Abstract
This paper addresses the allocation of Energy Storage Systems (ESSs) in power grids by finding the optimal number of ESSs and their locations and sizes with the goal of improving reliability in contingency states. We propose a contingency-sensitivity-based heuristic to decide the optimal number of ESSs and the most effective locations for ESSs support, while circumventing the combinatorial nature of the siting problem. A contingency sensitivity index (CSI) is proposed which represents the impacts of contingencies on the network buses. The CSI ranks the buses, such that those with higher impacts have the privilege for installing ESSs. For the ESSs being fixed, the sizing is formulated as a multi-period AC optimal power flow (OPF) problem and solved by Self-Organizing Hierarchical Particle Swarm Optimization with Time Varying Acceleration Coefficients (HPSO TVAC). The optimal ESSs sizes are selected by minimizing a total cost, which includes investment cost of storage devices, bus voltage deviation cost and average network losses cost. Uncertainties of the renewable generation are accounted by considering different realizations of the generation profiles, then, ESSs sizes are selected by taking the worst case approach. The proposed methodology has been demonstrated on the modified IEEE 30-bus system and Tunisian Grid. The obtained results show the effectiveness of the proposed methodology and the related reliability merits.
Highlights
The penetration of renewable energy sources (RES) is rapidly increasing in recent years to achieve a sustainable power system
Energy storage systems play a key role to improve the reliability of power system in contingency states
Statistical information on potential contingency locations seems to be decisive for the optimal siting of energy storage systems (ESSs), to increase the probability of supporting the power grid against faults
Summary
The penetration of renewable energy sources (RES) is rapidly increasing in recent years to achieve a sustainable power system. The performance is in terms of ESS support in contingency states and reliability improvement (voltage deviation, frequency control) thanks to the proposed siting approach that prefers the vulnerable locations for ESS support and in terms of computation time, thanks to the proposed heuristic that reduces the complexity of the ESS allocation problem. The objective of the proposed methodology is to find a cost-effective ESS allocation strategy, to improve stability and reliability of the power grid and to minimize network losses and voltage deviation, while reducing the computational burden. The proposed methodology deals with many optimization issues relevant to the addressed problem, the integration is optimized in terms of investment and operation cost, the effects of integration are minimized such as the network losses and bus voltage deviation. PROBLEM FORMULATION This section describes the power grid model with equations and constraints characterizing the system, distributed generators and ESS units
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