An electricity market with a probabilistic spinning reserve criterion

By François Bouffard, F. D. Galiana. IEEE Transactions on Power Systems, 2004

271 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/565a593ba5481aadba7c27e747224206541b5a57

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Citations in the corpus

Spinning Reserve Estimation in Microgrids (2009, methodology): “One way to limit computational complexity is to replace the higher order terms in the product expansions of these probabilities by upper bounds [8], [21].”
Optimizing the Spinning Reserve Requirements Using a Cost/Benefit Analysis (2007, background): “Bouffard and Galiana [12] have proposed a pool market clearing process that includes a probabilistic reserve determination.”
Market-clearing with stochastic security-part I: formulation (2005, methodology): “This paper and its companion [13] contribute to this research effort by developing a new market-clearing formulation with the following generalizations and improvements of the previous work in [2]: a) Time-coupling generation constraints like minimum up and down times as well as ramping limits are c”
Stochastic security for operations planning with significant wind power generation (2008, background): “This is a weakness that has been recognized for some time now, and several authors have investigated ways to better represent the impact of contingency probabilities on operating reserve levels [25], [26].”
Cost of Reliability Analysis Based on Stochastic Unit Commitment (2008, background): “As computational requirements for LOLE indices and expected-energy-not-supplied (EENS) matrices are complicated by their nonlinear and combinatorial nature, [11] defined LOLE and EENS explicitly in terms of unit commitment and dispatch variables as well as forced outage rates.”
Energy and reserve pricing in security and network-constrained electricity markets (2005, methodology): “To derive probabilistic indices such as loss-of-load probability (LOLP) and expected unserved energy (EUE), a number of approaches have been proposed in the literature: the widely used decision tree methods [16], [17] and a probabilistic unit commitment method [18].”