期刊
ENERGY
卷 166, 期 -, 页码 755-764出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2018.10.087
关键词
Economic dispatch; Energy storage; Quadratic programming; Unit commitment; Mixed-integer relaxation
资金
- U.S. Department of Energy (DOE) [DE-AC36-08GO28308]
- U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Fuel Cell Technologies Office
- US-Italy Fulbright Commission
- European Union RESILIENT project
- NSF CMMI grant [1461583]
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1461583] Funding Source: National Science Foundation
Economic dispatch for micro-grids and district energy systems presents a highly constrained non-linear, mixed-integer optimization problem that scales exponentially with the number of systems. Energy storage technologies compound the mixed-integer or unit-commitment problem by necessitating simultaneous optimization over the applicable time horizon of the energy storage. The dispatch problem must be solved repeatedly and reliably to effectively minimize costs in real-world operation. This paper outlines a method that greatly reduces, and under some conditions eliminates, the mixed-integer aspect of the problem using complementary convex quadratic optimizations. The generalized method applies to grid-connected or islanded district energy systems comprised of any variety of electric or combined heat and power generators, electric chillers, heaters, and all varieties of energy storage systems. It incorporates constraints for generator operating bounds, ramping limitations, and energy storage inefficiencies. An open-source platform, EAGERS, implements and investigates this optimization method. Results demonstrate a >99% reduction in computational effort when comparing the newly minted optimization strategy against a benchmark commercial mixed-integer solver applied to the same combined cooling, heating, and power problem. (C) 2018 Elsevier Ltd. All rights reserved.
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