Penetration of Distributed Renewable Energy in active distribution network has increased year by year, and the distributed characteristics of active distribution network has become increasingly prominent; it is difficult for traditional centralized energy scheduling to solve the coordination of random output of distributed energy and the communication pressure of a large number of distributed data. In this paper, we propose a Distributed Renewable Energy Coordination Strategy based on price guidance, through hierarchical multi-agent model. The coordination model of each agent is introduced in detail, regional target, price coordination response strategy and regional security constraints, using Agent’s Distributed Autonomy and Global Collaboration to realize the Energy Balance of Active Distribution Network and promote the Storage of Distributed Renewable Energy; the coordination strategy focuses on the impact of price adjustment on energy storage and flexible load response capacity to improve the distributed renewable energy consumption. Finally, through the quantitative analysis of the comprehensive performance of the index, the evaluation results of the traditional sequential simulation method are compared, and the rationality and validity of the proposed method are verified.
References
[1]
Prostejovsky, A., Merdan, M. and Schitter, G. (2013) Demonstration of a Mul-ti-Agent-Based Control System for Active Electric Power Distribution Grids. IEEE Inter-national Workshop on Intelligent Energy Systems, 14 November 2013.
[2]
Shi, T., Zhang, B., Chao, Q., et al. (2016) Economic Storage Ratio and Optimal Control of Hybrid Energy Capacity Combining Stabilized Wind Power Fluctuations with Compen-sated Predictive errors. Power System Technology, 40, 477-483.
[3]
Atwa, Y.M. and El-Saadany, E.F. (2000) Optimal Allocation of ESS in Distribution Sys-tems with a High Penetration of Wind Energy. IEEE Transaction on Power System, 25, 1815-1822. https://doi.org/10.1109/TPWRS.2010.2045663
[4]
Yan, G., Liu, J., Cui, Y., et al. (2013) Economic Evaluation of Improving the Wind Power Scheduling Scale by Energy Storage System. Proceedings of the CSEE, 33, 45-52.
[5]
Logenthiran, T., Srinivasan, D., Khambadkone, A.M., et al. (2012) Multi Agent System for Real-Time Operation of Amicrogrid in Real-Time Digital Simulator. IEEE Trans Smart Grid, 3, 925-933. https://doi.org/10.1109/TSG.2012.2189028
[6]
Li, J., Song, X. and Meng, X. (2015) Hierarchical Control Model of Smart Distribution Network Based on Self-Organizing Multi-Agent System. In: International Conference on Renewable Power Generation, North China Electric Power University Press, Beijing, 1-6.
[7]
Bellifemine, F., Poggi, A. and Rimassa, G. (1999) JADE—A FIPA-Compliant Agent Framework. C Selt Internal, 31, 103-128.
[8]
Dimeas, A.L. and Hatziargyriou, N.D. (2005) Operation of a Multi Agent System for Mi Crogrid Control. IEEE Transactions on Power Systems, 20, 1447-1455.
https://doi.org/10.1109/TPWRS.2005.852060
[9]
Jiang, R., Qiu, X. and Li, D. (2014) Multi-Agent System Based Dynamic Game Model of Smart Distribution Network Containing Multi-Microgrid. Power System Technology, 38, 3321-3327.
[10]
Hao, Y., Wu, Z., Dou, X., et al. (2012) Application of Multi-Agent Systems to the DC Microgrid Stability Control. Proceedings of the CSEE, 32, 27-35.
[11]
Yuan, T., Chen, J., Liu, P., et al. (2014) Strategy of Improving Large-Scale Wind Farm Output Fluctuation Based on Energy Storage System. Power System Protection and Con-trol, 42, 47-53.
[12]
Yu, N., Yu, L. and Li, G. (2015) Controllable Load Management Strategy for Commercial Users Based on Multi-Agent in Smart Grid Environment. Automation of Electric Power Systems, 39, 89-95.
[13]
Pu, T., Liu, K., Li, Y., et al. (2015) Multi-Agent System Based Simulation Verification for Autonomy-Cooperative Optimization Control on Active Distribution Network. Proceedings of the CSEE, 35, 1864-1874.
[14]
Lan, J., Xu, Y., Huo, L., et al. (2006) Research on the Priorities of Fuzzy Analytical Hierarchy Process. Systems Engineering-Theory & Practice, No. 9, 107-112.
[15]
Chen, F., Liu, D. and Chen, Y. (2015) Hierarchically Distributed Voltage Control Strategy for Active Distribution Network. Automation of Electric Power Systems, 39, 61-67.
[16]
Wang, C., Sun, W., Yi, T., et al. (2013) Review on Energy Storage Application Planning and Benefit Evaluation Methods in Smart Grid. Proceedings of the CSEE, 33, 33-41.
