Multistage Scheduling of VPP under Distributed Locational Marginal Prices and LCOE Evaluation

This article delves into the security-constrained scheduling of a Virtual Power Plant (VPP) through a two-stage methodology. In the proposed framework, a decentralized locational marginal pricing (DLMP) based primary pricing mechanism is applied to realize the pricing in first stage. An exclusive Mixed Integer Linear Programming (MILP) framework is crafted for the VPP's scheduling to enhance the utilization of Distributed Energy Resources (DERs) and controllable loads in both the Day Ahead Market (DAM) and Real-Time Market (RTM). The primary objective is maximizing joint profit for the VPP and the DERs, while the economic assessment hinges on Levelized Cost of Energy (LCOE) for financial evaluation of the proposed scheme. The model's practicality is verified using the GAMS environment, and its efficiency is gauged through LCOE benchmarking. Furthermore, this paper unveils a communication framework for the VPP, grounded in IEC 61850-8-2 protocol. This framework exemplifies the exchange of XMPP stanzas among distinct clients during the strategy's implementation.