As a small energy system, microgrid plays an important role in utilizing distributed energy
resources, improving traditional energy networks, and building intelligent integrated energy …

Mutation takes a vital part in assisting differential evolution (DE) to achieve satisfactory
performance. The most crucial factor for a good mutation scheme is to mutate individuals …

Demand response programs, energy storage systems, electric vehicles, and local electricity
markets are appropriate solutions to offset the uncertainty associated with the high …

Energy resource management (ERM) is important to an energy system. Effective
management is hard to achieve because of the ubiquitous uncertainty of distributed energy …

When dealing with optimisation problems, Metaheuristics (MHs) quickly come to our minds.
A quick literature review reveals a vast universe of MHs. Although the metaphors behind …

This study develops a novel variant of particle swarm optimization (PSO), which improves its
balance of exploration and exploitation by modifying neighborhood topology, self-adaptive …

In this study, the novel hybrid machine learning approach is proposed in carbon price
fluctuation prediction. Specifically, a research framework integrating DILATED Convolutional …

We propose the concept of “explainergy”, a new way of including explainability in the
metaheuristic performance of algorithms solving problems in the energy domain. To this …

In the energy field, the “WCCI (CEC)/GECCO Competition Evolutionary Computation in the
Energy Domain: Risk-based Energy Scheduling” is a platform for testing and comparing new …

Efficient energy management is critical to building inclusive, safe, resilient, and sustainable
cities and human settlements. Optimizing the operation and planning of smart grids is crucial …