Intermittent renewable energy generation, which is determined by weather conditions, is increasing in power markets. The efficient integration of these energy sources calls for flexible participants in smart power grids. It has been acknowledged that a large, underutilized, flexible resource lies on the consumer side of electricity generation. Despite the recently increasing interest in demand flexibility, there is a gap in the literature concerning the incentives for consumers to offer their flexible energy to power markets. In this paper, we examine a virtual power plant concept, which simultaneously optimizes the response of controllable electric hot water heaters to solar power forecast error imbalances. Uncertainty is included in the optimization in terms of solar power day-ahead forecast errors and balancing power market conditions. We show that including solar power imbalance minimization in the target function changes the optimal hot water heating profile such that more electricity is used during the daytime. The virtual power plant operation decreases solar power imbalances by 5–10% and benefits the participating households by 4.0–7.5 € in extra savings annually. The results of this study indicate that with the number of participating households, while total profits increase, marginal revenues decrease.

中文翻译：

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利用分布式热存储的灵活性来最小化太阳能预测误差成本

由天气条件决定的间歇性可再生能源发电在电力市场中正在增加。这些能源的高效整合需要智能电网的灵活参与者。人们已经认识到，发电的消费者侧存在着大量的、未充分利用的、灵活的资源。尽管最近人们对需求灵活性的兴趣日益浓厚，但有关消费者向电力市场提供灵活能源的激励措施的文献中仍存在空白。在本文中，我们研究了虚拟发电厂的概念，该概念同时优化了可控电热水器对太阳能预测误差不平衡的响应。太阳能发电日前预测误差和平衡电力市场状况的优化中包含不确定性。我们表明，将太阳能不平衡最小化纳入目标函数会改变最佳热水加热曲线，从而在白天使用更多电力。虚拟发电厂运营可将太阳能发电不平衡现象减少 5-10%，并使参与家庭每年额外节省 4.0-7.5 欧元。这项研究的结果表明，随着参与家庭数量的增加，虽然总利润增加，但边际收入却减少。