of their platform comes from replacing multiple existing systems.

That can be a daunting prospect for an IT organization — both in terms of the switching costs as well as the timeline required for a multi-system migration.

Utility IT teams have already invested money, time, and resources in CIS systems, customer care and billing systems, CRM systems, digital self-service systems, and potentially even legacy customer experience solutions. Understandably, the idea of throwing all of that out and starting from scratch creates a significant barrier to entry.

By contrast, Bidgely’s perspective is that there’s no need to upend your organization in order to upgrade your CX platform.

If existing systems are performing well, there is no reason to replace them. Instead, the focus should be on supercharging existing platform capabilities and elevating the value of the entire IT infrastructure to get the most out of your investment.

A Single Source of Truth

Behind-the-meter energy intelligence derived from load disaggregation and non-intrusive load monitoring has the capacity to augment existing tech stacks to maximize performance. In essence, consumer energy use data becomes a single source of truth that informs and boosts the capabilities of technology platforms across utility operational areas. Household energy use data serves as the core building block for both the CX platform and the aggregate IT infrastructure.

With a uniform foundation of granular, highly accurate customer insights, energy providers can ensure that customers have a consistent experience across every touchpoint and channel in their utility customer journey, which boosts CX and lowers costs to serve.

Take CRMs for example. Call center agents answering calls from consumers typically have very little knowledge about what’s happening in a caller’s home. Instead, every call requires a discovery process.

Leveraging AI-based disaggregation technology, Bidgely is able to inject appliance-level insights about a customer’s usage into the call center system, equipping agents to quickly understand why the consumer might be calling, even before picking up the line. This energy intelligence leads to faster call resolution, reduced hold times, and more personalized customer experiences.

Beyond customer-facing technology applications, a smart meter data-informed CX platform can also better inform grid management and planning by making it possible for utilities to better understand what the load on the grid is today and is likely to be tomorrow. This intelligence is crucial to achieving transportation, home, and building electrification as well as distributed energy resource goals.

Seamless Technology Integration

Rather than introduce new technology systems, Bidgely’s CX Platform is a highly flexible solution that uses APIs and widgets to seamlessly infuse customer intelligence into the existing IT systems utility teams know well.

For example, our REST API Integration enhances a utility’s native mobile app with personalized energy insights. Our API Notification Integration enables a utility to send personalized insights via both email and SMS. Our widgets allow a utility to embed new CX features within existing web portals and call center systems to maximize customer personalization and relevance.

Seeking just this sort of flexible integration, Electric Ireland partnered with Bidgely to harness insights from its residential customer data to improve engagement across its existing digital channels. Bidgely’s insight tools were delivered as widgets that could be seamlessly integrated to improve email communications with tailored, customer-specific content and add personalized energy insights, individualized customer energy usage education, and recommendations to the energy retailer’s existing residential web portal. Nearly 33,000 customers accessed Bidgely widgets on the Electric Ireland residential portal during their first three months of availability, and Bidgely-informed email communications realized a 94.62% click-through rate, demonstrating customer enthusiasm for the deeper intelligence Electric Ireland was able to provide through its established channels.

A utility’s tech stack is always informed by the most relevant, actionable data, and IT system ROI is continuously maximized...

Future-Ready Solutions

The utility business model is changing rapidly, and it’s essential that a CX platform is built to evolve in response to emerging expectations from digitally centric customers and the transformative impact beneficial electrification, distributed energy resources, and other new technologies are having on grid operations. As utility needs and goals evolve, so too must their CX platform. Rather than implementing a CX platform for today, utilities need a CX platform that is always primed to deliver for tomorrow.

Unlike many static point solutions, Bidgely’s CX platform was designed to be dynamic. Customer energy intelligence continues to be enriched over time to reflect evolving energy use habits, preferences, and values. In this way, a utility’s tech stack is always informed by the most relevant, actionable data, and IT system ROI is continuously maximized.

For example, as beneficial electrification scales, managing load to maintain grid resiliency will become increasingly mission-critical for energy providers worldwide. The accelerating adoption of EVs, electric appliances, and DERs is creating a new utility-consumer dynamic in which consumers play a more active role in reducing stress on the grid during periods of high demand through direct managed charging, virtual power plants, and more. To accommodate this shift in business model, utilities will need to leverage smart meter data insights to deepen customer engagement. A CX platform capable of enhancing organization-wide IT systems with customer intelligence will be crucial.

Getting Started

In a crowded industry, there are hundreds of CX solutions vying for utility attention and promising to deliver the best results. The best platforms will deliver meaningful value by boosting the tech stack rather than disrupting it.

To help utilities evaluate their options, we’ve developed a Building a CX Platform Playbook with 10 practical criteria utilities can use to inform CX platform comparison, including those presented in this blog and more:

Criteria 1: Advanced Disaggregation for Meaningful Intelligence
Criteria 2: Personalized Insights for Higher CSAT
Criteria 3: Customer Empowerment to Enable Self-Service
Criteria 4: Bill Insight and Analysis Tools to Improve Billing Understanding
Criteria 5: Cross-Promotion to Increase Participation
Criteria 6: Support for Customers’ Decarbonization & Electrification Transition
Criteria 7: Digital Engagement to Reduce Cost to Serve
Criteria 8: Seamless Technology Integration for Ease of Implementation
Criteria 9: Call Center Support for CSRs Empowerment
Criteria 10: Proven Track Record to Build Confidence

Download the playbook today.

