Risk-averse stochastic model predictive control-based real-time operation method for a wind energy generation system supported by a pumped hydro storage unit

Application of information gap decision theory in practical energy problems: A comprehensive review

“…As an example, CAES has been utilized to cope with stochastic nature of uncertainties like wind [35,36] and demand [37]. Additionally, pumped hydro storage (PHS) has been used to handle the uncertainties like the uncertainties of stream flow [38], solar systems [39], wind units [40,41,42] and loads [43].…”

Potential of model predictive control of a polder water system including pumps, weirs and gates

“…Therefore, correct modeling of the pump behavior (head, discharge and power) is essential to minimize energy cost or energy consumption. [10] use stochastic model predictive control on a reservoir-pump-wind-turbine system, but the dynamics of the pumps are not taken into account. One way to overcome the heavy computational burden is to not minimize the energy used by the pumps directly, but the number of switching intervals [11] or total on-time of the pumps [12].…”

Automatic risk adjustment for profit maximization in renewable dominated short‐term electricity markets

“…Risk awareness in performance maximization methods has attracted a high level of interest within the power systems community, including several studies on conventional electricity generation, [14][15][16] energy storage systems, 17,18 weather-dependent generation, 7,8,19,20 demand-response, 12,21,22 and hybrid power plants. [9][10][11][23][24][25][26] Overall, following a scenario-based stochastic optimization framework, most authors incorporate risk measures, for example, the conditional value-at-risk (CVaR), in the objective function to assign higher weights to the scenarios with the lowest profits.…”