Abstract
Energy storage system (ESS) has been advocated as one of the key elements for the future energy system by the fast power regulation and energy transfer capabilities. In particular, for distribution networks with high penetration of renewables, ESS plays an important role in bridging the gap between the supply and demand, maximizing the benefits of renewables and providing various types of ancillary services to cope the intermittences and fluctuations, consequently improving the resilience, reliability and flexibility. To solve the voltage fluctuations caused by the high permeability of renewables in distribution networks, an optimal capacity allocation strategy of ESS is proposed in this paper. Taking the life cycle cost, arbitrage income and the benefit of reducing network losses into consideration, a bilevel optimization model of ESS capacity allocation is established, the coordination between active/reactive power of associate power conversion system is considered, and the large scale nonlinear programming problem is solved using genetic algorithm, simulated annealing and mixed integer second-order cone programming method. The feasibility and effectiveness of the proposed algorithm have been verified.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
To solve the voltage fluctuations in distribution networks (DNs) caused by the proliferation of PV, an interactive bilevel Energy storage system (ESS) planning strategy was proposed considering the factors of life cycle cost (LCC), the arbitrage income and the benefit of reducing line losses
The outer model was solved by genetic algorithm (GA) combined with simulated annealing (SA), and the inner optimization was solved by mixed integer second-order cone programming (MISOCP)
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. It is worth noting that the reactive power regulations play important roles in optimal operation strategy development considering the possible ancillary services in DNs, affecting the network configuration, operation and the life cycle cost (LCC), further studies are required to investigate the cooperation between the active and reactive power from the overall life time of the system. With active/reactive power support from the ESSs in four quadrants, the proposed ESS planning method can both reduce the LCC and increase arbitrage revenue while providing ancillary services of voltage support in DNs. The main contributions and salient features of this paper can be highlighted as:. (1) A bilevel ESS optimal capacity allocation model for DNs is proposed to suppress voltage fluctuations and line losses caused by photovoltaic (PV) integration, and to accommodate the increasing penetration level of renewables in the near future.
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