Multi-dimensional signaling method for population-based metaheuristics: Solving the large-scale scheduling problem in smart grids

Abstract

The dawn of smart grid is posing new challenges to grid operation. The introduction of Distributed Energy Resources (DER) requires tough planning and advanced tools to efficiently manage the system at reasonable costs. Virtual Power Players (VPP) are used as means of aggregating generation and demand, which enable smaller producers using different generation technologies to be more competitive. This paper discusses the problem of the centralized Energy Resource Management (ERM), including several types of resources, such as Demand Response (DR), Electric Vehicles (EV) and Energy Storage Systems (ESS) from the VPP's perspective to maximize profits. The complete formulation of this problem, which includes the network constraints, is represented with a complex large-scale mixed integer nonlinear problem. This paper focuses on deterministic and metaheuristics methods and proposes a new multi-dimensional signaling approach for population-based random search techniques. The new approach is tested with two networks with high penetration of DERs. The results show outstanding performance with the proposed multi-dimensional signaling and confirm that standard metaheuristics are prone to fail in solving these kind of problems.

Enhanced Multi-Objective Energy Optimization by a Signaling Method

“…In addition, constraints violations were easily avoided with signaling when compared with the standard approaches counterpart, which presented a high number of infeasibilities in both scenarios. This enable to conclude that, the use signaling leverages the better performance of the addressed methods in the ERM as it was demonstrated previously in single-objective problem [23]. In this case, the metaheuristic that featured better results was W-PSO, however, the execution time was higher, when compared with the NSGA-II and MOPSO, mainly in single-core.…”

“…In [23], a multi-dimensional signaling method is presented to improve metaheuristics performance to solve the energy scheduling problem. The method relies on a scheme to exchange signals between the metaheuristic core process, i.e., movement and evaluation stage.…”

“…The constraints for high-voltage (HV)/medium-voltage (MV) power transformers limits considering the power flow direction from HV to MV are taken into account, where the maximum amount of apparent power supplied from the upstream network cannot be higher than a predefined limit. This limit can correspond in reality to the capacity of the substation [23]. In the present ERM model the upstream network supply corresponds to the power bought from the external suppliers.…”

“…The algorithm stops after the defined number of iterations is reached. This setup is widely used in other multi-objective metaheuristic-based algorithms [20,23,36,37].…”

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

“…In our opinion, this is a potential indicator that energy resource management-related research is getting more mature in the last years and ready for publication in journal. Energy resource management has been considered by some researchers as one of the most complicated optimization problems in power systems due to its combinatorial nature, nonlinearities, and large number of energy resources which leads to high dimensionality and highly constrained problems [23,[41][42][43]. Adequate optimization frameworks are a key part of the new paradigm brought by the smart grid operation.…”