论文标题

使用分销系统中的峰值负载定价的互动计划和操作

Interactive Planning and Operations using Peak Load Pricing in Distribution Systems

论文作者

Ilic, Marija, Gough, Matthew

论文摘要

分布式能源资源(DERS)的出现为分销系统的规划和运营提供了挑战和机会。这些资源可以以与传统网络操作和计划竞争的方式部署,因为DERS可以为电网运营商和公用事业提供许多重要的服务。本文提出了一种新的方法,可以使用动态峰值定价(PLP)方法来估算DERS和传统投资之间的权衡。 PLP是一种定价策略,用于依赖于时间的非遗产商品,并基于长期边际成本的理论。重要的是,PLP处理能力利用率和消费者福利之间的权衡。因此,容量价格的设定是在投资将带来的额外社会福利所抵消的投资成本的位置。重要的是,它允许没有提高付款的资本成本回收。这种动态PLP方法论是基于动态监控和决策系统(DYMONDS)框架的互动计划和操作模型,有助于将电能系统中许多利益相关者的物理,信息和经济激励措施保持一致。 Dymonds框架有助于解决PLP的缺点,这些框架与PLP模型的计算复杂性有关,考虑到在长期投资范围内具有不同回报期的不同技术。结果表明,动态PLP模型可以准确评估不同技术在减少拥塞和增加服务客户数量方面的影响。这使网络运营商可以轻松识别每个投资周期中应选择哪些技术。

The emergence of Distributed Energy Resources (DERs) provides both challenges and opportunities for the planning and operations of distribution systems. These resources can be deployed in a manner that is either complementary to or in competition with traditional network operations and planning as the DERs can provide numerous important services to grid operators and utilities. This paper presents a novel method to estimate the trade off between DERs and traditional investments using a dynamic Peak-Load Pricing (PLP) methodology. PLP is a pricing strategy for a time-dependent quantity of a non-storable commodity and is based on the theory of long-run marginal costs. Importantly PLP deals with the trade-off between capacity utilization and consumer welfare. Therefore, the capacity price is set at a point where the cost of investment is exactly offset by the additional social welfare that the investment would bring. Importantly it allows for capital cost recovery with no uplift payments. This dynamic PLP methodology is an interactive planning and operations model based on the Dynamic Monitoring and Decision Systems (DyMonDS) Framework which helps to align physical, information, and economic incentives across many stakeholders within the electric energy system. The DyMonDS framework helps to solve the drawbacks of PLP, which are related to the computational complexity of the PLP models considering different technologies with different payback periods over a long investment horizon. Results show that the dynamic PLP model can accurately value the impact of different technologies in reducing congestion and increasing the number of customers served. This allows the network operator to easily identify which technologies should be chosen in each investment cycle.

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