分散式电采暖负荷协同优化运行策略

Collaborative Optimal Operation Strategy for Decentralized Electric Heating Loads

分散式的电采暖负荷是一种典型的热储能设备,功率较大,电能产出的热量具有滞后性和存储性,现有运行方式单一且仅针对单个设备,无法实现区域范围内电采暖负荷的协同优化。针对上述问题,文中首先提出了智能电暖网络的概念、架构以及衡量该网络运行效果的优化指标。其次,提出了智能电暖网络的确定性优化运行模型,该模型首先在保证最大功率限制的约束下,求解可达到的最大舒适度;再将最大的舒适度作为约束,寻求使运行电费最小化的运行策略。进而,在等效热参数模型的基础上引入温度波动不确定量,构建了确定性模型对应的鲁棒优化模型。算例分析表明,相比现有的实时温控策略,确定性优化策略可有效控制尖峰负荷,明显提高温度效用,降低运行电费;鲁棒优化策略比确定性优化策略更好地保证了用户舒适度,但运行电费略有升高。所提优化策略充分响应峰谷电价,在实现经济运行的同时,可以间接响应电网削峰填谷。

As a typical heat energy storage device,the decentralized electric heating load has a large power and contributes to the hysteresis and storability of electric energy output. But since the existing operation control mode is unitary and available only for single equipment,its impossible to achieve collaborative optimization of electric heaters on a regional scale. For this reason,this paper proposes the concept and framework of a smart electric heating network as well as optimization indexes that could be used to measure the running effect of this network. Then a deterministic operation optimization model for this smart electric heating network is put forward.On the premise of ensuring peak-power limitation,the model is able to calculate the achievable maximum comfort level. By taking the maximum comfort level as a constraint,the minimum operating electricity charges can be calculated. Further,by introducing the uncertainty temperature fluctuation into the equivalent thermal parameter（ ETP） model,a robust optimization model for the smart electric heating network is developed. The analysis of examples shows that,compared with the existing temperature control strategies,the deterministic optimization strategy is able to effectively reduce the peak load,significantly improve temperature control effect,and lower operating electricity charges. Compared with the deterministic optimization strategy,the robust optimization strategy can better ensure the comfort level,with its operating power charges slightly higher than those with the deterministic optimization strategy. The proposed optimization strategies can fully respond to the time-of-use price,which realizes load shifting indirectly while enhancing users＇ economic benefits.