Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach

Abstract

Establishing accurate electrical load prediction is vital for pricing and power system management. However, the unpredictable behavior of private and industrial users results in uncertainty in these power systems. Furthermore, the utilization of renewable energy sources, which are often variable in their production rates, also increases the complexity making predictions even more difficult. In this paper an interval type-2 intuitionist fuzzy logic system whose parameters are trained in a hybrid fashion using gravitational search algorithms with the ridge least square algorithm is presented for short-term prediction of electrical loading. Simulation results are provided to compare the performance of the proposed approach with that of state-of-the-art electrical load prediction algorithms for Poland, and five regions of Australia. The simulation results demonstrate the superior performance of the proposed approach over seven different current state-of-the-art prediction algorithms in the literature, namely: SVR, ANN, ELM, EEMD-ELM-GOA, EEMD-ELM-DA, EEMD-ELM-PSO and EEMD-ELM-GWO.

Energy Management Scheduling for Microgrids in the Virtual Power Plant System Using Artificial Neural Networks

“…The MG could manage, aggregate, and deploy DGs, for the most part when a grid is disconnected. Alternative aggregator choice dependent on smart grid upgrades is the concept of a virtual power plant (VPP) [9][10][11].…”

“…In this regard, scheduling problems need a smart controller for the VPP system using optimization algorithms. Thus, several optimization algorithms have been established by researchers recently, such as the genetic algorithm [7], gravitational search algorithm [9][10][11], butterfly algorithm [12], herd-related optimization approaches [13], whale optimization algorithm [14], cat swarm optimization [15], practical swarm optimization (PSO) [16], etc. The energy management duties are to ensure security; use a mixture of energy, generation, transmission, and distribution resources; and minimize losses and increase profit [17][18][19][20][21].…”