Coordinated control scheme for provision of frequency regulation service by virtual power plants

This paper proposes a coordinated control strategy for a Virtual Power Plant (VPP) contribution to load frequency control. The considered VPP comprises distributed Battery Energy Storage Systems (BESSs) and Heat Pump Water Heaters (HPWHs). The frequency regulation signal is distributed between thermal generator and the VPP based on distribution coefficients which are calculated through conducting a multi-objective optimization problem. The optimization framework incorporates the dynamic regulation performance as well as the total regulation cost. A fuzzy strategy is adopted to obtain the final solution according to user-defined conditions. The regulation signal of VPP is dispatched based on the speed and the available power capacity of VPP components. The performance of the proposed coordination scheme is compared to the scheme without coordination and that with no involvement of VPP in frequency regulation. The regulation performance is also evaluated for varying time delays expected in the communication channels. An approach based on brain emotional learning is developed to coordinate the VPP and conventional generation unit to avoid large frequency deviations caused by the communication delays. Case studies are conducted on a multi-area power system in MATLAB/Simulink environment, and the results are verified by the OPAL-RT real-time simulator.

Automated summary

This paper proposes a coordinated control strategy for load frequency control in a Virtual Power Plant (VPP). The strategy considers distributed Battery Energy Storage Systems (BESSs) and Heat Pump Water Heaters (HPWHs) as part of the VPP. The optimization framework takes into account dynamic regulation performance and total regulation cost, and a fuzzy strategy is used to determine the final solution. The regulation signal of the VPP is dispatched based on the speed and available power capacity of its components.