Ancillary services in systems with high penetrations of renewable energy sources, the case of ramping
Renewable Energy Sources (RES) are likely to continue the upward trend observed in the past decade. The change from dispatchable generation to an environment in which Independent System Operators (ISOs), Regional Transmission Operators (RTOs), Load Serving Entities (LSEs) and consumers dynamically respond to the conditions in the system and help to alleviate the uncertainty linked to RES requires appropriate tools to evaluate the social benefits and costs of different policies implemented. This paper presents a framework for evaluating the aforementioned effects using an engineering and economic optimization model. The proposed framework is applied to a stylized case study with operations on a test network that simulates a typical day. The objective of the case study is to compare the effects of (1) controllable demand, (2) on-site storage, and (3) upgrading transmission capacity. The different scenarios are evaluated in terms of (1) the percentage of potential wind generation spilled, (2) the total operating cost of production, and (3) the amount of installed capacity needed to maintain operating reliability. The results show that controllable demand improves (reduces) all of the three criteria by alleviating congestion and mitigating wind variability. In contrast, the beneficial effects are smaller for RES's on-site storage, because it does not shift load to off-peak periods or reduce congestion, and for upgrading transmission, because it does not shift load to off-peak periods or mitigate wind variability.
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- Timothy D. Mount, Surin Maneevitjit, Alberto J. Lamadrid, Ray D. Zimmerman, and Robert J. Thomas, 2012.
"The Hidden System Costs of Wind Generation in a Deregulated Electricity Market,"
The Energy Journal,
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- Mount, Timothy D. & Maneevitjit, Surin & Lamadrid, Alberto J. & Zimmerman, Ray D. & Thomas, Robert J., 2011. "The Hidden System Costs Of Wind Generation In A Deregulated Electricity Market," Working Papers 126529, Cornell University, Department of Applied Economics and Management.
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