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arXiv 1902.07779math.OC
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满足灵活性需求的基于功率的发电扩展规划

Power-Based Generation Expansion Planning for Flexibility Requirements

Diego A. Tejada-Arango, Germán Morales-España, Sonja Wogrin, Efraim Centeno

摘要:

由于可变可再生能源(vRES)的集成,电力系统规划中的灵活性要求变得更加相关。为了考虑这些要求,发电扩展规划(GEP)模型最近纳入了机组组合(UC)的限制,使用传统的能源为基础的配方。然而,最近的研究表明,基于能量的UC公式高估了系统的实际灵活性。相反,基于功率的UC模型通过正确建模斜坡约束和操作储备来克服这些问题。本文提出了一种基于功耗的GEP-UC模型,改进了现有的模型。该模型优化了vRES、储能系统(ESS)和热技术的投资决策。此外,它还包括实时灵活性要求、ESS提供的灵活性以及其他UC约束,例如,最小上/下时间、启动和关闭功率轨迹、网络约束。结果表明,基于功率的模型比基于能量的模型更有效地使用安装投资,因为它更准确地代表了灵活性能力和系统需求。例如,基于功率的模型获得更少的投资(6 - 12%),但它更有效地利用了这一投资,因为在实时验证中运营成本也更低(2 - 8%)。我们还提出了一个半放松的基于功率的GEP-UC模型,这是至少10倍的速度比其完整的整数版本,而不会显着失去结果的准确性(小于0.2%的误差)。

英文摘要:

Flexibility requirements are becoming more relevant in power system planning due to the integration of variable Renewable Energy Sources (vRES). In order to consider these requirements Generation Expansion Planning (GEP) models have recently incorporated Unit Commitment (UC) constraints, using traditional energy-based formulations. However, recent studies have shown that energy-based UC formulations overestimate the actual flexibility of the system. Instead, power-based UC models overcome these problems by correctly modeling ramping constraints and operating reserves. This paper proposes a power-based GEP-UC model that improves the existing models. The proposed model optimizes investment decisions on vRES, Energy Storage Systems (ESS), and thermal technologies. In addition, it includes real-time flexibility requirements, and the flexibility provided by ESS, as well as other UC constraints, e.g., minimum up/down times, startup and shutdown power trajectories, network constraints. The results show that power-based model uses the installed investments more effectively than the energy-based models because it more accurately represents flexibility capabilities and system requirements. For instance, the power-based model obtains less investment (6-12%) and yet it uses more efficiently this investment because operating cost is also lower (2-8%) in a real-time validation. We also propose a semi-relaxed power-based GEP-UC model, which is at least 10 times faster than its full-integer version and without significantly losing accuracy in the results (less than 0.2% error).

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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