Optimizing hierarchical power distribution of multiple local energy network systems in grid-connected mode

• Autorzy: Fuxing Z. , Tao Z. , Rui W.
• Języki publikacji: EN

Abstrakty

EN

This paper focuses on the hierarchical power distribution optimization of multiple local energy network (LEN) systems that are formed in three levels and can be operated in six typical modes. The decentralized optimal model for each LEN (the first level) and LENs (the second level) as well as the concentrated optimal model for the top level of the system are built, respectively. For each LEN, all the basic unities such as power generated by wind turbines and photovoltaic, and their upper nodes are considered. For LENs, the aggregated results (e.g., supply-demand requirements) from each LEN are dispatched. Furthermore, in the concentrated optimal control model (the third level), the ultimate supply-demand requirements of networked LENs together with other resources such as electric vehicles are considered. Due to the large number of control resources, the whole system is formulated as a large-scale global optimization (LSGO) problem. The self-adaptive differential evolution with neighborhood search method (SaNSDE) modified with the Lagrange multiplier method is used to solve the problem. The algorithm is firstly examined on 10 constrained benchmark functions, then it is applied to our problem. Experimental results show that the proposed model and algorithm are effective and efficient.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2017
• Tom: 26
• Numer: 5
• Opis fizyczny: p.1981-2000,fig.,ref.

Twórcy

autor

Fuxing Z.

• College of Information Systems and Management, National University of Defense Technology, Changsha, P.R. China, 410073

autor

Tao Z.

• College of Information Systems and Management, National University of Defense Technology, Changsha, P.R. China, 410073
• State Key Laboratory of High-Performance Computing, National University of Defense Technology, Changsha, P.R. China, 410073

autor

Rui W.

• College of Information Systems and Management, National University of Defense Technology, Changsha, P.R. China, 410073

