基于“效益-精度”对冲的两级电力市场负荷预测技术

电力市场的引入对协助电力行业实现电网的稳定运行和规划，促进电能的有效利用和调度，避免资源的浪费，发挥着不可替代的作用。在各国的电力市场中，售电公司/大用户通常会采用预测模型开展负荷预测，并为日前电力市场交易提供依据。当前提出的各负荷预测模型主要以“精准”作为唯一的优化目标，缺乏对各市场价格的差异性波动及售电公司/大用户经济效益的考虑。提出兼顾精确性和经济性的目标策略，建立基于“效益-精度”对冲的两级电力市场负荷预测技术，此技术基于传统负荷预测技术，在目标函数中引入成本因素，采用改进的反向传播法作为网络训练方法。通过对纽约地区负荷数据开展实例验证，验证结果显示，该方法对量化售电公司效益，推进其经济性和准确性综合提升，具有明显成效。

“Cost-Accuracy” Hedging Based Load Forecasting Technique on Two-Stage Electricity Market

Electricity plays an irreplaceable role in the national economy as a fundamental industry. Electricity contributes to the stable operation and scheduling of the power grid, promotes the efficient consumption of energy and avoids waste of resources. In most of electricity markets, the Load Serving Entities (LSEs) would submit the load scheduling by adopting model of load forecasting, which can be provided as a basis for trading in day ahead market. At present, most of load forecasting model focus on predicting accuracy instead of the fluctuation of market prices and LSEs’ benefits. This paper proposes a load forecasting strategy which balances accuracy and economic efficiency for two-stage electricity markets and establishes a “Cost-Accuracy” hedging based load forecasting technique (CAHFT). This technique is based on the traditional load forecasting technique, the term cost is introduced into the objective function, the improved backpropagation is used as the neural network for training. Case studies uses load data in New York area, and the verification results show that CAHFT has obvious effects on quantifying the benefits of the LSEs and contributing to the comprehensive improvement of its economic efficiency and accuracy.