Strong DSM programs are rooted in knowing your customer. While legacy programs were dependent on polls or active customer input to inform design, the power of analytics now gives utilities the ability to understand specific appliance usage frictionlessly and at an unprecedented scale. Now, rather than designing programs based on 1% of customer inputs, utilities can confidently design by accounting for a majority of their customer base.
Bidgely Co-founder and CTO, Vivek Garud, explains how in this 1-minute video.
Balancing energy demand and supply will be a lot more weather-dependent going forward as we shift from reliance on traditional coal and gas plants to a greener portfolio with solar and wind.
At the same time, energy demand is also becoming more variable with electrification, especially due to EVs.
With demand more volatile and supply more weather dependent, the grid-balance equation completely changes, requiring much more data and automation to manage.
In this 1-minute video, Bidgely Co-Founder and CEO Abhay Gupta shares how energy analytics can help solve this equation.
Behavioral demand response lives in the space between a critical peak event and cost intensive response measures like direct load control or a rebate- or incentive-based strategy.
While direct load control is the classic example of demand response, it's not practical at scale. For example installing a load control device on every residential AC unit in the United States. Utilities need another, more affordable, agile and scalable tool in their tool belt: behavioral demand response.
In this 2-minute video, Bidgely's Hannah Courtney explains how behavioral demand response, through personalized nudges based on a household's unique energy habits, can educate and empower customers to shift their usage outside of peak windows each time they receive a peak event notification.
Through the science of energy disaggregation, smart meter data can be analyzed to derive specific appliance-level usage patterns. This patented technology is especially helpful when it comes to EV detection, enabling electric companies to identify, inform, influence and engage EV customers. Check out the 1-minute video!
Iterative program design is hinged upon real time feedback. Utilities can no longer afford to lose valuable time waiting for program performance as measured by traditional, lengthy measurement and verification (M&V) cycles. However, using AI, utilities now have visibility into the health of key metrics, offering the opportunity to pivot, or further optimize, programs.
Bidgely’s Chief Revenue Officer, Gautam Aggarwal, shares more in this 1-minute video.
Utilities have known for a long time that DERs are coming, but it certainly feels like they're coming faster than ever.
Customer-owned DERs are going to solidify the link between grid and customer, making it even more important that utilities understand their customers and how DERs can impact grid performance locally.
In this ungated 1-minute video, Bidgely Head of Innovation Maria Kretzing explains how DERs can play a tremendous role in reliability and resiliency and why utilities should be very excited to take advantage of this opportunity.
In this 2-minute video, Bidgely's Pauline Marcou explains how personalization can help utilities maximize the impact of both opt-in and opt-out Time-of-Use (TOU) rates.
Both options can be very successful. The key to both, though, is to provide customers with energy insights and help them transition to the new type of rate.
In an opt-in model, for example, customers need a little nudge. They need to understand the key benefits of that rate and why they should switch. These advantages need to be laid out in very clear, relevant and personalized messaging.
When you look at an opt-out model, on the other hand, providing customers with insights and energy intelligence reduces the chance that they opt-out of the rate. It is very important to help them understand how their usage is impacting their energy costs on the new rate, as well as how adjusting their usage of specific appliances could cost them less.
Energy intelligence and appliance level insights help maximize customer participation in TOU rates, whether the program is opt-in or opt-out.
Generative AI-based GPT is opening up a future in which utility customers can interact with data in very natural ways. For example, if a customer asks "Why did my energy bill go up?" GPT can interact with the data on the back end and reply with the reason for the increase. Alternatively, an operations manager could ask "Who are the people who have solar and EV in my territory?" GPT's creativity could unlock so many different use cases in the utility industry.
Hear more in this brief interview with Bidgely Chief of Staff and Innovation Advisor Shriram Ramanathan.
The presence of new distributed energy resources like solar, batteries and electric vehicles has the same impact on DSM programs as they have on grid planning. The focus of DSM programs used to be primarily energy efficiency, with an average energy saving goal of 2%. However now, as consumers install solar on their roof and become producers of their own energy, energy savings may no longer be a motivating factor. The DSM paradigm will shift from reducing consumption to flexible demand and influencing when consumers use energy.
Bidgely’s CEO, Abhay Gupta, shares more in this 1-minute video.
In order to achieve decarbonization and align clean generation with demand requirements, every customer requires unique and hyper-personalized interactions with their energy provider.
In this video, VP Strategy and Growth, Jeff Wahl, explains how to integrate customers in utility decarbonization efforts. Check out the 2-min video.
