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

机译:综合单电市场的短期电力负荷预测(I-SEM)

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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.
机译:正在重建爱尔兰电力市场结构,以满足欧盟第三能源包的要求。即将到来的综合单电市场(I-SEM)在许多方面与当前的市场结构不同。但是,这项研究涉及I-SEM下的平衡责任问题。鉴于平衡市场价格的波动性,在世界各地的同类结构市场中观察到,爱尔兰供应公司需要能够准确地预测客户在日前市场的负担,以便在平衡市场管理风险。本文介绍了供应商实施电力短期负荷预测(STLF)的供应商的手段。使用神经网络模型以及Holt-Winters方法的双季节性指数平滑变化。来自爱尔兰市场的数据用于预测供应公司的负载以及国家负荷,使用这些方法。通过MAPE测量(平均绝对百分比误差),两种方法产生的阳性结果低于3 %。设想,在这些结果中,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,以提出适度准确的出价,以确保其在现代市场中的地位并减少其职位。在平衡市场中累施的任何财务影响的潜力。

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