Optimal Distribution Voltage Control and Coordination With Distributed Generation

TLDR

Distributed generation from renewable sources has grown to mitigate climate change and fossil fuel depletion, but its variable output near customers can cause voltage fluctuations in distribution networks. This study proposes an optimal voltage control strategy that coordinates multiple distributed devices—load‑ratio transformers, SVRs, shunt capacitors, shunt reactors, and static VAR compensators—to maintain voltage stability. The authors model SVRs as tap‑changing units controlled centrally, assume a widespread communication network, employ a genetic algorithm to optimize device settings, and validate the approach through simulations on a PV‑laden distribution network.

Abstract

In recent years, distributed generation, as clean natural energy generation and cogeneration system of high thermal efficiency, has increased due to the problems of global warming and exhaustion of fossil fuels. Many of the distributed generations are set up in the vicinity of the customer, with the advantage that this decreases transmission losses. However, output power generated from natural energy, such as wind power, photovoltaics, etc., which is distributed generation, is influenced by meteorological conditions. Therefore, when the distributed generation increases by conventional control techniques, it is expected that the voltage change of each node becomes a problem. Proposed in this paper is the optimal control of distribution voltage with coordination of distributed installations, such as the load ratio control transformer, step voltage regulator (SVR), shunt capacitor, shunt reactor, and static var compensator. In this research, SVR is assumed to be a model with tap changing where the signal is received from a central control unit. Moreover, the communication infrastructure in the supply of a distribution system is assumed to be widespread. The genetic algorithm is used to determine the operation of this control. In order to confirm the validity of the proposed method, simulations are carried out for a distribution network model with distributed generation (photovoltaic generation).