1.中国船舶集团风电发展有限公司,北京 100084
2.郑州大学化工学院,河南 郑州 450001
3.中船海为(新疆)新能源有限公司,新疆 乌鲁木齐 830002
杨乐萍(1994—),女,博士,工程师,从事综合能源规划与运行控制技术,E-mail:yanglp@csscwindpower.com.cn。
收稿:2025-10-10,
修回:2025-12-05,
纸质出版:2026-02-28
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杨乐萍, 邓晓宗, 闵烨, 等. 面向购网电量抑制与峰谷收益提升的风电场储能系统控制方法研究[J]. 储能科学与技术, 2026, 15(2): 538-551.
YANG Leping, DENG Xiaozong, MIN Ye, et al. Evaluation of benefits and strategies to reduce grid electricity purchases by wind farms under high price-differential scenarios[J]. Energy Storage Science and Technology, 2026, 15(2): 538-551.
杨乐萍, 邓晓宗, 闵烨, 等. 面向购网电量抑制与峰谷收益提升的风电场储能系统控制方法研究[J]. 储能科学与技术, 2026, 15(2): 538-551. DOI: 10.19799/j.cnki.2095-4239.2025.0895.
YANG Leping, DENG Xiaozong, MIN Ye, et al. Evaluation of benefits and strategies to reduce grid electricity purchases by wind farms under high price-differential scenarios[J]. Energy Storage Science and Technology, 2026, 15(2): 538-551. DOI: 10.19799/j.cnki.2095-4239.2025.0895.
随着电力交易市场价格竞争机制的不断深化,电网对风/光电消纳能力的隐性成本转嫁为显著的上网/下网电价差。枯风季风电出力低于场站负荷需求,需高价购入电网电力以维持运行,导致购网电费激增,旺风季风电场被动响应调峰指令,被迫弃风或低价售电,两者的交替波动增加了风电场运维的不确定性和经济风险。基于此,本工作提出了一种兼顾调峰与场站用电需求的风电场储能经济运行控制策略,通过构建基于购网成本、弃风损失与储能损耗的联合优化框架,综合考虑电网调度指令、日内电价、风机出力特性与储能运行约束,设计了基于动态阈值的储能充放电决策机制。该机制在功率冗余时段按峰谷差异化设置充电阈值,以平衡调峰容量储备与设备启停损耗;在功率不足时段采用电价驱动的分级放电策略,协同保障场站用电与高价放电收益。结果表明,该策略显著提升了弃风时段储能消纳效率,减少了高价购网电量,并通过峰谷套利使储能典型月收益占风电场上网收益的10%以上,同时有效延缓了储能寿命损耗,为高比例新能源场景下储能经济调度提供了可行路径。
With the advancement of market-oriented electricity trading mechanisms
the implicit costs of grid accommodation capacity for wind and solar power have become increasingly apparent through significant on-grid and off-grid price differentials. During low-wind seasons
when wind generation falls below station load demand
wind farms must purchase high-priced grid electricity to maintain normal operations
leading to rapidly rising procurement costs. Conversely
during high-wind seasons
wind farms are often required to comply with peak-shaving directives
resulting in large-scale wind curtailment or low-price electricity sales. This alternating operational pattern amplifies uncertainty and economic risks for wind farm operators. To address these challenges
an economic operation control strategy for energy storage systems is proposed to coordinate peak regulation with station electricity demand. A joint optimization framework is developed
integrating grid electricity purchase costs
wind curtailment losses
and energy storage degradation
while comprehensively considering grid dispatch instructions
time-of-use electricity pricing
wind turbine output characteristics
and energy storage operational constraints. Based on this framework
a dynamic threshold-based charging and discharging decision mechanism is designed. It sets differentiated charging thresholds during periods of power surplus
informed by peak-valley price variations
to balance peak regulation capacity reserves with equipment switching losses. During power shortage periods
an electricity price-driven hierarchical discharging strategy is adopted to ensure station electricity demand while maximizing high-priced electricity discharge revenue. Results demonstrate that this strategy significantly improves energy storage utilization during wind curtailment periods
reduces high-priced grid electricity purchases
and generates typical monthly energy storage revenues exceeding 10% of the wind farm's feed-in revenue through peak-valley arbitrage. Moreover
it mitigates energy storage degradation and extends system lifespan
offering a practical and economically viable solution for energy storage dispatch in high-penetration renewable energy scenarios.
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