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Aiming at the deficiencies and shortcomings of traditional reactive power compensation devices in controlling and improving voltage quality, a bilevel programming model for the coordinated optimal allocation of active and reactive power capacity of photovoltaic power generation systems, wind-driven generators, shunt capacitors and static var compensators is established based on chance-constrained programming. In the optimization model, the randomness and intermittence of the output power of the distributed generation and the reactive power regulation ability of the distributed generation are considered. The correlation of illumination, wind speed and load fluctuation is considered and affected by seasonal variation. Latin hypercube sampling method is used to deal with the correlation of random variables. Monte Carlo probabilistic power flow method is used to calculate the power flow of distribution network with intermittent distributed generation systems. The location and capacity of active and reactive power sources in outer programming are optimized by adaptive artificial fish swarm algorithm, and the allocation scheme of active and reactive power sources determined by outer programming is optimized by inner adaptive artificial fish swarm algorithm. The two-layer nested adaptive artificial fish swarm algorithm is used to solve the optimal allocation problem constructed in this paper, and the optimal allocation scheme of active and reactive power supply capacity is determined. Taking IEEE33 distribution system as an example, the feasibility and applicability of the proposed model and algorithm are verified.

Collaborative Management of Multi-Type Energy for Optimal Control of Voltage and Loss of Distribution Systems with DGs and SVCs