Most existing data-driven power system short-term voltage stability assessment (STVSA)
approaches presume class-balanced input data. However, in practical applications, the …

The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …

Optimal management and planning of microgrids (MG) are the most important goals for
operators. In this study, a Multiobjective Genetic Algorithm (MOGA) is applied to the …

Energy has been the cornerstone for all the technological advancements that are happening
in the world. The need for energy at present is great than ever before and it is foreseen to …

The continuously growing population and urban growth rates are responsible for the sharp
rise in energy consumption, which leads to increased CO 2 emissions and demand-supply …

Many countries have experienced a surge in the level of the penetration of solar PV systems
in the last decade. A huge portion of the newly deployed PV systems are connected to low …

In this paper, we formulate a stochastic long-term optimization planning problem that
addresses the cooperative optimal location and sizing of renewable energy sources (RESs) …

As power systems around the world are rapidly evolving to achieve decarbonization
objectives, it is crucial that power system planners and operators use appropriate models …

Net/nearly zero energy buildings (NZEBs) are being recognized as a promising solution to
improve environmental friendliness and reduce energy consumption in the building sector …

Compared to traditional building energy systems, the energy systems used in nearly/net
zero energy buildings face more complex challenges due to highly uncertain characteristics …