Journal
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
Volume 44, Issue 1, Pages 615-628Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2012.07.048
Keywords
Optimal stochastic dispatch; Renewable integration; Reserve markets; Risk minimization; Threshold rule; Multi-period dispatch
Categories
Funding
- NSF [1129001, 1135872]
- CERTS
- Inst for Adv Study, HKUST
- Direct For Computer & Info Scie & Enginr [1135872] Funding Source: National Science Foundation
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1129001] Funding Source: National Science Foundation
- Division Of Computer and Network Systems [1135872] Funding Source: National Science Foundation
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [1239178] Funding Source: National Science Foundation
Ask authors/readers for more resources
Risk-limiting dispatch or RLD is formulated as the optimal solution to a multi-stage, stochastic decision problem. At each stage, the system operator (SO) purchases forward energy and reserve capacity over a block or interval of time. The blocks get shorter as operations approach real time. Each decision is based on the most recent available information, including demand, renewable power, weather forecasts. The accumulated energy blocks must at each time t match the net demand D(t) = L(t) - W(t). The load L and renewable power W are both random processes. The expected cost of a dispatch is the sum of the costs of the energy and reserve capacity and the penalty or risk from mismatch between net demand and energy supply. The paper derives computable 'closed-form' formulas for RLD. Numerical examples demonstrate that the minimum expected cost can be substantially reduced by recognizing that risk from current decisions can be mitigated by future decisions; by additional intra-day energy and reserve capacity markets; and by better forecasts. These reductions are quantified and can be used to explore changes in the SO's decision structure, forecasting technology, and renewable penetration. (C) 2012 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available