Flexibilizing Distribution Network Systems via Dynamic Reconfiguration to Support Large-Scale Integration of Variable Energy Sources Using a Genetic Algorithm
In recent years, the level of variable Renewable Energy Sources (vRESs) integrated in power systems has been increasing steadily. This is driven by a multitude of global and local concerns related to energy security and dependence, climate change, etc. The integration of such energy sources is expected to continue growing in the coming years. Despite their multifaceted benefits, variable energy sources introduce technical challenges mainly because of their intermittent nature, particularly at distribution levels. The flexibility of existing distribution systems should be significantly enhanced to partially reduce the side effects of vRESs. One way to do this is using a dynamic network reconfiguration. Framed in this context, this work presents an optimization problem to investigate the impacts of grid reconfiguration on the level of integration and utilization of vRES power in the system. The developed combinatorial model is solved using a genetic algorithm. A standard IEEE 33-node distribution system is employed in the analysis. Simulation results show the capability of network switching in supporting large-scale integration of vRESs in the system while alleviating their side effects. Moreover, the simultaneous consideration of vRES integration and network reconfiguration lead to a better voltage profile, reduced costs and losses in the system.
KeywordsDistributed generation Network reconfiguration RESs Genetic algorithm Variable energy resources
This work was supported by FEDER funds through COMPETE 2020 and by Portuguese funds through FCT, under Projects SAICT-PAC/0004/2015 - POCI-01-0145-FEDER-016434, POCI-01-0145-FEDER-006961, UID/EEA/50014/2013, UID/CEC/50021/2013, and UID/EMS/00151/2013. The research leading to these results has received funding from the EU Seventh Framework Programme FP7/2007-2013 under grant agreement no. 309048.
- 13.Ma, Y., Tong, X., Zhou, X., Gao, Z.: The review of smart distribution grid. In: 2016 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 154–158 (2016)Google Scholar
- 14.Zhou, X., Cui, H., Ma, Y., Gao, Z.: Research review on smart distribution grid. In: 2016 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 575–580 (2016)Google Scholar
- 15.Hayfa, S., Omar, K., Hsan, H.A.: Optimal power distribution system reconfiguration using genetic algorithm. Presented at the 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, Monastir, Tunisia (2015)Google Scholar
- 16.Cruz, M.R.M.: Benefits of coordinating distribution network reconfiguration with distributed generation and energy storage systems. Universidade do Porto (2016)Google Scholar
- 17.Cruz, M.R.M., Fitiwi, D.Z., Santos, S.F., Catalão, J.P.S.: Influence of distributed storage systems and network switching/reinforcement on RES-based DG integration level. Presented at the 2016 13th International Conference on the European Energy Market (EEM), OPorto (2016)Google Scholar