Abstract
With the large-scale integration of renewable energy such as wind power and PV, it is necessary to maintain the voltage stability of power systems while increasing the use of intermittent renewable energy sources. The rapid development of energy storage technologies permits the deployment of energy storage systems (ESS) for voltage regulation support. This paper develops an ESS optimization method to estimate the optimal capacity and locations of distributed ESS supporting the voltage regulation of a distribution network. The electrical elements of the network integrated with PV and ESS are first modelled to simulate the voltage profile of the network. Then an improved multi-objective particle swarm optimization (PSO) algorithm is employed to minimise a weighted sum of the overall nodal voltage deviation from the nominal level across the network and across the time horizon and the energy capacity of ESS reflecting the associated investment. The improved PSO algorithm adaptively adjusts the inertia weight associated with each particle based on its distance from the best known particle of the population and introduces the cross-mutation operation for a small distance to avoid falling into local optimal solutions. Then the dynamic dense distance arrangement is taken to update the non-inferior solution set and indicate potential global optimal solutions so as to keep the scale and uniformity of the optimal Pareto solution set. To mitigate the impact of decision makers’ preference, the information entropy based technique for order of preference by similarity to ideal solution is used to select the optimal combination of the ESS access scheme and capacity from the Pareto solution set. The proposed ESS optimization method is tested based on the IEEE 24-bus system with additional imports from high-voltage power supply. The voltage profile of the network simulated without the ESS or with the random or optimized ESS placement is compared to illustrate the effectiveness of the optimized ESS in performing voltage regulation under normal operation and supporting emergency power supply during high-voltage transmission failures.
Highlights
Due to the continuous consumption of fossil fuels and the resulting aggravation of environmental pollution, the utilization of renewable energy sources (RES) has developed rapidly in recent years
This paper has proposed an improved multi-objective particle swarm optimization (PSO) based method to estimate the best combination of sizes and locations of distributed energy storage systems (ESS) that effectively support the voltage regulation of a distribution network with PV access
The improved multiobjective PSO algorithm produces an optimal Pareto solution set by minimising a weighted sum of the overall deviation between the voltage profile of the network and the nominal level across the time horizon and the energy capacity of ESS reflecting their investment
Summary
Due to the continuous consumption of fossil fuels and the resulting aggravation of environmental pollution, the utilization of renewable energy sources (RES) has developed rapidly in recent years. To alleviate the voltage limit violation caused by the increased use of RES, many literatures regulate the node voltage from the perspective of conventional generator outputs and reactive power compensation devices but rarely consider the optimization of ESS locations and sizes for voltage regulation. This paper is structured as follows: describes the Modeling of Distribution Network Integrated With ESS and PV; establishes a multi-objective Optimization Model of ESS Capacity and Locations for Voltage Regulation; develops an Improved Multi-Objective Particle Swarm Optimization Algorithm for the ESS access scheme optimization based on the TOPSIS; Case Study implements simulation experiments based on the IEEE 24-bus system to validate the performance of the optimized ESS in the voltage regulation and emergency power supply; and presents Conclusion and Recommendations for Future Work. The effective control of charging and discharging of the ESS placed at more suitable access points can better reduce the node power fluctuation and improve the voltage stability of the network
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