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Flexible multi-objective transmission expansion planning with adjustable risk aversion

机译:可变风险规避的灵活多目标传输扩展计划

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摘要

This paper presents a multi-objective transmission expansion planning (TEP) framework. Rather than using the conventional deterministic reliability criterion, a risk component based on the probabilistic reliability criterion is incorporated into the TEP objectives. This risk component can capture the stochastic nature of power systems, such as load and wind power output variations, component availability, and incentive-based demand response (IBDR) costs. Specifically, the formulation of risk value after risk aversion is explicitly given, and it aims to provide network planners with the flexibility to conduct risk analysis. Thus, a final expansion plan can be selected according to individual risk preferences. Moreover, the economic value of IBDR is modeled and integrated into the cost objective. In addition, a relatively new multi-objective evolutionary algorithm called the MOEA/D is introduced and employed to find Pareto optimal solutions, and tradeoffs between overall cost and risk are provided. The proposed approach is numerically verified on the Garver’s six-bus, IEEE 24-bus RTS and Polish 2383-bus systems. Case study results demonstrate that the proposed approach can effectively reduce cost and hedge risk in relation to increasing wind power integration.
机译:本文提出了一个多目标传输扩展计划(TEP)框架。代替使用常规的确定性可靠性标准,将基于概率可靠性标准的风险成分纳入TEP目标。该风险组件可以捕获电力系统的随机性,例如负载和风力发电的输出变化,组件的可用性以及基于激励的需求响应(IBDR)成本。具体而言,明确给出了规避风险后的风险价值表述,旨在为网络规划人员提供进行风险分析的灵活性。因此,可以根据个人风险偏好选择最终的扩张计划。此外,IBDR的经济价值被建模并整合到成本目标中。此外,引入了一种相对较新的称为MOEA / D的多目标进化算法,并将其用于找到Pareto最优解,并在总成本和风险之间进行权衡。 Garver的六总线,IEEE 24总线RTS和波兰2383总线系统在数字上验证了该提议的方法。案例研究结果表明,与增加风电集成度相比,该方法可以有效降低成本和对冲风险。

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