Optimal probabilistic scenario‐based operation and scheduling of prosumer microgrids considering uncertainties of renewable energy sources

Abstract

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A configuration optimization framework for renewable energy systems integrating with electric‐heating energy storage in an isolated tourist area

“…7 Electric power generation with wind and solar energy has low environmental pollution, but its output power is intermittent and random. 8,9 The combined cooling, heating, and power (CCHP) can provide electric energy and heating energy simultaneously, whose energy efficiency can reach 80%-90%. It can realize cascade utilization of energy with higher efficiency and reduce pollution emission of polluted gas, which bring them a promising future.…”

“…Optimizing energy structure and improving energy utilization rate have become effective measures to solve energy and environmental problems 7 . Electric power generation with wind and solar energy has low environmental pollution, but its output power is intermittent and random 8,9 . The combined cooling, heating, and power (CCHP) can provide electric energy and heating energy simultaneously, whose energy efficiency can reach 80%‐90%.…”

Reliability‐based operation studies of wave energy converters using modified PJM approach

“…Thus, in order to study the operation of wave power plants, ideas can be obtained from articles that have studied the operation of other renewable energy resources. In Reference 9, an optimal probabilistic scenario–based method is proposed to perform the operation scheduling of the micro grids considering the uncertainties associated with the renewable energy resources. In this paper, to consider the uncertainty nature of the wind turbines and photovoltaic systems, different scenarios are generated using the Monte Carlo Simulation method.…”

Optimization of microenergy grid including adiabatic compressed air energy storage by considering uncertainty of intermittent parameters

“…40 In addition, some advanced techniques such as hybrid and multistage methods are also developed in recent works to boost the forecasting accuracy of uncertain parameters. On the other hand, it is possible to model stochastic behavior of operational parameters using mathematical-based methods, namely stochastic programming, 41 robust optimization, 42 and information gap decision theory (IGDT). 43…”