Two-stage stochastic unit commitment model including non-generation resources with conditional value-at-risk constraints
Abbreviated Journal Title
Electr. Power Syst. Res.
Stochastic unit commitment; Demand response; Energy storage; Conditional; value-at-risk; Benders decomposition; Sensitivity analysis; TRANSMISSION NETWORK EXPANSION; WIND POWER-GENERATION; ENERGY-STORAGE; DEMAND RESPONSE; SYSTEM; UNCERTAINTIES; OPTIMIZATION; MANAGEMENT; ALGORITHM; RESERVE; Engineering, Electrical & Electronic
This paper presents a two-stage stochastic unit commitment (UC) model, which integrates non-generation resources such as demand response (DR) and energy storage (ES) while including risk constraints to balance between cost and system reliability due to the fluctuation of variable generation such as wind and solar power. This paper uses conditional value-at-risk (CVaR) measures to model risks associated with the decisions in a stochastic environment. In contrast to chance-constrained models requiring extra binary variables, risk constraints based on CVaR only involve linear constraints and continuous variables, making it more computationally attractive. The proposed models with risk constraints are able to avoid over-conservative solutions but still ensure system reliability represented by loss of loads. Then numerical experiments are conducted to study the effects of non-generation resources on generator schedules and the difference of total expected generation costs with risk consideration. Sensitivity analysis based on reliability parameters is also performed to test the decision preferences of confidence levels and load-shedding loss allowances on generation cost reduction. (c) 2014 Elsevier B.V. All rights reserved.
Electric Power Systems Research
"Two-stage stochastic unit commitment model including non-generation resources with conditional value-at-risk constraints" (2014). Faculty Bibliography 2010s. 5480.