When it comes to decarbonization and beneficial electrification, the surging electric vehicle wave has received most of the attention.

But reducing building emissions is an equally and increasingly critical part of the solution. In fact, energy use by homes and buildings contributes approximately 27 percent of global CO2 emissions – much of which stems from heating and cooling.

Without question, home and building decarbonization is foundational to achieving emissions goals. Not only is it a critical element of the carbon reduction equation, but the gas prices and political volatility have also elevated home and building electrification to a matter of global security and economic stability.

Many European countries are pivoting away from Russian energy imports and seeking non-fossil-fuel-powered cooling and space and water heating alternatives. In the United States, government officials used the Defense Production Act to ramp up heat pump production in the saying that over-reliance on fossil fuels leaves the United States and its allies vulnerable to threats and price shocks. Further, the U.S. Inflation Reduction Act included 10 years of tax credits and other incentives designed to make clean energy technology more accessible, including reducing the cost of heat pumps and electric water heaters.

But even as world leaders and energy providers increasingly prioritize home and building electrification, the majority of consumers aren’t yet on board.

The first barrier is that heat pump technology is not well understood — especially in terms of its viability for a wider-range of customers. Second, there is little consumer appetite to replace working HVAC or water heaters until their existing fossil fuel systems reach their end of life.

Globally, energy providers are in various stages of developing, getting approval and enacting beneficial electrification plans. Their progress is heavily influenced by customer expectations, fluctuating regulations, and their roll out of AMI infrastructure, meter data management systems (MDMS), generation management systems (GMS), demand response management systems (DRMS) and other technologies that facilitate beneficial electrification progress.

But no matter where they are in the process, there is a common understanding that customer engagement is perhaps the most important lever to achieving their goals. Engagement in the form of data-driven personalization, alignment and motivation is what it takes to inspire consumers to take action.

Personalize: Understand and Engage Customers Individually

Leveraging Bidgely’s patented disaggregation technology, utilities can look behind the meter to each household’s appliance-level energy use. Bidgely’s Analytics Workbench business intelligence platform delivers energy intelligence that enables utilities to rapidly run queries on appliance ownership, time of usage and appliance efficiency; and filter those queries by date range, appliance type, rate class, geography, premise type and customer communication preferences.

Not only does this hyper-targeting make customer engagement by location, appliance ownership or time of usage possible, but also by type of observed behavior — such as higher-than-average cooling, heating or hot water usage.

For example, when it comes to determining which homes should be targeted for heat pump programs, understanding which homes have electric heating and which homes have gas or oil-based heating is an essential first step. Similarly, it’s important to understand whether a household is currently operating window, mini-split, portable or central air conditioning. Then, since appliances often start consuming more energy as they approach end of life due to degradation, utilities can also run queries to identify changes in the duty cycle curve or other cycling patterns to identify inefficiencies and optimal targets for replacement programs.

Align: Offer Relevant, High-Value Insights and Programs

Utilities can leverage appliance-level energy use insights to personalize both digital and paper communications in support of home electrification goals.

At a foundational level, personalized outreach could include sending individualized monthly energy reports that show customers how their actual energy usage – itemized by time and appliance – is impacting their monthly utility bill.

Customer-facing web portals can also be enhanced to deliver insights about how a customer’s heat systems are impacting their energy costs and provide dynamic appliance-based similar home comparisons or calculate potential savings (CO2 and/or $) they could garner by switching to a more efficient appliance. When taking over incumbent programs, our utility partners often share that they have previously received customer complaints regarding inaccurate comparisons (different size homes, homes with different appliances, etc). Bidgely reverses this trend using a dynamic machine-learning based approach which results in comparing customers to more appropriate similar homes. Bidgely SHC algorithms dynamically recluster homes as heating fuel type or appliances change. This approach makes it possible for energy providers to realize simultaneous gains in CSAT and energy savings.

Energy providers can then layer on one-to-one outbound education and marketing outreach that highlights the most individually relevant benefits of heat pumps. Promotions can also include customized purchasing recommendations, such as those for rebates and installation professionals. And for inbound channels, Bidgely’s electrification insights turn call center agents into energy advisors who are better equipped to provide relevant information and recommendations when customers reach out with concerns about energy costs or questions about promotions they may have received.

The accuracy of our data science ensures that the insights and messaging customers receive are correct. Demonstrating a clear, measurable, short-term and easily attainable personalized appliance ROI is one of the most effective ways to accelerate beneficial electrification.

Motivate: Inspire Customers to Take Action by Aligning With Their Needs and Values

Presenting the right information to the right people is only half the equation. The other half is motivating them to take action, which happens by connecting with the needs and goals that matter to them the most.

Making the decision to electrify appliances is driven by a variety of personal factors, including economic and environmental motivations, and more. Energy providers can more successfully capture customers’ attention and prompt action using personalized marketing that aligns with each customer’s needs, unique circumstances, and values.

