| 基于纵向修正ARIMA的负荷聚合商潜力计算及调峰策略 |
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| 作者姓名： | 周颖 石坤 李德智 陈宋宋 窦迅 严胜 |
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| 作者单位： | 需求侧多能互补优化与供需互动技术北京市重点实验室中国电力科学研究院有限公司,需求侧多能互补优化与供需互动技术北京市重点实验室中国电力科学研究院有限公司,需求侧多能互补优化与供需互动技术北京市重点实验室中国电力科学研究院有限公司,需求侧多能互补优化与供需互动技术北京市重点实验室中国电力科学研究院有限公司,南京工业大学 电气工程与控制科学学院,国家电网公司 |
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| 基金项目： | 基金项目：国家电网公司科技项目（以新能源为主体的新型电力系统实施路径研究，5100-202155289A-0-0-00） |
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| 摘 要： | 负荷聚合商组织需求侧资源参与调峰市场和电能量市场时，存在负荷预测准确度不够导致合同购电量误差大、市场界限模糊导致考核结算重复等问题，因此文中提出基于纵向修正差分自回归滑动平均(autoregressive integrated moving average, ARIMA)模型的负荷聚合商潜力计算和调峰策略。首先，利用纵向修正ARIMA算法预测基线负荷，构建负荷聚合商的调峰潜力测算模型，挖掘需求侧资源的可调节能力，为电力市场交易提供数据基础；其次，制定电能量市场与调峰市场的负荷偏差考核方式，以月度滚动时域综合结算收益最大为目标，构建考虑偏差考核的负荷聚合商调峰模型；最后，基于某典型地区负荷聚合商月度历史负荷数据，对所提方法进行算例分析。结果表明考虑负荷偏差考核的负荷聚合商调峰策略可以提升聚合商的调峰收益约23.7%,降低负荷聚合商峰谷差约10%,验证了文中方法的合理性和有效性。
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| 关 键 词： | 可调潜力 纵向修正 差分自回归滑动平均(ARIMA)模型 滚动优化 调峰策略 偏差考核 |
| 收稿时间： | 2022/9/15 0:00:00 |
| 修稿时间： | 2023/1/5 0:00:00 |
Calculation of load aggregator potential and peak regulation strategy based on longitudinal modified ARIMA |
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| Authors: | ZHOU Ying SHI Kun LI Dezhi CHEN Songsong DOU Xun YAN Sheng |
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| Affiliation: | Beijing Key Laboratory of Demand-Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology China Electric Power Research Institute,Beijing Key Laboratory of Demand-Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology China Electric Power Research Institute,Beijing Key Laboratory of Demand-Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology China Electric Power Research Institute,Beijing Key Laboratory of Demand-Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology China Electric Power Research Institute,Nanjing Tech University Electrical Engineering and Control Science,State Grid Corporation of China |
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| Abstract: | In response to the exist problems such as the lack of accuracy in load forecasting leading to large errors in contracted power purchases, and the more ambiguous market boundaries leading to duplication in assessment and settlement, when load aggregators organize demand-side resources to participate in the peaking market and the electricity energy market, a load aggregator potential calculation and peaking strategy based on the longitudinal modified Autoregressive Integrated Moving Average model (ARIMA) is proposed. First, the longitudinal modified ARIMA forecasting algorithm is used to forecast the baseline, build a model to measure the peak regulation potential of load aggregators, and explore the adjustable capacity of demand-side resources to provide a data base for power market trading. Second, to develop a load deviation assessment method for the electricity energy market and the peaking market, and on this basis, con-struct a load aggregator peaking model considering deviation assessment with the goal of maximizing the monthly rolling time-domain comprehensive settlement revenue. Finally, the proposed method is analyzed based on the month-ly historical load data of load aggregators in a typical region. The results show that the proposed load aggregator peak-ing strategy considering load deviation assessment can improve the peaking revenue of aggregators by about 23.7% and reduce the load aggregator peak-to-valley difference of about 10%, which verifies the rationality and effectiveness of the method.
Keywords: adjustable potential, vertical correction, ARIMA algorithm, rolling optimization, peaking strategy, deviation assessment |
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| Keywords: | adjustable potential vertical correction ARIMA algorithm rolling optimization peaking strategy deviation assessment |
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