TY - EJOU
AU - Lee, Yeonwoo
TI - Energy Management System with Power Offering Strategy for a Microgrid Integrated VPP
T2 - Computers, Materials \& Continua
PY - 2023
VL - 75
IS - 1
SN - 1546-2226
AB - In the context of both the Virtual Power Plant (VPP) and microgrid (MG), the Energy Management System (EMS) is a key decision-maker for integrating Distributed renewable Energy Resources (DERs) efficiently. The EMS is regarded as a strong enabler of providing the optimized scheduling control in operation and management of usage of disperse DERs and Renewable Energy reSources (RES) such as a small-size wind-turbine (WT) and photovoltaic (PV) energies. The main objective to be pursued by the EMS is the minimization of the overall operating cost of the MG integrated VPP network. However, the minimization of the power peaks is a new objective and open issue to a well-functional EMS, along with the maximization of profit in the energy market. Thus, both objectives have to be taken into account at the same time. Thus, this paper proposes the EMS application incorporating power offering strategy applying a nature-inspired algorithm such as Particle Swarm Optimization (PSO) algorithm, in order to find the optimal solution of the objective function in the context of the overall operating cost, the coordination of DERs, and the energy losses in a MG integrated VPP network. For a fair DERs coordination with minimized power fluctuations in the power flow, the power offering strategies with an active power control and re-distribution are proposed. Simulation results show that the proposed MG integrated VPP model with PSO-based EMS employing Egalitarian reDistribution (ED) power offering strategy is most feasible option for the overall operating cost of VPP revenue. The total operating cost of the proposed EMS with ED strategy is 40.98$ compared to 432.8$ of MGs only without EMS. It is concluded that each MGs in the proposed VPP model intelligently participates in energy trading market compliant with the objective function, to minimize the overall cost and the power fluctuation.
KW - Artificial intelligence; energy management system; microgrid; nature-inspired algorithm; virtual power plant
DO - 10.32604/cmc.2023.031133