Customers who are motivated by sustainability, energy efficiency, savings, and comfort should be messaged differently...

Customers who are motivated by sustainability, energy efficiency, savings, and comfort should be messaged differently. An environmentally conscious customer will find carbon reduction impacts most compelling, while a savings-minded customer is likely to respond best to messages about incentives available to mitigate the costs associated with converting. Further, customers who have already embraced solar and/or electric vehicles are likely to be interested in how switching to a heat pump will further beneficially electrify their life.

Bidgely’s analytics reveal customer lifestyle and value insights that provide utilities with the essential context to authentically connect with their customers with messages that resonate.

It’s important to note that utilities can also leverage customer energy use insights to drive other beneficial electrification measures that align with their own needs and goals, whether those are driven internally, or externally through variables like new regulatory requirements, investor relations or public expectations.

Boost Your Building Electrification Outcomes

Data science empowers utilities to Personalize, Align and Motivate, thereby achieving home and building beneficial electrification goals on or ahead of schedule. Learn more about how AI can amplify your home and building electrification initiatives with our Heat Pump Adoption and Beneficial Electrification Playbook.

Utilities around the world continue to struggle with energy theft, with an estimated $80 to $100 billion lost globally to theft each year.

In India, some DISCOMs report losing as much as 25% of their total revenue to theft. In the United States, the US Energy Information Administration (EIA) estimates that electricity transmission and distribution losses were about 5% of the electricity transmitted and distributed in the United States between 2016 and 2020. In Jamaica, electricity theft is estimated to cost the Jamaica Public Service Company $200 million – 80 percent more than a decade ago.

Matt Copeland, head of policy and public affairs for National Energy Action in England, said in August 2022 that the problem is getting much worse. “The staggering increases in the cost of energy is leading to desperation. Some households… are resorting to electricity theft, which is illegal as well as dangerous.”

Beyond the substantial economic impact, theft impacts grid reliability by manipulating local area supply, which can lead to transformer overloading, blackouts, damage to utility assets, poor customer experience and safety vulnerabilities.

On every continent, theft is a significant challenge, with rising energy costs and new energy-intensive practices like bitcoin mining causing it to escalate even further.

Mitigating Theft With AI

With an expected 1.3 billion smart meters to be installed globally by 2025, energy providers now have the opportunity to leverage the trillions of granular AMI data points those meters produce to accelerate transportation electrification, improve customer engagement, advance decarbonization and enable bottom-up grid planning for greater resiliency and reliability. But for many, one of the most exciting applications of AMI data is revenue protection. In fact, combating non-technical losses is one of the primary drivers behind the massive 250M smart meter roll out now underway in India.

Historically, apart from basic meter hardware tamper alerts, broad-scale theft detection has been a top-down approach implemented at the grid level. This high-level view has been limited to assessing groups of homes associated with a single substation — for example, the 100 homes on a particular feeder/ substation — and flagging that group for review. The resulting investigation process often takes days or weeks to resolve in the field. Beyond that, there has been no consistently accurate means to pinpoint exactly which of those 100 customers are bad actors.

Now, however, Artificial Intelligence (AI) makes it possible to process data in hours, not days, and, like a detective, provide a clear, data-driven picture of exactly what is happening behind each meter. For the first time, energy providers are empowered with accurate and precise information about each meter upon which they can act to deter theft.

Bidgely’s Energy Theft Solution

Bidgely’s AI-based analytics — backed by 17 energy-specific data science patents — center on disaggregating consumption data. This data science makes it possible for utilities to conduct theft analysis home-by-home, at the appliance level, rather than only at the transformer level.

By analyzing historical AMI data and correlating it with external factors like weather, AI-derived occupancy, and appliance/lifestyle profiling, Bidgely’s Energy Theft Detection Solution makes it possible to identify consumption-related anomalies that signal theft has or is occurring. Anomalies in appliance-level consumption patterns accurately reveal theft via meter bypassing, meter tampering, tariff misuse and more.

Meter Tampering
In cases in which electricity thieves take steps to prevent energy consumption from being recorded, our AI algorithms leverage energy consumption patterns, technical parameters of phase currents, neutral currents, voltages, power factors and available smart meter events to identify where and how meter tampering is most likely to have taken place. Tampering patterns include notable drops in consumption with corresponding electric anomalies.

Direct Theft
When consumers bypass the meter using an illegal connection mechanism, consumption patterns might flag such anomalies as when there is a change in outside temperature but no corresponding change in electrical use — i.e. when a heat wave occurs but there is no increase in cooling-related electrical use. Our analysis also looks at characteristic energy use for all homes with similar sanctioned/connected loads to identify significant outlier homes.

Tariff Misuse
Because smart meter data analytics isolate appliance-level signatures, it is possible to accurately distinguish between residential appliance behavior and commercial appliance behavior and identify patterns indicative of commercial activity on a residential tariff.

Targeting Bad Actors
Beyond smart theft detection, Bidgely’s advanced data science categorizes theft incidents and bad actors as high, medium or low probability and estimates how much energy loss occurred during an anomaly period. Our analytics also reveal the duration of theft activity and how many times the behavior was repeated — information a theft inspector cannot determine in a visit to a tampering site. This loss analysis enables utilities to focus mitigation efforts on the most significant violators and prioritize high probability and high value cases to ensure the highest possible return on investment to ensure the greatest theft mitigation success and return on AMI investment.