Bibliografia

• 1. FANG X., YANG Q., WANG J., YAN W. Coordinated dispatch in multiple cooperative autonomous islanded microgrids. Applied Energy. 162, 40, 2016.
• 2. LI, W., ZHANG, H. Decomposition Analysis of Energy Efficiency in China’s Beijing-Tianjin-Hebei Region. Polish Journal of Environmental Studies. 26 (1), 189, 2017.
• 3. JENDRUS, R. Environmental Protection in Industrial Areas and Applying Thermal Analysis to Coal Dumps. Polish Journal of Environmental Studies. 26 (1), 137, 2017.
• 4. ZHANG Y., LIU B., ZHANG T., GUO B. An Intelligent Control Strategy of Battery Energy Storage System for Microgrid Energy Management under Forecast Uncertainties. Int. J. Electrochem. 9, 4190, 2014.
• 5. WANG Z., CHEN B., WANG J., BEGOVIC M.M., CHEN C. Coordinated Energy Management of Networked Microgrids in Distribution Sysrems. IEEE TRANSACTIONS ON SMART GRID. 6 (1), 45, 2015.
• 6. WANG Z., CHEN B., WANG J., CHEN C. Networked Microgrids for self-Healing Power Systems. IEEE TRANSACTIONS ON SMART GRID. 7 (1), 310, 2016.
• 7. BUI V.H., HUSSAIN A., KIM H.M. A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response. IEEE TRANSACTIONS ON SMART GRID. DOI 10.1109/TSG.2016.2585671, 2016.
• 8. XU Y., ZHANG W., HUG G., KAR S., LI Z. Cooperative Control of Distributed Energy Storage Systems in a Microgrid. IEEE TRANSACTIONS ON SMART GRID. 6 (1), 238, 2015.
• 9. LI Q., PENG C., CHEN M., CHEN F., KANG W., GUERRERO J.M., ABBOTT D. Networked and Distributed Control Method with Optimal Power Dispatch for Islanded Microgrids. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS. DOI 10.1109/TIE.2016.2598799, 2016.
• 10. CHEN F., CHEN M., LI Q., MENG K., GUERRERO J.M., ABBOTT D. Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY. 7 (3), 1232, 2016.
• 11. MALYSZ P., SIROUSPOUR S., EMADI A. An Optimal Energy Storage Control Strategy for Grid-connected Microgrids. IEEE TRANSACTIONS ON SMART GRID. 5 (4), 1785, 2014.
• 12. WANG Z., CHEN B., WANG J., KIM J. Decentralized Energy Management System for Networked Microgrids in Grid-Connected and Islanded Modes. IEEE TRANSACTIONS ON SMART GRID. 7 (2),1097, 2016.
• 13. YU X., XU X., CHEN S., WU J., JIA H. A Brief Review to Integrated Energy System and Energy Internet. TRANSACTIONS OF CHINA ELECTROTECHNICAL SOCIETY. 31 (1), 1, 2016.
• 14. ZHANG T., ZHANG F., ZHANG Y. Study on Energy Management System of Energy Internet. Power System Technology. 40 (1),146, 2016.
• 15. ZENG M., YANG Y., LIU D., ZENG B., OUYANG S., LING H., HAN X.“Generation-Grid-Load-Storage” Coordinative Optimal Operation Mode of Energy Internet and Key Technologies. Power System Technology. 40 (1), 114, 2016.
• 16. DOU C., WANG W., HAO D., LI X. MAS-based solution to energy management strategy of distributed generation system. Electrical Power and Energy Systems. 69, 354, 2015.
• 17. REYASUDIN BASIR KHAN M., JIDIN R., PASUPULETI J.. Multi-agent based distributed control architecture for microgrid energy management and optimization. Energy Conversion and Management. 112, 288, 2016.
• 18. WANG Y., MAO S., NELMS R.M. On Hierarchical Power Scheduling for the Macrogrid and Cooperative Microgrids. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS. 11 (6), 1574, 2015.
• 19. YANG F., LIU S., WANG H., FANG Y., LI W., ZHENG W. A Decomposition Method to Calculate Available Transfer Capability of Large Interconnected Power Grid. Power System Technology. 38 (1), 138, 2014.
• 20. MA W.J., WANG J., GUPTA V., CHEN C. Distributed Energy Management for Networked Microgrids Using Online ADMM with Regret. IEEE TRANSACTIONS ON SMART GRID. DOI 10.1109/TSG.2016.2569604, 2016.
• 21. SUN Q., TENG F., ZHANG H., MA D. Construction of Dynamic Coordinated Optimization Control System for Energy Internet. Proceedings of the CSEE. 35 (14), 3667, 2015.
• 22. MINCIARDI R., SACILE R. Optimal Control in a Cooperative Network of Smart Power Grids. IEEE SYSTEMS JOURNAL. 6 (1),126,2012.
• 23. HAMIDI R.J., LIVANI H., HOSSEINIAN S.H., Gharehpetian G.B. Distributed cooperative control system for smart microgrids. Electric Power Systems Research. 130, 241, 2016.
• 24. SHEN X., CAO M., ZHOU N., ZHANG L. Research on coordinated optimal scheduling and economic operation of multi-microgrid distribution system. JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENTATION. 30 (4), 568, 2016.
• 25. MALIK F.H., LEHTONEN M. A review:Agents in smart grids. Electric Power Systems Research. 131, 71, 2016.
• 26. LI X., YAO X. Cooperatively Coevolving Particle Swarms for Large Scale Optimization. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION. 16 (2), 210, 2012.
• 27. MAHDAVI S., SHIRI M.E., RAHNAMAYAN S. Metaheuristics in large-scale global continues optimization: A survey. Information Sciences. 295, 407, 2015.
• 28. YANG Z., TANG K., YAO X. Large scale evolutionary optimization using cooperative co-evolution. Information Sciences. 178, 2985, 2008.
• 29. YANG Z., TANG K., YAO X. Multilevel cooperative co-evolution for large scale optimization. 2008 IEEE Congress on Evolutionary Computation (CEC). 1663, 2008.
• 30. OMIDVAR M., LI X., YAO X. Cooperative co-evolution with Delta grouping for large scale non-separable function optimization. 2010 IEEE Congress on Evolutionary Computation (CEC). 1762, 2010.
• 31. OMIDVAR M., LI X., MEI Y., YAO X. Cooperative co-evolution with differential grouping for large scale optimization. IEEE Transactions on Evolutionary Computation. 18 (3), 378, 2014.
• 32. SUN Y., KIRLEY M., HALGAMUGE S. K. Extended Differential Grouping for Large Scale Global Optimization with Direct and Indirect Variable Interactions. 2015 Genetic and Evolutionary Computation Conference (GECCO). 313, 2015.
• 33. YU Y., YU X., LI Y. Solving Engineering Optimization Problem by Augmented Lagrange Particle Swarm Optimization. JOURNAL OF MECHANICAL ENGINEERING. 45 (12), 167, 2009.
• 34. YANG Z., TANG K., YAO X. Self-adaptive differential evolution with neighborhood search. 2008 IEEE Congress on Evolutionary Computation (CEC). 1110, 2008.
• 35. WANG Y., CAI Z., ZHOU Y., FAN Z. Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique. Struct Multidisc Optim. 37, 395, 2009.
• 36. LIU D., GUO J., HUANG Y., WANG W. Dynamic Economic Dispatch of Wind Integrated Power System Based on Wind Power Probabilistic Forecasting and Operation Risk Constraints. Proceedings of the CESS. 33 (16), 9, 2013.
• 37. HONG T., PINSON P., FAN S., ZAREIPOUR H., TROCCOLI A., Hyndman R.J. Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond. International Journal of Forecasting. 32, 896, 2016.
• 38. PRAGASPATHY, S., BASKARAN, A. Mitigation of Uncertainties in Wind-Powered Renewable Systems for Environmental Assets. Polish Journal of Environmental Studies. 26 (1), 253, 2017.
• 39. XIONG C., YANG D., HUO J., ZHAO Y. The Relationship between Agricultural Carbon Emissions and Agricultural Economic Growth and Policy Recommendations of a Low-carbon Agriculture Economy. Polish Journal of Environmental Studies. 25 (5), 2187, 2016.

Identyfikatory

DOI

10.15244/pjoes/69440