Optimal Distribution Voltage Control and Coordination With Distributed Generation

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).Index Terms-Centralized control, coordinated control, distribution system, genetic algorithm (GA), voltage/reactive power control.

Evaluation of Voltage Control Approaches for Future Smart Distribution Networks

“…This procedure is applied in both the get cuckoo function and empty nest function. It can be represented by (8).…”

“…In [8], the genetic algorithm (GA) was applied to control the tap position of on-load tap changer (OLTC) transformers and static var compensator to minimize the network losses and voltage deviation. In [9], an evolutionary particle swarm optimization-based algorithm is used to manage reactive power from distributed generations (DGs), active power and reactive power from micro-grids, and the OLTC tap positions to minimize network losses and microgeneration shedding.…”

Comparative study of reactive power control methods for photovoltaic inverters in low‐voltage grids

“…The solution to the mentioned problem can be obtained by using several non-linear optimisation techniques including those described in Section 1 [24][25][26][27][28][29]. However, in this paper, the Nelder-Mead non-linear minimisation method is employed due to its easy application [37].…”

“…For example, in [21][22][23], the local data is sent to all the PV units with the aim of equalising the reactive power injection. In addition, non-linear control techniques have been used to optimise the operation of these systems, such as fuzzy logic in [24], neural network in [25], swarm optimisation in [26], and genetic and evolutionary algorithms in [27][28][29]. Control algorithms with better performance are expected using these techniques as discussed in [29].…”

A Study on the Voltage Stabilization Method of Distribution System Using Battery Energy Storage System and Step Voltage Regulator

“…In order to maintain customer voltage within allowable limit, tap operation of SVR installed in primary feeder is usually carried out according to the pre-designed setting value of delay time ranging from 30 to 150 sec. Existing papers regarding SVR operation are only dealt with optimal voltage regulation methods in distribution systems with PV system by SVR to deliver reasonable voltage to as many customers as possible [1][2][3][4][5]. However, there are not considered that power quality problems such as under voltage and over voltage could be occurred during the delay time of SVR.…”