Optimal Allocation of Renewable Sources and Energy Storage Systems in Partitioned Power Networks to Create Supply-Sufficient Areas


Oskouei M. Z. , Mohammadi-Ivatloo B., ERDİNÇ O. , Erdinc F. G.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, vol.12, no.2, pp.999-1008, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 12 Issue: 2
  • Publication Date: 2021
  • Doi Number: 10.1109/tste.2020.3029104
  • Title of Journal : IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
  • Page Numbers: pp.999-1008

Abstract

Given the increasing complexity and scale of power networks, the probability of system collapse has dramatically increased during natural disasters and malicious cyber attacks. The results of recent studies indicate the state-of-the-art solution to overcome these challenges is to partition existing power networks into several interconnected areas. To address this open problem, this paper presents a unified decision-making structure that consists of network partitioning and optimal operational planning issues. Unlike conventional partitioning mechanisms that overlook the physical characteristics of power grids, the proposed structure attempts to decompose the integrated power network into the optimal number of robust partitions by using the electrical modularity and electrical coupling strength (ECS) indicators. The partitioning mechanism is accomplished in line with an optimization problem to construct supply-sufficient partitions with the aim of increasing hosting capacity of renewable generation in partitioned areas and decreasing the exchanged power between available partitions. To this end, an operational planning problem is performed to determine the optimal allocation of wind farms (WFs), photovoltaic (PV) parks, and energy storage systems (ESSs) in each created partition. The proposed structure ensures the uniform distribution of renewable generation in the partitioned power networks. The presented partitioning and planning problem is applied to the IEEE 30-bus test system, and it is solved using GAMS software. The advantage of the proposed structure is demonstrated using a set of case studies. To assure precise performance assessment, optimization outputs are further analyzed by DIgSILENT PowerFactory for detailed monitoring of the effectiveness of the proposed structure under normal and emergency conditions.