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A Novel Demand Response Model with an Application for a Virtual Power Plant

机译：一种新颖的需求响应模型及其在虚拟电厂中的应用

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摘要

In modern power systems and electricity markets, demand response (DR) programs play an important role enabling the mitigation of critical load periods or price-peaking scenarios, thereby improving system reliability. Price fluctuations, in forward or real-time markets, can be an effective price-based DR mechanism for curtailing or shifting load. However, using dynamic pricing to achieve a desired load profile requires both an accurate demand forecast and knowledge of the price elasticity of demand, which is notoriously difficult to estimate. The limited accuracy of these parameter estimates is the main source of uncertainty limiting appropriate DR implementation. In this paper, we present a novel DR scheme that avoids the need to predict the price elasticity of demand or demand forecast, yet still delivers a significant DR. This is done based on the consumers’ submissions of candidate load profiles ranked in the preference order. The load aggregator then performs the final selection of individual load profiles subject to the total system cost minimization. Additionally, the proposed DR model incorporates a fair billing mechanism that is enhanced with an ex post consumer performance tracking scheme implemented in a context of a virtual power plant aggregating load and generation units.
机译：在现代电力系统和电力市场中，需求响应（DR）计划发挥了重要作用，可以减轻关键的负载周期或价格高峰情况，从而提高系统可靠性。远期或实时市场中的价格波动可能是减少或转移负载的基于价格的有效DR机制。但是，使用动态定价来获得所需的负载曲线既需要准确的需求预测，也需要了解需求的价格弹性，这是众所周知的，很难估计。这些参数估计值的有限准确性是不确定性的主要来源，不确定性限制了适当的DR实施。在本文中，我们提出了一种新颖的DR方案，该方案避免了预测需求价格弹性或需求预测的需求，但仍然提供了重要的DR。这是根据用户提交的按优先顺序排列的候选负载配置文件完成的。然后，负载汇总器将最终选择单个负载配置文件，以使总系统成本最小化。此外，提出的DR模型结合了公平的计费机制，该机制通过在虚拟电厂聚集负载和发电单元的环境中实施的事后消费者性能跟踪方案进行了增强。

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