An Intelligent Web-based Energy Management System for Distributed Energy Resources Integration and Optimization
DOI:
https://doi.org/10.13052/jwe1540-9589.2316Keywords:
Energy management systems, web engineering, generative AI, active distribution networks, soft open points, dynamic scenario generationAbstract
The integration of renewable energy sources into power distribution systems frequently presents challenges for conventional energy management systems (EMS) due to the unpredictable and unstable characteristics of such energy sources. As a result, novel and cutting-edge solutions are required. This paper presents an intelligent web-based energy management system (iW-EMS) specifically designed to address the integration and optimization of distributed energy resources, as outlined in the proposed approach. The system incorporates a hybrid novel optimization approach that integrates simulated annealing and cone programming to effectively manage the distribution of energy resources and attain optimal outcomes from the proposed EMS. Additionally, it leverages generative AI services to create optimal scenarios based on historical data and real-time information, ensuring adaptability to the dynamic nature of renewable energy generation, providing a user-friendly and flexible web environment for scenario planning. The proposed framework facilitates seamless communication and collaboration among stakeholders involved in renewable energy integration, while also enabling the incorporation of real-world data sources such as weather forecasts and energy consumption patterns into the planning process.
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References
W. Chengshan and L. Peng, “Development and challenges of distributed generation, the micro-grid and smart distribution system[J],” Autom. Electr. Power Syst., vol. 34, no. 2, pp. 10–14, 23, 2010.
S. Conti, R. Nicolosi, and R. S. A, “Optimal dispatching of distributed generators and storage systems for MV islanded microgrids[J],” IEEE Trans. Power Deliv., vol. 27, no. 3, pp. 1243–1251, 2012.
A. Rueda-Medina and A. Padilha-Feltrin, “Distributed generators as providers of reactive power support-a market approach[J],” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 490–502, 2013.
H. Shaojun, W. Qiuwei, and O. S, “Distribution locational marginal pricing through quadratic programming for congestion management in distribution networks[J],” IEEE Trans. Power Syst., vol. 30, no. 4, pp. 2119–2128, 2015.
R. Verzijlbergh, L. De-Vries, and Z. Lukszo, “Renewable energy sources and responsive demand. Do we need congestion management in the distribution grid[J]?,” IEEE Trans. Power Syst., vol. 29, no. 5, pp. 2170–2178, 2014.
J. Bloemink and T. Green, Increasing distributed generation penetration using soft normally-open points[C]// 2010 IEEE Power and Energy Society General Meeting. Minneapolis, MN: IEEE, 2010.
C. Wanyu, W. Jianzhong, and N. J, “Operating principle of soft open points for electrical distribution network operation[J],” Appl. Energy, vol. 164, pp. 245–257, 2016.
C. Wanyu, W. Jianzhong, and N. J, “Benefits analysis of soft open points for electrical distribution network operation[J],” Appl. Energy, vol. 165, pp. 36–37, 2016.
W. Qun, D. Wenlue, and Y. Li, “A wind power/photovoltaic typical scenario set generation algorithm based on the Wasserstein distance metric and revised K-medoids cluster[J],” Proc. CSEE, vol. 35, no. 11, pp. 2654–2661, 2015.
D. Lei, T. Aizhong, and Y. Ting, “Reactive power optimization for distribution network with distributed generators based on mixed integer semi-definite programming[J],” Autom. Electr. Power Syst., vol. 39, no. 21, pp. 66–72, 2015.
X. Xiaoyuan, W. Han, and Y. Zheng, “Overview of power system uncertainty and its solutions under energy transition[J],” Autom. Electr. Power Syst., vol. 45, no. 16, pp. 2–13, 2021.
Y. X. Hao, Q. Long, S. F. Qiao, L. P. Xia, and X. Y. Wang, “Coordinated Control and Characteristics of an Integrated Hydraulic-Electric Hybrid Linear Drive System,” IEEE-Asme T Mech, vol. 27, pp. 1138–1149, 2022, doi: 10.1109/Tmech.2021.3082547.
W. Shouxiang, L. Qi, and Z. Qianyu, “Improved particle swarm optimization algorithm for multi-objective voltage optimization of AC/DC distribution network considering the randomness of source and loads[J],” Proc. CSUEPSA, vol. 33, no. 12, pp. 10–17, 2021.
W. Wenchuan, Z. Boming, and S. Hongbin, “Energy management and distributed energy resources cluster control for active distribution networks[J],” Autom. Electr. Power Syst., vol. 44, no. 9, pp. 111–118, 2020.
L. L. Y. and C. C. C, “Consensus-based secondary frequency and voltage droop control of virtual synchronous generators for isolated AC micro-grids[J],” IEEE J. Emerg. Sel. Top. Circuits Syst., vol. 5, no. 3, pp. 443–455, 2015.
P. Sulc, S. Backhaus, and M. Chertkov, “Optimal distributed control of reactive power via the alternating direction method of multipliers[J],” IEEE Trans. Energy Convers., vol. 29, no. 4, pp. 968–977, 2014.
Z. Niancheng, L. Jianquan, and W. Qianggang, “Analysis and prospect of deep learning application in smart grid[J],” Autom. Electr. Power Syst., vol. 43, no. 4, pp. 180–191, 2019.
Y. Ting, Z. Liyuan, and W. Chengshan, “Review on application of artificial intelligence in power system and integrated energy system[J],” Autom. Electr. Power Syst., vol. 43, no. 1, pp. 2–14, 2019.
K. S. H., C. R. B., and R. R, “Probabilistic performance assessment of autonomous solar-wind energy conversion systems[J],” IEEE Trans. Energy Convers., vol. 14, no. 3, pp. 766–772, 1999.
L. Xian, “Economic load dispatch constrained by wind power availability: a wait-and-see approach[J],” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 347–355, 2010.
L. Jinghua, W. Hua, and M. Dong, “Asymptotically optimal scenario analysis and wait-and-see model for optimal power flow with wind power[J],” Proc. CSEE, vol. 32, no. 22, pp. 15–23, 2012.
W. Chengshan, S. Chongbo, and L. Peng, “SNOP-based operation optimization and analysis of distribution networks[J],” Autom. Electr. Power Syst., vol. 39, no. 9, pp. 82–87, 2015.
W. Chengshan, P. Ke, and S. Xujiang, “Universal modeling method of power electronics controller for distributed generation system[J],” Autom. Electr. Power Syst., vol. 36, no. 18, pp. 122–127, 2012.

