Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability
Abstract
This article proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that an optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.
- Authors:
-
- SLAC National Accelerator Lab., Menlo Park, CA (United States); Univ. of Victoria, BC (Canada). Inst. for Integrated Energy Systems and Mechanical Engineering Dept.
- Univ. of Victoria, BC (Canada). Inst. for Integrated Energy Systems and Mechanical Engineering Dept.
- Publication Date:
- Research Org.:
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE; California Energy Commission; University of Victoria
- OSTI Identifier:
- 1425624
- Grant/Contract Number:
- AC02-76SF00515
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 213; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 29 ENERGY PLANNING, POLICY, AND ECONOMY; Electricity pricing; Bulk electric system; Optimal energy dispatch; Optimal ramping; Renewable integration; Resource allocation
Citation Formats
Chassin, David P., Behboodi, Sahand, and Djilali, Ned. Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability. United States: N. p., 2018.
Web. doi:10.1016/j.apenergy.2018.01.041.
Chassin, David P., Behboodi, Sahand, & Djilali, Ned. Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability. United States. https://doi.org/10.1016/j.apenergy.2018.01.041
Chassin, David P., Behboodi, Sahand, and Djilali, Ned. Sun .
"Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability". United States. https://doi.org/10.1016/j.apenergy.2018.01.041. https://www.osti.gov/servlets/purl/1425624.
@article{osti_1425624,
title = {Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability},
author = {Chassin, David P. and Behboodi, Sahand and Djilali, Ned},
abstractNote = {This article proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that an optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.},
doi = {10.1016/j.apenergy.2018.01.041},
journal = {Applied Energy},
number = C,
volume = 213,
place = {United States},
year = {2018},
month = {1}
}
Web of Science
Figures / Tables:
