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Ingegneria Sismica

Ingegneria Sismica

Particle swarm algorithm-based user regulation and station autonomy strategies in low-voltage distributed photovoltaic systems

Author(s): Guocheng Li1, Cong Wang1, Zeguang Lu1, Ze Zhang1, Xiaoran Li1, Xiaoqin Wang1
1State Grid Dezhou Power Supply Company, Dezhou, Shandong, 253000, China
Li, Guocheng. et al “Particle swarm algorithm-based user regulation and station autonomy strategies in low-voltage distributed photovoltaic systems.” Ingegneria Sismica Volume 43 Issue 2: 1-25, doi:10.65102/is2026595.

Abstract

In the face of the problems of voltage overstepping the limit and three-phase unbalance which are caused by large-scale access of distributed photovoltaic power into low-voltage distribution networks, this research, in a creative way, uses the chaotic particle swarm optimization algorithm. This present application seeks to achieve a result that brings benefits to both sides, hence guaranteeing both the safe and money-saving running of the electric network and the promotion of the benefits of users.On the electric grid part, there exists a coordinating arrangement of energy storage systems, static var generators (SVG), and flexible load resources. At the same time, on the side of users, a model which puts emphasis on economic optimization has been established.Furthermore, through the usage of the chaotic particle swarm optimization (CPSO) algorithm, chaotic sequences are brought into the iterative procedure for enhancing the whole optimization ability. Carry out the development of a cooperative control strategy for three-layer optical storage, that is, storage, reactive power, and active power. Take the intelligent convergence terminal as the central node, carry out real-time monitoring on the condition of the station. First, we ought to give the first place to the use of energy storage for providing fast voltage support. When the storage capacity is not enough, we ought to trigger the reactive power adjustment function that the PV inverter has. Only when the situation is absolutely necessary, we should consider carrying out the reduction of a part of the PV active power. Through this kind of doing, it can be achieved that the station area carries out the self-governance.Compared with the no-optimization state, the strategy in this paper reduces the voltage mean offset (SVA) from 6.36 × 10-3 to 2.66 × 10-3. Before we carry out optimization work, the passing percentage of node voltage inside the station region has been increased from 65.17% to the complete 100%. At the same time, the peak voltage has been lowered from 1.063 per-unit to 1.029 per-unit.

 

Keywords
low voltage distribution network; distributed photovoltaic; chaotic particle swarm algorithm; user regulation; station autonomy

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