Bidgely's loss analysis enables utilities to focus mitigation efforts on the most significant violators & prioritize high probability and high value cases...

In-The-Field Validation

Bidgely has been selected by REC Ltd., a CPSE under MoP, GoI to participate in Ministry of Power, GoI Technology Incubation Challenge Powerthon 2022, which was organized in collaboration with SINE incubation lab of IIT Bombay. Our category is AI/ML based data analytics of consumer power consumption/ behavior and detection of theft for energy in support of the National Revamped Distribution Sector Scheme (RDSS) to reduce losses of State DISCOMs in India to 12-15% by 2025.

Through this challenge, we have engaged in a theft detection effort with a state utility to further demonstrate how AI-enabled data analytics can detect and resolve India’s energy misuse issues. At the same time, we’re working with a large utility in central India — in collaboration with the World Bank — to further prove theft detection analytics use cases.

The New Standard

Household-level energy theft detection enabled by artificial intelligence is setting a new standard. As the leader in energy disaggregation, Bidgely’s Energy Theft Solution enables utilities to not only see and understand loss with precision and accuracy, but also evaluate its severity and impact on revenue. Our results promise to significantly benefit utility revenue, grid performance, customer experience and safety.

To learn more about how Bidgely can help you successfully combat theft, visit our Energy Theft Solution knowledge center for a full library of solution briefs, playbooks, videos and more.

Utilities are making solid strides in small-scale DER integrations. While efforts like these are helping with grid modernization and beneficial electrification efforts, the scale of the current challenge requires a more ambitious approach than proof-of-concept deployments and pilot electrification projects.

DER deployments will accelerate as cost of ownership continues to fall and wholesale markets unlock additional benefits, whether utilities choose to take an active role or not. And, the longer utilities wait to engage DERs at an enterprise level, the more difficult and expensive it will be to coordinate and manage rapid DER expansion on their grids.

Bidgely offers utilities a roadmap to successfully navigate — and more importantly benefit from — the DER revolution.

Locate and Analyze DERs on Your Grid: Penetration, Location, Capacity, Activity

Energy providers need to know where DERs are located on the grid, their size, and how they’re being operated — preferably on a real-time or near real-time basis. This is especially true for customer-sited DERs and behind-the-meter DERs, where utilities typically have little to no visibility.

Applying sophisticated algorithms to AMI data makes it possible to learn how customer net generation is moving onto and off of the grid, and understand the characteristics of their residual behind-the-meter demand across household appliances and mechanical systems. Bidgely’s patented disaggregation algorithms powered by our UtilityAI® platform deliver a high fidelity profile of every end-use present in a household or small business. Utilities can determine with certainty if and how a customer is using a PEV, a rooftop solar system with battery storage, a heat pump water heater, and more.

Utilities typically rely on grid monitoring and analysis tools that focus on the distribution system and go as deep as the low voltage lines. That approach only shows half the picture. Demand data disaggregation and analytics are critical additions to the tool kit for any utility that’s serious about planning, deploying, and operating a two-way communicating, decentralized grid. Just because the traditional distribution system analysis shows you CAN invest in a distributed resource at a certain location, doesn’t necessarily mean you SHOULD.

For example, a hosting capacity analysis may show that a feeder can handle an additional 15 MW of distributed capacity, so a third party solar developer signs up to build it. However, disaggregated load data may reveal that most of the non-shiftable load on the feeder doesn’t match well with the duck-curve load the solar resource will provide. Or it reveals that there is an additional 10 MW of behind-the-meter DERs on the feeder that could be utilized to boost the hosting capacity to 25 MW, allowing additional technology types and configurations for utility DERs deployments on the feeder. Or, maybe the disaggregated data reveals a consistent end-use demand on a different feeder that more closely matches the export load shape of the solar resource offering a more efficient and effective deployment location.

Bidgely’s near-real-time DER usage behavior, pattern and trend data provides utilities and regulators with a single source of truth...

Get in Front of Wholesale Energy Markets Opening to DERs

Wholesale markets have already started opening to DERs this summer, and third-party aggregators are already on the scene signing up utility customers into their own wholesale programs. There is an urgent need right now for utilities to get a handle on who is participating and how. It’s possible that a utility that fails to fully engage in this opportunity might one day buy day-ahead, or spot market wholesale power aggregated from its own customers.

That example may seem far fetched, afterall FERC Order 2222 requires extensive coordination between distribution utilities, RTOs/ISOs, aggregators, and state regulators in order to streamline the integration of DERs into wholesale markets. And utility scale DERs deployments will be captured through interconnection agreements, and monitored through the inverter technology required to connect them to the grid.

But what about all the customer-sited and behind-the-meter DERs? Bidgely’s near-real-time DER usage behavior, pattern and trend data provides utilities and regulators with an invaluable single source of truth that ensures all parties are on the same page.

