Fuzzy theory-based best generation mix considering renewable energy generators

Jeongje Park, Liang-Qi Wu, Jaeseok Choi, J. Cha, A. El-Keib, J. Watada
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引用次数: 5

Abstract

This paper proposes a fuzzy linear programming (LP)-based solution approach for the long-term multi-stages best generation mix (BGM) problem considering wind turbine generators (WTG) and solar cell generators (SCG), and CO2 emissions constraints. The proposed method uses fuzzy set theory to consider the uncertain circumstances ambiguities associated with budgets and reliability criterion level. The proposed approach provides a more flexible solution compared to a crisp robust plan. The effectiveness of the proposed approach is demonstrated by applying it to solve the multi-years best generation mix problem on the Korean power system, which contains nuclear, coal, LNG, oil, pumped-storage hydro, and WTGs and SCGs.
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基于模糊理论的可再生能源发电机组最佳发电组合
针对考虑风力发电机组(WTG)和太阳能电池发电机组(SCG)以及二氧化碳排放约束的长期多阶段最佳发电组合问题,提出了一种基于模糊线性规划(LP)的求解方法。该方法利用模糊集理论来考虑与预算和可靠性准则水平相关的不确定情况的模糊性。与清晰的健壮计划相比,所建议的方法提供了更灵活的解决方案。通过将所提出的方法应用于解决韩国电力系统的多年最佳发电组合问题,证明了该方法的有效性,该系统包含核能,煤炭,液化天然气,石油,抽水蓄能水电以及wtg和SCGs。
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