Cooperative Planning of Active Distribution System With Renewable Energy Sources and Energy Storage Systems

In this paper, a multi-objective, multi-level model is proposed for active distribution system expansion planning with high-penetration renewable energy sources (RESs) and energy storage systems (ESSs). To optimize the planning of RESs, ESSs, and distribution networks cooperatively, a three-level optimization method is adopted based on the leader–follower strategy of hierarchic optimizations. In this model, the upper level and the middle-level serve to model the planning problems from different perspectives of multi-stakeholders; the lower level serves to model the operation aspect of ESSs. The multi-level model enables us to integrate operation optimization into a planning model and achieve the collaborative optimization of them in different time-scales. The multi-scenario tools and K-means clustering are adopted to deal with the uncertainties and capture the time-variable nature of RESs and load demand. In order to balance the multiple objectives of costs reduction, reliability improvement, and RES penetration promotion, a modified Pareto-based particle swarm optimization is employed to solve the proposed optimization problem. Finally, results obtained by case studies are presented and discussed, where the availability and the effectiveness of the proposed planning model are verified.

[1]  Mahmoud-Reza Haghifam,et al.  Distribution network expansion considering distributed generation and storage units using modified PSO algorithm , 2013 .

[2]  Y. M. Atwa,et al.  Optimal Allocation of ESS in Distribution Systems With a High Penetration of Wind Energy , 2010, IEEE Transactions on Power Systems.

[3]  Zhe Chen,et al.  A Simple Adaptive Overcurrent Protection of Distribution Systems With Distributed Generation , 2011, IEEE Transactions on Smart Grid.

[4]  Kashem M. Muttaqi,et al.  Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm , 2014 .

[5]  Ali Ahmadian,et al.  Optimal Storage Planning in Active Distribution Network Considering Uncertainty of Wind Power Distributed Generation , 2016, IEEE Transactions on Power Systems.

[6]  Sanna Syri,et al.  Electrical energy storage systems: A comparative life cycle cost analysis , 2015 .

[7]  Carmen L. T. Borges,et al.  Multistage expansion planning for active distribution networks under demand and Distributed Generation uncertainties , 2012 .

[8]  R. Billinton,et al.  Predicting bulk electricity system reliability performance indices using sequential Monte Carlo simulation , 2006, IEEE Transactions on Power Delivery.

[9]  Vahid Vahidinasab,et al.  An aggregated model for coordinated planning and reconfiguration of electric distribution networks , 2016 .

[10]  Donald W. Bouldin,et al.  A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Vahid Abbasi,et al.  Multistage distribution network expansion planning considering the emerging energy storage systems , 2015 .

[12]  Behnam Mohammadi-Ivatloo,et al.  Dynamic planning of distributed generation units in active distribution network , 2015 .

[13]  M.M.A. Salama,et al.  An integrated distributed generation optimization model for distribution system planning , 2005, IEEE Transactions on Power Systems.

[14]  Vinod Khadkikar,et al.  Planning active distribution networks considering multi-DG configurations , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[15]  Loutfi Nuaymi,et al.  Integrating Cellular Networks, Smart Grid, and Renewable Energy: Analysis, Architecture, and Challenges , 2015, IEEE Access.

[16]  Vahid Vahidinasab,et al.  SoS-based multiobjective distribution system expansion planning , 2016 .

[17]  Ricardo H. C. Takahashi,et al.  Multiobjective planning of power distribution networks with facility location for distributed generation , 2016 .

[18]  H. A. Hejazi,et al.  Independent distributed generation planning to profit both utility and DG investors , 2013, IEEE Transactions on Power Systems.

[19]  Wei Wang,et al.  An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow , 2015 .

[20]  Carmen L. T. Borges,et al.  Optimal distributed generation allocation for reliability, losses, and voltage improvement , 2006 .

[21]  Birgitte Bak-Jensen,et al.  Planning and optimization methods for active distribution systems , 2014 .

[22]  Sayyad Nojavan,et al.  Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation , 2016 .

[23]  Jianhua Zhang,et al.  A multi-level approach to active distribution system planning for efficient renewable energy harvesting in a deregulated environment , 2016 .

[24]  Haozhong Cheng,et al.  Active distribution network expansion planning integrating dispersed energy storage systems , 2016 .

[25]  Johanna M. A. Myrzik,et al.  Integration Issues of Distributed Generation in Distribution Grids , 2011, Proceedings of the IEEE.

[26]  Emilio Ghiani,et al.  New electricity distribution network planning approaches for integrating renewable , 2013 .

[27]  Jeng Shiun Lim,et al.  Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods , 2017 .

[28]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..