As well, this new policy reality is creating a blurred line between wholesale and retail markets, and it’s essential to equitably allocate costs between retail customers, DER owners, and aggregators. Bidgely’s data science empowers utilities to create granular and nuanced rate structures to successfully balance cost recovery — maintaining a safe, reliable grid system, and appropriately compensating DER owners for their resources. Bidgely’s DER insights inform responsive and hyper-targeted tariff structures to avoid a mismatch between rates and cost to serve, mitigating concerns over cross-subsidization and ensuring equity goals can be achieved.

Rethink Demand Response

Analytics-driven demand response programs have the power to alleviate congestion on transformers and substations in a more agile and scalable way by shifting the highest propensity end-uses within a given load profile and location.

For example, legacy demand-side management approaches might offer all customers within a congested area an incentive to shift their EV load. But not every customer in that area will have an EV, and among those who do, it is likely that many are already charging off-peak (or at public stations/work). Bidgely’s AI-powered data analytics allow energy marketers to pinpoint which customers have an EV and when they are charging at home. With those insights, energy providers can focus demand response programs to compensate these customers in proportion to their load contribution to realize greater grid benefit.

Demand response programs must also evolve from focusing unilaterally on reducing load to a two-way provision of flexible load and supply. BIdgely’s more agile and hyper-personalized approach to customer engagement plays an essential role in empowering utilities to influence where, when, and how customers use energy.

Accelerate Grid Modernization Timelines

Current “business as usual” approaches to grid modernization and beneficial electrification are likely to take 20-plus years to complete, in direct conflict with more aggressive decarbonization timelines.

To accelerate this progress, Bidgely is working with utilities worldwide to leverage their AMI data to develop bottom-up, baseline views of their grids and plot roadmaps for truly distributed, two-way communicable grids. With a data-enabled foundation, it is possible to scale DER investments very quickly and shrink modernization timelines to 10 years or less.

The Time to Act is Now

Energy customers are deploying DERs at an increasing pace, and rules like FERC 2222 and massive investment programs like the IRA and IIJA are unlocking new revenue streams, which will have many third parties vying to engage customers in aggregation and integration programs that promise to ramp DER adoption even faster.

That’s why immediately harnessing demand data to catalog and deploy the variety of energy services DERs provide, and scale and optimize DERs across the grid is an imperative.

For more DER program strategies, download the full Navigating the Distributed Energy Resources Revolution: A Playbook to Guide Grid Modernization and FERC 2222 Compliance. Behind-the-meter, demand-side data has the power to enhance outcomes and increase the value of distributed resources utility-wide, but the time to act is now.

As electric vehicle adoption accelerates at an exponential rate, how can utilities maximize grid benefits, customer satisfaction and revenue? Scaling readiness for transportation electrification requires an intelligent, analytics-driven strategy.

In the third episode of Bidgely’s 2022 Engage+ video series, host Neil Strother has a conversation with Charles Spence, Customer Programs and Products Manager at Avangrid, to explore how utilities can leverage meter intelligence to design long-term EV strategy that is both cost effective and flexible.

“We know these EVs are coming, and they are going to be a demand on our system,” said Spence. “Our biggest challenge is obviously integrating that load both on a volume basis and on a timing basis. The issue there being that the system is designed for those peak moments, and we have end-of–day peaks already, when people come home, they turn on their AC, TV, all these things, and now when they plug in that EV it will create an issue where it’s not just the volume, it’s the time. That is what we’re trying to do with our demand response managed charging programs.”

Spence emphasized that data analytics is serving as the foundation for Avangrid’s EV approach.

“We’re interfacing with a lot of different types of people, usage patterns and new technologies, and we have to be able to understand what’s going on on a very granular level, specific to each customer, in order to predict what they are going to do what and how they are going to interact with the programs or platforms that we create. That’s why we leverage data all along the way,” he explained. “It informs programmatic changes and platform changes, from offering new features or incentives to tracking each customer’s progress, and then being able to aggregate those insights to see how our program is performing compared to the goals that we have. Ideally, these insights allow us to adjust on the fly if things are not going the way we want them to.”

We leverage data predict what a customer is going to do and how they will interact with the programs we create...

Spence went on to describe what his team is learning through one of Avangrid’s first demand response charging programs – a Bidgely partnership.

“In Connecticut we have 100% or close to 100% AMI coverage. So we are able to utilize that household energy data for a number of different purposes – primarily through disaggregation. We’re able to pull apart that historic data, identify people who likely do have an EV and offer those customers opportunities,” he said. “We are able to then see which customers are on the more constrained circuits and say, ‘Hey, that neighborhood has 20 Teslas in it, let’s see about getting them into the program.’ For our demand response programs, we’re able to verify if somebody is participating or not, and when they receive price signals, if they actually respond or not. Because we can see where EV use is concentrated, that data also guides us in upgrading the grid in a given neighborhood or section of our market.”

Spence went on to talk about the many flavors of managed charging programs that are possible, ranging from pure demand response to more active managed charging.

