Electricity market-clearing with stochastic security

In this dissertation we formulate a short-term electricity market-clearing problem with stochastic security criteria. The proposed stochastic security criteria, snake use of probabilistic measures of the expected bald not served or of the loss-of-load probability associated with the random failures of pre-selected sets of generators, lines as well as load disturbances. We snow that by economically penalizing the operation of the market through the associated demand-side costs of involuntary load shedding, the reserve service requirements are determined implicity, thus removing the needs for specifing any a priori reserve requirements. Under this approach, the market-clearing problem gains in flexibility as it can balance file respective expected costs of: (i) the pre-contingency preventive security control actions that include unit commitment, generation and load dispatch as well as reserve scheduling; (ii) the post-contingency corrective actions that deploy reserves through further unit, commitment decisions and load and generation re-dispatch; and, (iii) any post-contingency involuntary load shedding decisions. Case studies illustrate that electricity market-clearing with stochastic security leads to non-negligible economic savings for society; while it can still ensure that consumers benefit from a secure supply of electricity given how they value load shedding.;We then extend the model of electricity market-clearing with stochastic security by proposing a short-term electricity market-clearing formulation capable of accounting for non-dispatchable and intermittent power generation sources like wind power. We show how the electricity market-clearing model can take into account uncertainties in the next day/hours wind power generation predictions as well as those of the demand. Also, We demonstrate how the market-clearing formulation can integrate the scheduling of a large-scale centralized energy storage infrastructure.;Finally we define rigorously the concept of the set of umbrella, contingencies for security-constrained optimal power flow problems, a class of power system scheduling problems to which market-clearing with stochastic: security belongs. We propose an identification method to identify the members of this set by making use of the vector norms of the Lagrange multipliers associated with the post-contingency power balance relations. We suggest a heuristic contingency ranking rule based on those vector norms, and we argue that, the proposed identification rule and ranking method can be of use to system operators when specifying reduced sets of contingencies for security-constrained market-clearing problems.;We derive theoretical results pertaining to the prices of energy and security corresponding to the optimal schedules of the market-clearing process. The key result of this analysis establishes that involuntary load shedding is used after a contingency if and only if the expected marginal costs of scheduling reserves and deploying them are greater than the expected marginal costs of load shedding.