Estimation of Locational Marginal Pricing Using Hybrid Optimization Algorithms

At present, the restructured electricity market has been a prominent research area and attracted attention. The motivation of restructuring in power system is to introduce competition at various levels generate correct economic signal reduce generation cost. As result, it required have an effective price scheme deliver useful information about power. pricing mechanism dependent on demand load level, generator bids, limits transmission network. To address congestion charges, Locational Marginal Pricing (LMP) utilized markets. improve efficiency, this paper, Hybrid Backtracking Search Optimization Algorithm with Grey Wolf (GWO-HBOA) proposed, based Security Constrained Economic Dispatch (SCED). objective proposed minimize fuel cost under loss lossless conditions, considering both normal conditions. BOA conducted first, Grasshopper (GOA) subsequently combined BOA, which results GWO-HBOA. predict for power, response estimated exactly. Moreover, LMP can be segregated service security respect entities. In way, overcharging underpayment issues solved constrained optimization. Furthermore, determine loss, DC optimal flow analyzed. GWO IEEE 30-bus test system. Compared existing techniques, algorithm achieves better performance, terms cost, voltage stability, deviations, real reactive loss.