Optimization models have been widely used in the power industry to aid the decision-
making process of scheduling and dispatching electric power generation resources, a …

Static robust optimization (RO) is a methodology to solve mathematical optimization
problems with uncertain data. The objective of static RO is to find solutions that are immune …

The use of wind power is often restricted by the strong interdependence between the
electricity generation and thermal energy generation of combined heat and power units …

The significant growth of gas-fired power plants and emerging power-to-gas (PtG)
technology has intensified the interdependency between electricity and natural gas systems …

This paper proposes a novel model for the day-ahead self-scheduling problem of a virtual
power plant trading in both energy and reserve electricity markets. The virtual power plant …

The development of distributed renewable energy, such as photovoltaic power and wind
power generation, makes the energy system cleaner, and is of great significance in reducing …

The parametric uncertainties inherent in the models of renewable and sustainable energy
systems (RSESs) make the associated decision-making processes of integrated resource …

This paper proposes a distributionally robust optimization model for solving unit commitment
(UC) problems considering volatile wind power generation. The uncertainty of wind power is …

The exceptional benefits of wind power as an environmentally responsible renewable
energy resource have led to an increasing penetration of wind energy in today's power …

Multi-uncertainties impose enormous challenges to the optimal scheduling of power
systems, and two-stage robust optimization (TSRO) theory has been widely investigated and …