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Cost impact of dynamically managing generation reserves

机译:动态管理发电储备的成本影响

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Generation reserves are needed to maintain the real time balance between power supply and power demand. Because power is noninventoriable, power generation follows power demand. Demand for power varies considerably depending on the time of day, day of the week and season. The predictable portion of power demand is met by purchasing firm energy on a day ahead or real time market. The random unpredictable portion of demand is met by purchasing a set of online and offline generation reserves on an ancillary market. The total energy purchasing cost includes payments for firm energy and payments for generation reserves. The latter include fixed capacity payments for reserve generation capacities and variable payments for the random energy produced from these reserves. The main contribution of this paper is to present an optimization model that captures the dynamism in the selection of the dispatch interval to determine the amount of firm energy and reserve capacities given a set of market prices. This is done by explicitly including in the model the duration of the dispatch period and the frequency this decision is reevaluated. In this model the randomness of the demand is captured by using a Doubly Truncated Normal Distribution. The cost incurred to activate generation reserves is modeled as a Poisson process. The total model captures the price differences from using different reserve sources. An empirical example is presented to illustrate the cost benefits of using the method proposed in this research with two different strategies: a static strategy and a dynamic strategy. It is shown that dynamically setting generation reserves results in cost savings.
机译:需要发电储备来维持电源和电力需求之间的实时平衡。因为电力是无法盘点的,所以发电遵循电力需求。电力需求根据一天中的时间,星期几和季节的不同而有很大差异。电力需求的可预测部分可以通过在未来一天或实时市场上购买公司能源来满足。通过在辅助市场上购买一组在线和离线发电储备,可以满足需求的随机不可预测部分。能源购买总成本包括公司能源支付和发电储备支付。后者包括针对储备发电能力的固定容量支付,以及针对这些储备产生的随机能量的可变支付。本文的主要贡献是提出了一种优化模型,该模型可以捕捉调度间隔选择中的动态性,从而在给定的市场价格下确定公司的能源量和储备容量。这可以通过在模型中明确包括调度周期的持续时间和重新评估此决策的频率来完成。在此模型中,需求的随机性是通过使用双截断正态分布来捕获的。激活发电储备所产生的成本被建模为泊松过程。总体模型通过使用不同的储备资源来捕获价格差异。给出了一个经验示例,以说明使用本研究中提出的方法并采用两种不同策略的成本优势:静态策略和动态策略。结果表明,动态设置发电储备可以节省成本。

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