Next Wave of Energy Systems

Why is next wave research important for Smart Local Energy Systems?

We set out to provide policy evidence on how a “next wave” of Smart Local Energy Systems (SLES) would benefit the energy system. We started by classifying SLES nationally, by strengthening empirical evidence on geography, types, and local conditions of SLES projects. We have developed three models that, together, give us a comprehensive whole-system view of the opportunities and challenges that SLES can offer. Both the Energy HUB and Whole Electricity System Investment Model (WeSIM) detail technologies, infrastructures, and markets. The Bounded Rationality Agents Investments (BRAIN-Energy) is an agent-based model of electricity generation and investment.

How did EnergyREV explore these issues?

In the Energy HUB model we modeled local energy systems by mathematically describing energy flows within the local energy system and external energy networks. Combining different energy vectors and local energy storage provides an opportunity to meet local objectives such as site energy cost or carbon minimisation and simultaneously offer flexible services to the power grid. We used the Energy HUB to model the investments required by campus energy systems to achieve Net-zero commitments and to investigate the changes to the techno-economic-emissions behaviour of one site with new Net-zero compliant energy system configurations.

We have expanded the BRAIN-Energy model to represent the investment behaviours of national and local investors (e.g. limited foresight of future system status and diverse technology preferences). We used the new model to investigate the influences of local investor participation and policy instruments on the increase of SLES and long-term decarbonisation. We also explored how new business strategies from local investors could accelerate the transition. We conducted a scenario analysis with the BRAIN-Energy model to reveal the impacts of different system settings on the scale-up of SLES, taking into consideration the participation of local investors, carbon pricing and demand-side responses.

WeSIM quantitative modelling allowed us to differentiate between energy needs and flexibility characteristics for the three main SLES archetypes across different UK regions. We modelled all three archetypes within WeSIM and varied their cost to see when they become a net benefit for the system. Then we contrasted the outcomes for the different SLES archetypes and compared the benefits of SLES for a Net-zero system with those from a previous briefing paper, noting that we were now assuming a more realistic counterfactual case than before.

What did EnergyREV learn?

Local energy system (LES) projects are rooted in specific local contexts. Our analysis of the local conditions associated with LES projects in the UK historically points to several general approaches for national and local policymakers to support future LES projects. We identified the importance of locally available skills and knowledge resources, strategic direction, and living conditions. In the long run, LES projects could enable the levelling up of disadvantaged local areas. National policies targeting disadvantaged areas can support a more equitable distribution of LES projects by providing the appropriate financial and regulatory incentives to energy and technology businesses and enabling entrepreneurs.

Results from our models indicate a great value from low voltage connected flexibility sources such as electric vehicles heat pumps and other appliances where most SLES value appears to originate. The participation of local investors can considerably increase the share of renewable energy in the power system and scale-up of SLES. However, the market role of incumbents is still essential to ensure system stability.