Name
Title | ||
|---|---|---|
A stochastic, contingency-based security-constrained optimal power flow for the procurement of energy and distributed reserve |
Abstract | ||
|---|---|---|
It is widely agreed that optimal procurement of reserves, with explicit consideration of system contingencies, can improve reliability and economic efficiency in power systems. With increasing penetration of uncertain generation resources, this optimal allocation is becoming even more crucial. Herein, a problem formulation is developed to solve the day-ahead energy and reserve market allocation and pricing problem that explicitly considers the redispatch set required by the occurrence of contingencies and the corresponding optimal power flow, static and dynamic security constraints. Costs and benefits, including those arising from eventual demand deviation and contingency-originated redispatch and shedding, are weighted by the contingency probabilities, resulting in a scheme that contracts the optimal amount of resources in a stochastic day-ahead procurement setting. Furthermore, the usual assumption that the day-ahead contracted quantities correspond to some base case dispatch is removed, resulting in an optimal procurement as opposed to an optimal dispatch. Inherent in the formulation are mechanisms for rescheduling and pricing dispatch deviations arising from realized demand fluctuations and contingencies. Because the formulation involves a single, one stage, comprehensive mathematical program, the Lagrange multipliers obtained at the solution are consistent with shadow prices and can be used to clear the day-ahead and spot markets of the different commodities involved. Co-optimization of energy and reserves, including system contingency requirementsComplete AC power flow formulation with static and dynamic security constraintsLagrange multipliers determine various day-ahead and spot market commodity prices.Comparison with traditional method shows improvements in system security and costs. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.dss.2013.04.006 | Decision Support Systems |
Keywords | Field | DocType |
optimal dispatch,contingency-based security-constrained optimal power,corresponding optimal power flow,day-ahead energy,problem formulation,optimal allocation,stochastic day-ahead procurement setting,optimal procurement,optimal amount,base case dispatch,pricing dispatch deviation,power systems,stochastic optimization,smart grid | Shadow price,Economic efficiency,Data mining,Stochastic optimization,Mathematical optimization,Smart grid,Computer science,Microeconomics,Electric power system,AC power,Procurement,Spot market | Journal |
Volume | Issue | ISSN |
56 | C | 0167-9236 |
Citations | PageRank | References |
5 | 1.02 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos E. Murillo-Sánchez | 1 | 5 | 1.02 |
| Ray D. Zimmerman | 2 | 8 | 1.91 |
| C. Lindsay Anderson | 3 | 35 | 11.16 |
| Robert J. Thomas | 4 | 96 | 13.61 |