Energy Reports (Nov 2021)
Simulation analysis of distributed micro-energy clusters participating in voltage regulation and peak regulation
Abstract
The influence of distributing micro-energy access on power grid voltage and peak is analyzed. For the over-voltage and under-voltage problems caused by the distributed micro-power access distribution network, which proposes a reactive control algorithm based on fuzzy logic. In this algorithm, the fuzzy logic control algorithm is used to control the reactive power,which is based on the sensitivity matrix. For the peak shaving problem caused by distributed power access to the distribution network, a strategy of storing photovoltaic power generation energy in an air source heat pump is proposed. By setting air source heat pumps with different parameters, a multi-objective scheduling model of control strategy for photovoltaic power generation energy consumption and the air source heat pump are proposed. And the improved non-dominated sorting genetic algorithm NSGA-II (Non-dominated Sorting Genetic Algorithms) is used to optimize the model. Through the introduction of fuzzy logic control to the research on the node voltage, the no-voltage control and the change of the node voltage of the introduction of fuzzy logic control are analyzed. The voltage fluctuation range of the introduction of fuzzy control is between 0.9–1.05, which is 0.1v less than the no-voltage control. The introduction of fuzzy logic control can solve the problem of voltage over-limit. In the process of peak shaving simulation analysis, using the improved algorithm NSGA-II, through the joint operation of wind power, photovoltaic power generation, air source heat pump and so on. The output power of the net load is 500 MW lower than the output power of the load, which is realized through the coordinated operation of various energy sources. The net load output power is relatively stable. From the analysis of the simulation results, the proposed algorithm can solve the voltage and peak problems, which caused by the participation of distributed resources in the micro-energy grid. And it realizes the balance of local energy production and energy load.
