Multi-Objective Voltage and Reactive Power
Coordinated Control Strategy for Distribution
Networks Utilizing Gaining-Sharing Knowledge
Based Algorithm
Jinjin Ding
State Grid Anhui Electric Power
Research Institute
State Grid Anhui Electric Power Co.
Ltd.
Hefei, China
djinjin123@126.com
Xunting Wang
State Grid Anhui Electric Power
Research Institute
State Grid Anhui Electric Power Co.
Ltd.
Hefei, China
wangxt1994@163.com
Bin Xu
State Grid Anhui Electric Power
Research Institute
State Grid Anhui Electric Power Co.
Ltd.
Hefei, China
xubin1980@sina.com
Mingxing Zhu
Power Quality Engineer Researcher Center,
Ministry of Education
Anhui University
Hefei, China
xysah@163.com
Wei Liu
School of Electrical Engineering
and Automation
Anhui University
Hefei, China
williamliu19980525@outlook.com
Abstract—
Existing heuristic optimization algorithms are prone
to obtain a set of non-dominated solutions overconcentrated within
an intermediate area in the objective space. It results in a poor
diversity performance of the Pareto front when handling the
problem on multi-objective voltage and reactive power
coordinated control (MOVRPOC). For mitigating the
aforementioned disadvantages, a newly developed heuristic
algorithm, gaining-sharing knowledge based algorithm (GSK), is
implemented to handle the problem of MOVRPOC. Then, the
minimum system losses, the minimum average voltage deviation
and the minimum curtailment rate are treated as optimization
objectives, and then the revised IEEE 33-bus distribution system
is utilized as the benchmark networks. Grey wolf optimization
(GWO) and equilibrium optimizer (EO) are taken as a comparison
to validate the improvement on diversity of GSK. The results
reveal that GSK is capable to obtain more diverse non-dominated
solutions to MOVRPOC for distributed networks, which can be
better applied to the practical scenarios on MOVRPOC
distribution networks.
Keywords— Multi-objective voltage and reactive power
coordinated control (MOVRPOC); distribution networks; distributed
photovoltaics (PVs); gaining-sharing knowledge based algorithm
(GSK)
I.
I
NTRODUCTION
In order to achieve the proposal called “carbon peak, carbon
neutrality”, it is an important measure to prompt distributed
photovoltaics to access into the distribution power system. It
will contribute greatly to develop a novel power system in
which renewable energy is the major component, and to realize
the ‘dual carbon’ goal and rural revitalization strategy.
However, a large number of distributed PVs connected to the
distribution network result in active power flow fluctuations
and then cause a series of power quality problems such as more
power losses, overvoltage at terminal buses, power reversion to
the power grid, and three-phase unbalance [1]-[4]. As a result,
these power quality problems affect the secure, stable and
economic operation of the distribution system. Therefore,
MOVRPOC with distributed PVs is an urgent concern for the
distribution network.
Under the condition of distributed PVs access to the
distribution network, it is generally necessary to formulate the
MOVRPOC plan by integrating multiple optimization
objectives like the minimum system loss, the minimum average
voltage deviation and the minimum curtailment rate.
Unfortunately, trade-offs among various optimization
objectives cause the optimal results of the MOVRPOC model
not unique, which also increases the difficulty and complexity
This work is supported by State Grid Anhui Electric Power Research
Institute. Grant Number: 5400-202255279A-2-0-XG. (Corresponding
author: Wei Liu).
