Joint Planning of Distributed Generations and Energy Storage in Active Distribution Networks: A Bi-Level Programming Approach

TL;DR

This paper presents a bi-level programming model for joint planning of distributed generations and energy storage in active distribution networks, aiming to optimize placement, capacity, and operation to enhance system performance.

Contribution

It introduces a novel bi-level programming approach combined with an improved binary particle swarm optimization algorithm for joint planning in active distribution networks.

Findings

Reduces planning deviation due to DG output uncertainties

Improves voltage profile in distribution systems

Enhances operational economy

Abstract

In order to improve the penetration of renewable energy resources for distribution networks, a joint planning model of distributed generations (DGs) and energy storage is proposed for an active distribution network by using a bi-level programming approach in this paper. In this model, the upper-level aims to seek the optimal location and capacity of DGs and energy storage, while the lower-level optimizes the operation of energy storage devices. To solve this model, an improved binary particle swarm optimization (IBPSO) algorithm based on chaos optimization is developed, and the optimal joint planning is achieved through alternating iterations between the two levels. The simulation results on the PG & E 69-bus distribution system demonstrate that the presented approach manages to reduce the planning deviation caused by the uncertainties of DG outputs and remarkably improve the voltage profile and operational economy of distribution systems.