“The program we’re initiating with Bidgely in Connecticut is a pure demand response program, which you could consider to be a subset of the broader managed charging umbrella. We’re looking at how we integrate EV load and time it well,” he said. “On the one hand, you could do a demand response event a few times a month, during very specific hours in a day, for which customers receive a warning ahead of time. On the other hand, you could have a more active managed charging program in which the customer sets the amount of charge that they need, and they tell us what time they need that charge. And then we use smart algorithms to facilitate that charging on a very granular basis -– more so than just turn it off for two hours, turn back on after those two hours. Through that active managed charging, we will be able to get that new load under control. That’s what we’re working on with Bidgely right now.”

When it comes to lessons learned, Spence said that Avangrid, like energy providers worldwide, is still evaluating best practices.

“I think the industry is trying to figure out what works best for what contexts in what territory,” he acknowledged. “Every territory is different. Some have more constrained circuits and some need more heavy-handed programs than others. For this first year of the program, we’re setting ourselves up to be able to do a maximum of 15 events per month. I doubt we’ll ever call that many in a month, because that’s one every two days. But we’re giving ourselves that ability to be able to test with a couple groups of customers. For example, one group might get one event and then one immediately the next day. Another might get one on Monday, and then on Wednesday. A third might get one on Monday, and then one on Thursday. We want to see how participation does or does not drop off. If it does, we’ll be able to make programmatic changes and really get some great insights. We’re trying to build understanding for everyone in the industry at this point.”

Spence went on to discuss Avangrid’s next managed charging program roll out in New York state.

“We are soon going to be launching a very similar program in New York, except that we’re adding managed charging to the demand response,” he described. “We’re giving customers the option to either respond to signals on a basic level where they might earn if they decide not to participate on a given day. Or, they can opt-in to a more active managed charging program where people are earning more, but are also expected to allow us more flexibility to control their vehicle to a greater degree.”

Looking down the road past the program evaluation phase, Spence says Avangrid is simultaneously planning for the technology available today as well as what’s on the horizon – including how energy providers and consumers will increasingly work together.

“In terms of the broader strategy, we are thinking about the managed charging and the demand response programs that we can implement now. But we’re also cognizant of the fact that there’s vehicle-to-grid technology coming soon,” he said. “The vehicle-to-grid stuff is excellent. It’s an opportunity to evolve the utility customer relationship to a point where, rather than us selling kilowatt hours exclusively, consumers will also be able to sell them back to us. And we’ll have a nice little dynamic there.”

Spence said he is also looking forward to the broader adoption of telematics and its potential to inform grid planning.

“Telematics basically gives us the use of the onboard EV computer. Some models have a stronger capability where you don’t only see the data, you can also turn the charger on and off, and understand where people are charging and how much they’re charging. We’re using telematics not only for direct load control — where we turn off charging for a demand response event or throttle it slightly — but also to understand charging behavior outside the home charger. Most charging happens at home, but there is 20 percent-ish that happens elsewhere. And that is huge. Public charging generally occurs in constrained urban areas, which are the same places where grid upgrades are most expensive and the most disruptive to people’s lives. We want to avoid digging up concrete as much as possible. If we’re putting level-two, or even DC fast charging out in these contexts, we want to know who’s using it, when they’re using it, and how they’re using it. And telematics enables that.”

Spence pointed out that, because Avangrid is a subsidiary of the global Iberdrola group, they have a unique advantage in that they can learn from the EV experience of their European counterparts.

“We do get quite a bit of support,” Spence acknowledged. “We know that folks in the various European countries are there to answer questions and we can count on their assistance with EV messaging and knowing how to position EV programs in a way that speaks to people both in a value sense, but also in empathetic sense, to improve engagement.”

When asked what it takes to get EV strategy right, Spence replied that, “There are all sorts of ways we could measure success. Fundamentally, we have to get the load integrated and timed properly. But beyond that, we have to really work through that change in the utility-customer relationship. We have to move from an approach where we just send a bill to one where we have a little bit of back and forth with our customers. If we’re going to integrate the load that we are expecting, we have to have participation and buy-in from the customer, and that requires trust, ease of participation, meaningful insights, and lifestyle and financial help as well. If we’re, for example, going to get somebody to, on a regular basis, let us turn off their EV charging for a couple of hours several times a month, they need to know that we are going to be providing them with value — both monetary and lifestyle.”

If you’d like to hear more from Avangrid about its data-driven EV strategy, watch the full Engage+ episode on demand and sign up now to receive updates about future episodes.

Load forecasting has always been a mission-critical discipline for energy providers.

Accurate demand forecasting enables critical utility functions ranging from purchasing energy at a lower cost, avoiding black and brownouts, developing dynamic rate structures and implementing more effective demand response programs.

But as the grid grows exponentially more complex, accurate demand forecasting is becoming more challenging, and a greater imperative, than ever before.

Distributed energy resources like solar and wind are shifting the predictability of energy generation, while an increasing number of consumer electric vehicles (EV) and large-scale EV fleets are introducing more variability and greater peaks on the demand side.

Thankfully, new AMI data is at the same time expanding and improving the accuracy of the insights energy providers are able to draw upon as part of their grid planning process. AMI analytics enable more accurate predictions of future load patterns, more effective grid-stabilizing customer behavior strategies and more successful management of distributed energy resources.

Top-Down vs. Bottom-Up

Historically energy providers have only been able to evaluate energy usage at the substation level, or in some cases, at the feeder level.

