针对综合能源系统规划中源荷多重不确定性问题和容量与运行规划相互独立的问题,建立两阶段多目标随机规划模型。该模型采用随机分层场景生成方法来应对源荷多重不确定性问题,通过ε约束法和Benders分解来处理多目标优化和容量运行协同规划问题。结果表明：建立的随机分层场景生成模型能更好地表征源荷多重不确定性;规划结果的可再生能源份额可达80%,净交互水平仅为20%,费用年值为1752万元,在实现高比例可再生能源消纳和提高系统独立性的同时具有较强的供需协同能力。此外,扩大可再生能源份额将降低系统的经济性能,而降低的经济性能可通过提高净交互水平来改善。
Abstract
In response to the multiple uncertainties of source and load, as well as the independent of capacity and operation programming in integrated energy system（IES）, a two-stage multi-objective stochastic programming model is established. This model integrates the Latin Hypercube Sampling method and a scenario curtailment method based on Wasserstein distance to construct a stochastic hierarchy scenario generation model to address the multiple uncertainties of source and load. It handles multi-objective optimization and the collaborative programming of capacity and operation through the ε-constraint method and Benders decomposition. The results show that the established stochastic hierarchy scenario generation model can better characterize the multiple uncertainties of source and load; the renewable energy share（RES） in the programming results can reach 80%, with only a 20% net interaction level（NIL）, and an ATC of 17.52 million yuan. While achieving a high proportion of renewable energy consumption and enhancing system independence, it also possesses strong supply-demand collaborative capability. Moreover, increasing the RES will reduce the economic performance of the system, but the reduced economic performance can be mitigated by improving the NIL.
关键词
能源管理系统 /
随机规划 /
多目标优化 /
综合能源系统 /
Benders分解 /
协同规划
Key words
energy management systems /
stochastic programming /
multi-objective optimization /
integrated energy system /
Benders decomposition /
collaborative programming
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 韩旭, 周峻毅, 林俊军, 等. 计及弃电转热的IES系统设计及运行特性研究[J]. 太阳能学报, 2023, 44(10): 514-522.
HAN X, ZHOU J Y, LIN J J, et al.Design and operation characteristics of IES system considering power to heat[J]. Acta energiae solaris sinica, 2023, 44(10): 514-522.
[2] 韩旭, 周峻毅, 王小东, 等. 基于穷举搜索法的城市建筑CCHP系统优化配置[J]. 动力工程学报, 2023, 43(7): 923-929.
HAN X, ZHOU J Y, WANG X D, et al.Optimal configuration of urban building CCHP system based on exhaustive search method[J]. Journal of Chinese Society of Power Engineering, 2023, 43(7): 923-929.
[3] SU H, ZIO E, ZHANG J J, et al.A systematic method for the analysis of energy supply reliability in complex Integrated Energy Systems considering uncertainties of renewable energies, demands and operations[J]. Journal of cleaner production, 2020, 267: 122117.
[4] ZHANG Y C, LIU Y, SHU S W, et al.A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources[J]. Energy, 2021, 216: 119171.
[5] 周文操, 张学军, 闫来清. 一种缩小CCHP系统优化调度解空间的方法[J]. 太阳能学报, 2023, 44(11): 556-564.
ZHOU W C, ZHANG X J, YAN L Q.An optimal scheduling scheme of CCHP systems by reducing solution space[J]. Acta energiae solaris sinica, 2023, 44(11): 556-564.
[6] YAN R J, LU Z R, WANG J J, et al.Stochastic multi-scenario optimization for a hybrid combined cooling, heating and power system considering multi-criteria[J]. Energy conversion and management, 2021, 233: 113911.
[7] 赵振宇, 解冰清. 计及风光互补特性的风光容量优化配置模型[J]. 太阳能学报, 2023, 44(8): 149-156.
ZHAO Z Y, XIE B Q.Optimal allocation model of wind-solar capacity considering wind-solar complementary characteristics[J]. Acta energiae solaris sinica, 2023, 44(8): 149-156.
[8] RAHMANIANI R, CRAINIC T G, GENDREAU M, et al.The Benders decomposition algorithm: a literature review[J]. European journal of operational research, 2017, 259(3): 801-817.
[9] ABDOLMOHAMMADI H R, KAZEMI A.A Benders decomposition approach for a combined heat and power economic dispatch[J]. Energy conversion and management, 2013, 71: 21-31.
[10] PAN C Q, WANG C, ZHAO Z Y, et al.A copula function based Monte Carlo simulation method of multivariate wind speed and PV power spatio-temporal series[J]. Energy procedia, 2019, 159: 213-218.
[11] LI Y, WANG C L, LI G Q, et al.Optimal scheduling of integrated demand response-enabled integrated energy systems with uncertain renewable generations: a Stackelberg game approach[J]. Energy conversion and management, 2021, 235: 113996.
[12] ZHOU Y Z, WEI Z N, SUN G Q, et al.A robust optimization approach for integrated community energy system in energy and ancillary service markets[J]. Energy, 2018, 148: 1-15.
[13] 董骁翀, 孙英云, 蒲天骄, 等. 一种基于Wasserstein距离及有效性指标的最优场景约简方法[J]. 中国电机工程学报, 2019, 39(16): 4650-4658.
DONG Y Y, SUN Y Y, PU T J, et al.An optimal scenario reduction method based on Wasserstein distance and validity index[J]. Proceedings of the CSEE, 2019, 39(16): 4650-4658.
[14] ABARESHI M, ZAFERANIEH M.A bi-level capacitated P-median facility location problem with the most likely allocation solution[J]. Transportation research part B: methodological, 2019, 123: 1-20.
[15] WANG Y L, HUANG F F, TAO S Y, et al.Multi-objective planning of regional integrated energy system aiming at exergy efficiency and economy[J]. Applied energy, 2022, 306: 118120.
基金
国家自然科学基金（52177084）; 河北省自然科学基金（E2022502017; E2023502040）
PDF(1635 KB)
