Solar Forecast Based Optimization of Distributed Energy Resources in the LA Basin and UC San Diego Microgrid
Solar forecast based optimization of distributed renewable energy resources
Projects Updates/The Results
The utility customers who use solar forecasting and smart EV charging could achieve a 67% reduction in energy costs over the year, reducing monthly peak demand by 63%. This study reveals that using aggregated vehicle load large enough to absorb the solar output on the studied circuit is years in the future. The studied circuit showed that connected PV output created an energy valley of 64.5 MWh. Using a typical commuter PEV requiring 7 kWh means that roughly 9,200 vehicles must be connected during the solar output period to create an adequately sized energy sink to absorb the full amount of this oversupply. The executive order B-48-18 will improve the perspectives for EV charging and grid net load balancing in California. But at 929,000 commercial buildings in California, Oregon, and Washington, even 250,000 chargers will fall short of the amounts required in this example.
This project aimed to integrate high-accuracy solar forecasting to optimize the operation of distributed energy resources, and utilize the value of solar forecasting in utility grid operations to improve grid reliability, reduce ratepayer costs and increase safety. The objectives were to apply forecasts to inform control and scheduling decisions for distributed energy resources with emphasis on energy storage and electric vehicle charging control at warehouse photovoltaic clusters in the LA-Orange-Riverside-San Bernardino-San Diego Counties as well as the UCSD microgrid.
The project showed that utility customers who use solar forecasting and smart electric vehicle charging could achieve a 67 percent reduction in energy costs over the year. Monthly peak demand was reduced by 63 percent on average. This tool contributes to a better utilization of existing generation resources and transmission and distribution (T&D) assets, unbundling of EV driver behavior or economical preferences, and lower consumer cost per kWh. The energy cost reduction is estimated at $6.8 million/year per 100 MW of DERs.
The tool and strategies developed in the project have the potential of boosting the economic activities associated with the optimized use of distributed solar energy resources and the reduction of grid net load variability. The economic benefits are the improvements in system operation efficiencies, and the creation of skilled people and local jobs that contribute to the advancement toward a green economy.
Optimal scheduling in comparison with conventional for one year of operation of a fleet of 49 electric vehicles in SCE territory results to a decrease of 65% in peak power demand, 13% in ratepayer costs and 63% in total customer costs, and lead to 100% PV self-consumption.
Environmental & Public Health
Optimized use of distributed solar energy technologies will lead to reduced water consumption and greenhouse gas (GHG) emissions in the energy generation sector. Furthermore, adoption of electric vehicles (EV) as alternative to fixed storage devices will contribute to reduced materials wastes and air pollutant overall. The GHG and NOx Reductions are estimated at 52,194 and 3.1 MT/year per 100 MW of DERs, respectively.
The project integrates high-accuracy solar forecasts to distributed energy resources (DERs) and provide the grid operators and balancing authorities the information needed to optimize operations leading to a more responsive and reliable operation of the grid. This integrating tool contributes to a peak load reduction of about 37MW per 100 MW of DERs.