A comprehensive metric study of distributed PV consumption capacity considering multiple uncertainties

Abstract

With the transformation of the energy structure, distributed photovoltaic (PV) power generation has become increasingly important. However, due to uncertain factors such as weather, equipment, and load demand, the consumption problem is prominent, which restricts the healthy development of the system. It is important to accurately measure the absorptive capacity of distributed PVs, but there are many shortcomings in existing research methods. This paper proposes a comprehensive measurement method to solve this problem and thus conducts a comprehensive metric study of the distributed PV Consumption Capacity considering multiple uncertainties. Based on the output uncertainty and load uncertainty of the distributed PV power generation, a mathematical model of the distributed PV power generation uncertainty is constructed. Based on the distributed PV operation data under various uncertain factors, considering the PV capacity and active power loss connected to the distribution network as objective functions, and setting constraints such as power balance, node voltage, line power flow, and distributed PV output, a comprehensive measurement model of the distributed PV absorption capacity is constructed. A local chaotic search is introduced to improve the firefly algorithm, and the improved firefly algorithm is used to solve the comprehensive measurement model and output the comprehensive measurement results of the absorption capacity. The experimental results show that this method can effectively evaluate the absorptive capacity. In a typical IEEE 32 - node distribution network, the network loss is 30 kW when PV access reaches 534 kW. This method is better than other methods in terms of maximum absorptive capacity, annual PV absorption, and annual network loss, and provides a scientific basis for the planning, operation, and management of distributed PV systems.