2021
DOI: 10.1016/j.orl.2021.01.012
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Energy and reserve dispatch with distributionally robust joint chance constraints

Abstract: We develop a two-stage stochastic program for energy and reserve dispatch, which ensures the safe operation of a power system with a high penetration of renewables and a strong interdependence with the natural gas system. Distributionally robust joint chance constraints with Wasserstein ambiguity sets ensure that there is no need for load shedding and renewable spillage with high probability under any distribution compatible with the given statistical data. To make this problem tractable, we solve it in linear… Show more

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Cited by 66 publications
(38 citation statements)
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“…The constraint of the system frequency in ( 17) is a joint chance constraint, and it can be split into two separated constraints according to Bernoulli's inequality [27], as…”
Section: P2: Minmentioning
confidence: 99%
See 1 more Smart Citation
“…The constraint of the system frequency in ( 17) is a joint chance constraint, and it can be split into two separated constraints according to Bernoulli's inequality [27], as…”
Section: P2: Minmentioning
confidence: 99%
“…Constraints ( 31)-( 34) are transformed from chance constraint (27), where φ j,z , φ j,z , and ψ z are the dual variables of the constraints for ω j,z . ϑ j,z is an auxiliary variable.…”
Section: P2: Minmentioning
confidence: 99%
“…[19] [32]. Taking constraint (4) with probability1, for example, two deterministic constraints can be obtained by matching the zero-and first-order coefficients of on both sides of ( 13) [32].…”
Section: A Linear Decision Rule Approximatementioning
confidence: 99%
“…[19] [32]. Taking constraint (4) with probability1, for example, two deterministic constraints can be obtained by matching the zero-and first-order coefficients of on both sides of ( 13) [32]. Thus, the above semi-infinite problem with the decision rule approximation can be reexpressed as the following form,…”
Section: A Linear Decision Rule Approximatementioning
confidence: 99%
“…To construct an ambiguity set, two paradigms exist in the literature, namely metric-and moment-based approaches. In the former, the ambiguity set encompasses all distributions that are close to an empirical distribution, measured by a probability distance metric [6]- [9]. In the latter, the ambiguity set contains all distributions satisfying identical moment constraints [2], [5].…”
Section: Introductionmentioning
confidence: 99%