Scheduling and Pricing for Expected Ramp Capability in Real-Time Power Markets
Scheduling and Pricing for Expected Ramp Capability in Real-Time Power Markets
复制标题
实时电力市场中预期爬坡能力的调度和定价
DOI：
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复制
发表时间：
2016
影响因子：
6.6
通讯作者：
M. O’Malley
中科院分区：
文献类型：
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作者：
E. Ela;M. O’Malley
更高的可变可再生能源发电渗透率正在世界各地不同的电力系统中发生。这些资源增加了系统上的可变性和不确定性，这必须通过增加系统资源的灵活性来适应，以便保持可靠性。许多调度策略已被讨论和介绍，以确保这种灵活性是在多个时间尺度。为了满足可变性，即系统条件的预期变化，最近引入了两种策略：时间耦合多周期市场清算模型和匝道容量约束的结合。为了适当地评估这些方法，重要的是评估效率和可靠性。但是，评估激励结构也很重要，以确保要求以不同方式执行的资源有适当的激励来遵循这些方向，这是模拟研究中经常忽略的一个步骤。我们发现这两种方法都有优点和缺点。我们还发现，在多期市场模型中的前瞻视野长度可以影响激励。本文提出了调度和定价方法，以确保可靠，有效地满足预期的坡道，并与基于真正的边际成本，激励资源做市场的指导下的相关价格。案例研究表明，新方法的改进。
Higher variable renewable generation penetrations are occurring throughout the world on different power systems. These resources increase the variability and uncertainty on the system which must be accommodated by an increase in the flexibility of the system resources in order to maintain reliability. Many scheduling strategies have been discussed and introduced to ensure that this flexibility is available at multiple timescales. To meet variability, that is, the expected changes in system conditions, two recent strategies have been introduced: time-coupled multi-period market clearing models and the incorporation of ramp capability constraints. To appropriately evaluate these methods, it is important to assess both efficiency and reliability. But it is also important to assess the incentive structure to ensure that resources asked to perform in different ways have the proper incentives to follow these directions, which is a step often ignored in simulation studies. We find that there are advantages and disadvantages to both approaches. We also find that look-ahead horizon length in multi-period market models can impact incentives. This paper proposes scheduling and pricing methods that ensure expected ramps are met reliably, efficiently, and with associated prices based on true marginal costs that incentivize resources to do as directed by the market. Case studies show improvements of the new method.