论文标题
电力最终用户消费者利润最大化：一种在线方法
Electric End-User Consumer Profit Maximization: An Online Approach
论文作者
论文摘要
智能网格概念中通信技术的快速增长可以以在线方式提供/向所有消费者提供数据和控制信号。这可以为最终用户客户提供更多的参与。这些类型的客户不一定具有存储大量历史数据的强大预测工具或能力。此外，相关信息并不总是先验地知道，而决策需要在非常有限的时间内快速做出。这些局限性以及决策的新结构，这是从有限的信息中非常快速地做出决定的必要性，这意味着要研究一个新型框架的要求：在线决策。在这项研究中，我们为实时操作响应式最终用户电气客户提供了一个在线约束的凸优化框架。在此在线决策框架中，提出了两种情况的算法：决策时没有预测数据，并且有限数量的远期时间段预测不确定参数。模拟结果表现出该模型在易于实施过程中获得可观利润的能力。进行全面的数值测试用例，以与现有的替代模型进行比较。
The fast growth of communication technology within the concept of smart grids can provide data and control signals from/to all consumers in an online fashion. This could foster more participation for end-user customers. These types of customers do not necessarily have powerful prediction tools or capability of storing a large amount of historical data. Besides, the relevant information is not always known a priori, while decisions need to be made fast within a very limited time. These limitations and also the novel structure of decision making, which comes from the necessities to make the decision very fast with a limited amount of information, implies a requirement for investigating a novel framework: online decision-making. In this study, we propose an online constrained convex optimization framework for operating responsive end-user electrical customers in real-time. Within this online-decision-making framework, algorithms are proposed for two cases: no prediction data is available at the moment of decision-making, and a limited number of forward time periods predictions of uncertain parameters are available. The simulation results exhibit the capability of the model to achieve considerable profits in an easy-to-implement procedure. Comprehensive numerical test cases are performed for comparison with existent alternative models.
