Assessing the potential of merchant energy storage to maximize social welfare of renewable-based distribution networks considering risk analysis

• Published in: Electric power systems research Vol. 188; p. 106522
• Main Authors: Abdolahi, Arya, Salehi, Javad, Gazijahani, Farhad Samadi, Safari, Amin
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2020; Elsevier Science Ltd
• Subjects: Alternative energy; Congestion; Congestion management; Constraints; Electric industries; Electricity distribution; Energy storage; Reconfiguration; Renewable energy; Renewable resources; Risk analysis; Studies; Uncertainty; Congestion management; Renewable energy; Risk analysis; Energy storage
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2020.106522

•An energy arbitrage strategy is proposed to alleviate the congestion of distribution systems.•The problem is formulated to maximize the social welfare pf whole system.•The stochastic programming is developed to cope with the uncertainty.•A risk measure is utilized to hedge the system against the risk of exposure to the uncertainty. Nowadays, a progressive increase in the penetration of dispersal renewable energies in electricity markets has imposed many serious challenges such as congestion of lines, customer dissatisfaction, and disassembly of nodal prices. To counter these problems, this article examines merchant cryogenic energy storage (CES) along with renewable resources to relieve the congestion of distribution systems considering distribution locational marginal pricing (DLMP). Moreover, a novel reconfiguration mechanism has been incorporated into the model to increase the performance of CES in smoothing DLMP. The proposed problem is formulated to alleviate the possible congestion aimed at maximizing the social welfare of the system while meeting the environmental constraints. To deal with uncertainty subject to renewable generation, and efficient risk-constrained stochastic programming is extended employing the conditional value-at-risk index to create a meaningful trade-off between the expected profit and the risk of exposure to the uncertainty. In the end, the simulation was demonstrated on the IEEE 33-bus and 118-bus distribution systems to prove the efficacy of the proposed method. The results evidenced that the proposed approach not only alleviates the congestion of network but also can smooth the LMPs at different locations.