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Optimal Operation of Combined Heat and Power System Based on Forecasted Energy Prices in Real-Time Markets

机译:实时市场中基于预测能源价格的热电联产系统的最优运行

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摘要

This paper develops a discrete operation optimization model for combined heat and powers (CHPs) in deregulated energy markets to maximize owners’ profits, where energy price forecasting is included. First, a single input and multi-output (SIMO) model for typical CHPs is established, considering the varying ratio between heat and electricity outputs at different loading levels. Then, the energy prices are forecasted with a gray forecasting model and revised in real-time based on the actual prices by using the least squares method. At last, a discrete optimization model and corresponding dynamic programming algorithm are developed to design the optimal operation strategies for CHPs in real-time. Based on the forecasted prices, the potential operating strategy which may produce the maximum profits is pre-developed. Dynamic modification is then conducted to adjust the pre-developed operating strategy after the actual prices are known. The proposed method is implemented on a 1 MW CHP on a typical day. Results show the optimized profits comply well with those derived from real-time prices after considering dynamic modification process.
机译:本文针对放松管制的能源市场中的热电联产(CHP)开发了一种离散的运行优化模型,以最大化所有者的利润,其中包括了能源价格预测。首先,考虑到在不同负载水平下热电输出之间的变化比例,建立了典型热电联产的单输入多输出(SIMO)模型。然后,使用灰色预测模型对能源价格进行预测,并使用最小二乘法基于实际价格实时进行修改。最后,建立了离散优化模型和相应的动态规划算法,以实时设计热电联产的最佳运行策略。根据预测价格,预先制定了可能产生最大利润的潜在经营策略。然后在知道实际价格后进行动态修改以调整预先制定的操作策略。建议的方法在典型的一天在1 MW CHP上实施。结果表明,在考虑了动态修改过程之后,优化后的利润与实时价格衍生的利润非常吻合。

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