Interconnected Operation and Economic Feasibility-Based Sustainable Planning of Virtual Power Plant in Multi-Area Context

Highlights: What are the main findings? The performance of the proposed system was determined for a multi-area-based VPP (MAREAVPP). The proposed MAREAVPP analysis was performed at multi-time intervals based on optimal scheduling. The proposed framework was then optimized, and the results were verified with an advanced MGO technique. What is the implication of the main finding? A series of flexible resources were combined to increase the system’s dependency by leveraging the potential of community-based energy systems. The collective profit of the MAREAVPP was also improved by employing dynamic multiple scheduling strategies. A virtual power plant (VPP) is a potential alternative that aggregates the distributed energy resources (DERs) and addresses the prosumer’s power availability, quality, and reliability requirements. This paper reports the optimized scheduling of an interconnected VPP in a multi-area framework established through a tie-line connection comprising multiple renewable resources. The scheduling was initially performed on a day ahead (hourly basis) interval, followed by an hour ahead interval (intra-hour and real time), i.e., a 15 min and 5 min time interval for the developed VPP in a multi-area context. The target objective functions for the selected problem were two-fold, i.e., net profit and emission, for which maximization was performed for the former and reduction for the later, respectively. Since renewables are involved in the energy mix and the developed problem was complex in nature, the proposed multi-area-based VPP was tested with an advanced nature-inspired metaheuristic technique. Moreover, the proposed formulation was extended to a multi-objective context, and multiple scheduling strategies were performed to reduce the generated emissions and capitalize on the cumulative profit associated with the system by improving the profit margin simultaneously. Furthermore, a comprehensive numeric evaluation was performed with different optimization intervals, which revealed the rapid convergence in minimal computational time to reach the desired solution.