期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 12, 期 1, 页码 368-377出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2020.2998408
关键词
Planning; Power systems; Capacity planning; Renewable energy sources; Wind power generation; Energy resolution; Portfolios; Bulk power system planning; computational tractability; flexibility; ramping; renewable energy generation; variability
资金
- Natural Sciences and Engineering Research Council of Canada, Ottawa, ON
- Ireland Canada University Foundation, Dublin, Republic of Ireland
The rapid increase of renewable energy adoption in power systems requires flexibility to manage variability and uncertainty. This paper proposes a new approach to plan the dispatchable generation mix of a power system using historical data, bridging the gap between long-term capacity planning and short-term operational needs.
We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, power systems need to have an adequate supply of flexibility to allow for suitable management of short-term operations. So far most of the work in this area has neglected how flexibility needs associated with renewables are fulfilled as part of dispatchable generation capital investments decisions. To address this challenge, we propose an approach to plan the dispatchable generation mix of a power system as needed to counteract variability and uncertainty associated with significant shares of variable renewable generation. The approach exploits the linear time-invariant feature of variable generation variability using historical phase planes of capacity (in MW) and ramp (in MW/min) to bridge the gap between long-term capacity planning and short-term intra-hour flexibility needs. This approach is much more computationally tractable than other proposals, while also being able to capture adequately short-term operational features like ramping and net load variability. Numerical tests are performed on realistic datasets to substantiate the effectiveness of the approach.
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