Evaluating the impact of integrating cryogenic energy storage and electric vehicles on congestion management in reconfigurable distribution networks considering conditional value-at-risk index

Nowadays, a progressive increase in the penetration of dispersed renewable energies in electricity markets has imposed many serious challenges, such as congestion of lines, customer dissatisfaction, and disassembly of nodal prices. To address these challenges, this paper looks into commercial cryogenic energy storage (CES) and electric vehicles (EV) in conjunction with distributed generations with the aim of congestion management while taking distribution locational marginal pricing (DLMP) into account. Additionally, a unique reconfiguration strategy has been considered in the formulation to maximize the efficiency of the CES and EV integration in the DLMP smoothing and ultimately social welfare maximization. An effective extension of risk-constrained stochastic programming is used to deal with uncertainty related to renewable energy sources. A conditional value-at-risk metric is employed to establish a substantial balance between anticipated gains and the susceptibility to uncertainties, offering a valuable framework for decision-making. The effectiveness of the suggested strategy was ultimately proved by the simulation on the IEEE 33-bus distribution system. The advocated reconfiguration strategy incorporating CES and EV has resulted in a 37.5% reduction in distribution line congestion compared to the initial case.