Now, by applying AI to smart meter data, utilities are empowered to understand load at the per-home or per-appliance-use level. While all usage may look the same at the substation level, it’s certainly not the same at the home level.

Applying AI to smart meter data, energy providers can define the foundational building blocks of service territory energy use: the consumption of individual appliances within a home. This bottom-up approach to grid management enables a deeper and more granular understanding of usage.

A bottom-up approach to grid management enables a deeper and more granular understanding of usage...

Granular Data to Inform Big Picture Strategies

AMI-derived household energy use data enables energy providers to cost effectively create highly accurate and comprehensive appliance-level energy use profiles for every residence. These profiles reveal essential load research data inputs, including such things as:

Which homes have EVs and who is charging during peak hours
Which homes have inefficient or degrading HVAC systems
Which homes have pool pumps and whether they are single or variable speed
Insights into appliance health

For example, as soaring temperatures strain grids across much of the northern hemisphere, a precise understanding of HVAC and pool pump usage and appliance health can inform impactful demand response programs that effectively engage customers to better reduce load.

NV Energy approached demand response with these goals in mind.

“We ran into some really good opportunities to target our customers and get the most value out of our customers based on AI-powered intelligence that told us when specific appliances were using more energy than their neighbor’s appliance or than a properly functioning appliance should have been,” explains NV Energy’s DSM Program Delivery Manager Adam Grant. “Maybe there was something wrong with their air conditioner, or we could tell that they had a single speed pool pump vs. a variable speed pool pump. Those insights gave us an opportunity to offer a solution to customers who either have a problem or who don’t have the equipment that is most optimal or most efficient. We could take what we knew about precisely where and why they were inefficient and try to help them become more efficient.”

Using Bidgely’s Analytics Workbench bottom-up load research and customer targeting capabilities, NV Energy piloted an HVAC efficiency program that identified 50,000 customers not already engaged in a utility program who would benefit from HVAC replacement based on certain high HVAC energy usage patterns.

Based on the success of the HVAC program, NV Energy built a similar Energy Efficient Pools and Spa program. Analytics Workbench was used to disaggregate AMI data to reveal pool pump appliance ownership and consumption and identify single speed pool pump owners who had the highest savings potential. The utility targeted this group with outreach to encourage upgrades to more efficient devices. At the same time, they sought to identify which homes were running their pool pump during peak hours as priority targets for the utility’s load shifting initiatives.

“There are 200,000 pools in southern Nevada and only 20 percent of them are efficient so far,” explains Grant. “So we used household energy use data to identify the most inefficient pools with high energy usage pool equipment. We targeted those 75,000 residential customers, telling them, ‘You seem to be using a lot of energy for your pool, we can help you.’ It was incredibly successful.”

Aggregating Appliance-Level Energy Use Data to Realize Segment-Level insights

Appliance-level insight building blocks can then be aggregated to provide actionable intelligence at both the customer-segment and grid-asset-levels -– such as in connection with a specific feeder or substation.

Bidgely worked with one utility in the Pacific Northwest to leverage disaggregation to map all of its customers to grid assets — first to specific feeders, and then those feeders to substations. The utility’s goal was to assess whether its existing feeder mapping would be able to withstand additional DERs, or if it should consider reconfiguration. Starting by disaggregating the energy use data for every household in the service territory, Bidgely empowered the utility to visualize the load on each of its feeders and other assets, and then assess whether any of the customer sets should be moved to a different feeder to optimize grid operation. This bottom-up approach to load research revealed essential grid management strategies to improve resiliency and avoid unnecessary infrastructure upgrades.

Iteratively Identifying Trends

Real-time, AI-powered customer energy use data analytics capture essential aspects of a customer’s energy use behaviors over time, and reveal the variation in customer behavior or occupancy at different points during the year. Customer profiles reflect current household conditions and how they have changed from one month to the next, including the impact of unexpected environmental and societal events.

The ability to track customer energy use on an ongoing and iterative basis makes it possible to identify emerging and growing trends before they impact grid operations to enable more accurate and strategic planning.

For example, in the case of electric vehicle grid planning. AI-powered data visualization allows teams to pinpoint where constraints may exist or develop.

Harnessing Bottom-Up Planning Potential

The grid is only going to continue to grow more complex in the years and decades ahead. Those utilities that can tackle this complexity with tools to simplify grid management will remain the most nimble in the face of change. By turning appliance-level energy consumption data into actionable intelligence, utilities can predict future load patterns, encourage grid-stabilizing customer behaviors and successfully manage distributed energy resources.

Learn more about bottom-up grid planning practices by downloading Bidgely’s AI-Powered Data-Visualization Playbook for Load Research and Grid Planning.

Against the backdrop of Houston’s extreme weather and vulnerable communities, CenterPoint Energy has prioritized strong resiliency and electrification strategies to maintain its status as the energy capital of the world. The key to both, they have determined, is a multi-stakeholder approach.

In the second episode of Bidgely’s 2022 Engage+ video series, we traveled to Texas to sit down with CenterPoint Energy’s Vice President of Energy Solutions and Business Services Elizabeth Gonzalez Brock to learn more about how the utility’s Reliance Now and EVolve Houston programs have engaged industry and community leaders in developing collaborative solutions to Houston’s greatest energy challenges and inform their grid planning with diverse perspectives.

