Short-term electricity load forecasting for the integrated single electricity market (I-SEM)

K. Kavanagh, M. Barrett, M. Conlon
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引用次数: 5

Abstract

The electricity market structure in Ireland is being reconstructed in order to meet with the requirements of the EU Third Energy Package. The forthcoming Integrated-Single Electricity Market (I-SEM) differs from the current market structure in many ways. However this research addresses the issue of balance responsibility under the I-SEM. Given the volatility of prices in the Balancing market, observed in similarly-structured markets around the world, Irish supply companies need to be able to accurately forecast their customers' load in the Day-Ahead market in order to manage risk in the Balancing market. This paper presents a means for suppliers to implement short-term load forecasting (STLF) of electricity. A Neural Network model is used as well as a Double Seasonal Exponential Smoothing variation of the Holt-Winters method. Data from the Irish market was used to forecast a supply company's load as well as the national load, using these methods. Measured by MAPE (mean absolute percentage error), both methods produced positive results of below 3%. It is envisaged that with these results, a supply company operating in the Irish market should be able to apply these forecasting methods to their historical customer data to submit modestly accurate bids, with the intention of securing their position in the Day-Ahead market and reducing the potential of any financial implications accruing in the Balancing market.
综合单一电力市场的短期负荷预测
爱尔兰的电力市场结构正在重建,以满足欧盟第三能源一揽子计划的要求。即将到来的综合单一电力市场(I-SEM)在许多方面不同于当前的市场结构。然而,本研究解决了I-SEM下的平衡责任问题。鉴于平衡市场价格的波动性,在世界各地类似结构的市场中观察到,爱尔兰供应公司需要能够准确预测其客户在前一天市场的负荷,以便管理平衡市场的风险。提出了一种电力供应商短期负荷预测(STLF)的方法。采用神经网络模型和双季节指数平滑变化的霍尔特-温特斯方法。来自爱尔兰市场的数据被用来预测供应公司的负荷以及国家负荷,使用这些方法。通过MAPE(平均绝对百分比误差)测量,两种方法的阳性结果均低于3%。根据这些结果,在爱尔兰市场运营的供应公司应该能够将这些预测方法应用于其历史客户数据,以提交适度准确的报价,以确保其在日前市场中的地位,并减少平衡市场中积累的任何财务影响的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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