Watch the full Engage+ episode on demand.

“In the Houston region, we’ve had seven national declared disasters during our current mayor’s six-year administration. We also have a lot of data that tells us that storms are coming with more frequency and more intensity,” said Brock. “An important part of what we do with that information is considering the question of equity versus equality. When we built our system, we built it for equality. We wanted to make sure that all of our customers were treated equally. But equity tells a different story. Not all customers have the same needs. Critical infrastructure like hospitals or grocery stores, and vulnerable low income, elderly and disabled customers and regions that experience the brunt of extreme weather most often experience a greater impact. So just having a good understanding of what our customers’ needs are is really important.”

Brock shared that CenterPoint believes when you’re solving big problems, you don’t solve them on your own. It’s that point of view that guides their approach to building the grid of the future.

“It’s not one company, not one utility, that can solve the problem of resiliency,” she said. “We need to bring our community together and get inputs from various sectors so we know how to best serve them. That’s why we developed a customer advisory panel to help us understand what the critical needs are. And we have used those inputs to inform our business decisions and make sure that we’re thinking about the future the right way.”

When it comes to advice for other energy providers worldwide, Brock said there were several key lessons learned from CenterPoint’s approach.

“First, communication is key. People want to know what happened. People want to know what you’re going to do to fix their problems. They want to know what’s going to be different next time,” she advised. “You also need community advocates. We’re working on building a more resilient city. But in order to do that, we need people to advocate for essential changes and new infrastructure. Finally, you need to be able to agree on how we’re going to optimize our funding. So whether it’s through seeking federal dollars, or whether it’s advocating at the PUC, or at the legislature, or even making our own customer investment. Energy providers need a strategy around how to pay for all these things that we want to do.”

When we built our system, we built it for equality. We wanted to make sure that all of our customers were treated equally. But equity tells a different story...

CenterPoint is demonstrating the benefit of this approach through its Resilient Now initiative – working with the City of Houston to create a master energy plan for the city that will preserve its reputation as the energy capital of the world.

“Resilient Now began with a conversation with our largest customer — the city of Houston — about how we can better serve their needs and align our business objectives and goals around their aspirations,” said Brock. “Together we explored what we need to do to ensure a more sustainable future. But also, how do we look at resilience? The “now” piece is crucial. We’re prioritizing shovel-ready projects that can instill confidence from our customers and our region. And we have put together a framework that enables us to communicate together with a united voice when we speak to our customers and the city’s constituents. We’ve gotten a lot of positive feedback about Resilient Now with other stakeholders and communities outside Houston wanting to join and give inputs. It’s another of those huge problems that we’re not going to solve by ourselves, so we need as much input as possible so that we can plan for the future.”

CenterPoint has tackled transportation electrification in the same way.

“We need to understand what our investment requirements are going to be if electric transportation takes off,” emphasized Brock. “You’ve got to think about all the things that can be electrified. Everything from ports, equipment, forklifts, cars, buses, rail — all of that electrification is included are in our C&I, customers’ 2030 goals. Part of the Resilient Now planning process is understanding what our infrastructure requirements will be. But at the same time, we’ve started a nonprofit called EVolve Houston. EVolve Houston is a 501c3 with a mission to improve air quality by enabling electric transportation. Getting our 501c3 for air quality was a huge accomplishment because it hadn’t been done before. We decided to go the 501c3 route, because it was important for fundraising — to be able to get charitable dollars and make it possible for businesses to invest. It is an extra bonus for our commercial partners to be able to use monies from either their foundation or corporate contributions. I absolutely recommend this approach to other utilities because it is a way to support a good cause that aligns very well with your business goals.”

EVolve Houston’s founding members include University of Houston, the City of Houston, NRG, Shell and CenterPoint Energy. A wide range of other transportation electrification stakeholders have also come on board, including BP, Buc-ees travel centers, Uber, the Texas Auto Association, and Houston Metro and the roster continues to grow.

CenterPoint’s stakeholder engagement strategy is serving them well in pursuit of both resiliency and sustainability.

“For example, we’re really excited that the Texas legislature authorized us to develop a load management program,” she said. “If we find ourselves in a situation where we need load, large industrial customers can volunteer to go offline so that we can have that additional capacity to serve residential customers. We have tested the program as part of an initial phase one and we are focused on strategies to sign up a lot of C&I customers, because it’s a volunteer program.”

CenterPoint’s inclusive approach to resiliency, sustainability and grid planning offer valuable lessons for utilities worldwide that are developing their own future-ready strategies. In Houston, inviting diverse stakeholders to co-create and implement unified energy solutions is delivering results that will help Houston reinforce its position as the energy capital of the world.

If you’d like to hear more about the CenterPoint resiliency approach, watch the full Engage+ episode on demand and sign up now to receive updates about future episodes, including episode 3 in July when we will speak with Avangrid’s Customer Programs & Products Manager Charles Spence about Avangrid’s approach to designing an intelligent, analytics-driven EV strategy to achieve long-term transportation electrification success.