Evaluating efficiency of renewable energy sources in planning micro-grids considering uncertainties

Abstract

Nowadays, the renewable energy sources (RES) are widely utilized in micro-grids due to technical development and emission increase, which make the planning the micro-grids integrated the RES very important. To obtain the optimal planning strategy and evaluating efficiency of the RES in micro-grids, a mixed integer programming (MIP) planning framework for a grid-connected micro-grid is presented in this study. The understudy micro-grid consists of the wind turbines and photo-voltaic systems, which are connected to utility grid through the point of common coupling (PCC). The objective function is minimizing the life cycle cost of object comprising of the investment and operation cost of the RES, the energy purchased cost from the utility grid, the emission taxes cost and the replacement cost or residual value of equipment at the end of the planning period. The uncertainties of load, electrical price, wind speed and solar radiation are taken into consideration and then a combinable model with the clustering technique is utilized to integrate them. Finally, numerical simulations for a test grid-connected micro-grid are made to validate the effectiveness of the proposed model and show efficiency of the RES to can apply to practical micro-grids.

Keywords

• Emission,Life cycle cost,Micro-grid planning,Renewable energy sources,Uncertainties

References

1. Prieto-Araujo, E, Olivella-Rosel, P, Cheah-Mañe, M, Villafafila-Robles, R, Gomis-Bellmunt, O. Renewable energy emulation concepts for microgrids. Renewable and Sustainable Energy Reviews 2015; 50: 325-345.
2. Kaur, S, Kaur, T. A Review of Microgrid Concept. International Journal of Advanced Research in Science, Engineering and Technology 2016; 3: 1513-1520.
3. Chen, D, Xu, L. AC and DC Microgrid with Distributed Energy Resources. In: Veneri, Ottorino. Technologies and Applications for Smart Charging of Electric and Plug-in Hybrid Vehicles. Cham, Switzerland: Springer International Publishing Switzerland, 2017. pp. 39-64.
4. Ahmed, M, Amin, U, Aftab, S, Ahmed, Z. Integration of Renewable Energy Resources in Microgrid. Energy and Power Engineering 2015; 7: 12-29.
5. Theo, WL, Limb, JS, Ho, WS, Hashim, H, Lee, CT. Review of distributed generation system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods. Renewable and Sustainable Energy Reviews 2017; 67: 531-573.
6. Sambaiah, KS. A Review on Optimal Allocation and Sizing Techniques for DG in Distribution Systems. International Journal of Renewable Energy Research 2018; 8: 1236-1256.
7. Singh, B, Sharma, J. A review on distributed generation planning, Renewable and Sustainable Energy Reviews 2017; 76: 529-544.
8. IRENA, International Renewable Energy Agency, Renewable Power Generation Costs 2017, Abu Dhabi, UAE, 2017.

9. Kapoor, P, Singh, MKR, Shashikant. A Review on Distributed Generation Definitions and DG Impacts on Distribution System. International Journal of Innovative Science and Modern Engineering 2017; 4: 1-6.
10. Latreche, Y, Bouchekara, HREH, Kerrour, F, Naidu, K, Mokhlis, H, Javaid, MS. Comprehensive review on the optimal integration of distributed generation in distribution systems. Journal of Renewable and Sustainable Energy 2018; 10: 1-33.
11. Mumtaz and Bayram, IS. Planning, Operation, and Protection of Microgrids: An Overview. Energy Procedia 2017; 107: 94-100.
12. Gamarraa, C. and Guerrero, JM. Computational optimization techniques applied to microgrids planning: a review. Renewable & Sustainable Energy Reviews 2015; 48: 413-424.
13. Jing, Z, Zhu, J, Hu, R. Sizing optimization for island microgrid with pumped storage system considering demand response. J. Mod. Power Syst. Clean Energy 2018; 6: 791-801.
14. Wang, Z, Chen, Y., Mei, S, Huang, S, Xu, Y. Optimal expansion planning of isolated microgrid with renewable energy resources and controllable loads. IET Renew. Power Gener. 2017; 11: 931-940.
15. Lotfi, H, Khodaei, A. Co-Optimization Generation and Distribution Planning in Microgrids. In: IEEE International Conference on Smart Grid Communications; 23-26 October 2017: Germany, pp .1-6.
16. Hernández, ACL, Aldana, NLD, Andrade, F, Graells, M, Guerrero, JM, Vasquez, JC. Economic Power Dispatch of Distributed Generators in a Grid-Connected Microgrid. In: ICPE-ECCE Asia. The 9th International Conference on Power Electronics and ECCE Asia; 1-5 June 2015: South Korea, pp. 1161-1168.
17. Ahamdi, SP, Lordejani, SN ,Rahimi-Kian, A, Milasi, AM, Vahdati, PM. Uncertainty based configuration design and optimal operation of a grid-connected Micro-Grid. In: 2013 Smart Grid Conference (SGC), 17-18 December 2013: Iran, pp. 102-107.
18. Fang, W, Liu, H, Chen, H, Zheng, H, Hua, G, He, W. DG planning in stand-alone microgrid considering stochastic characteristic. The Journal of Engineering 2017; 2017: 1181-1185.
19. Gazijahani, FS, Salehi, J. Optimal Bi-level Model for Stochastic Risk-based Planning of Microgrids Under Uncertainty. IEEE Transactions on Industrial Informatics 2018; 14: 3054-3064.
20. Khodaei, A, Bahramirad, S, Shahidehpour, M. Microgrid Planning Under Uncertainty. IEEE Transactions on Power Systems 2015; 30: 2417-2425.
21. Jahangir, H, Ahmadian, A, Golkar, MA. Opyimal desigh of standalone micro-grid considering reliability and investment cost. In: CIRED Workshop; 14-15 June 2016: Helsinki, pp. 1-4.
22. Nadimi, A, Adabi, F. Optimized Planning for Hybrid Microgrid in Grid-Connected Mode. International Journal of Renewable Energy Research 2016; 6: 494-503.
23. Wand, C, Jiao, B, Guo, L, Yuan, K, Ssun, B. Optimal planning of stand-alone microgrids incorporating reliability. J. Mod. Power Syst. Clean Energy 2014; 2: 195-205.
24. Liu, Z, Chen, Y, Luo, Y, Zhao, G, Jin, X. Optimized Planning of Power Source Capacity in Microgrid Considering Combinations of Energy Storage Devices. Appl. Sci. 2016; 6: 1-19.
25. González, A, Riba, JR, Rius, A. Optimal Sizing of a Hybrid Grid-Connected Photovoltaic–Wind–Biomass Power System. Sustainability 2015; 7: 12787-12806.
26. Jasemia, M, Adabi, F, Mozafari, B, Salahi, S. Optimal Operation of Micro-Grids Considering the Uncertainties of Demand and Renewable Energy Resources Generation. Int. Journal of Renewable Energy Development 2016; 5: 233-248.
27. Atwa, YM, El-Saadany, EF. Probabilistic approach for optimal allocation of wind based distributed generation in distribution systems. IET Renew. Power Gener. 2011; 5: 79-88.
28. Atwa, YM, El-Saadany, EF, Salama, MMA, Seethapathy, R. Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization. IEEE Transactions on Power System 2010; 25: 360-370.
29. Zhao, B, Zhang, X, Chen, J, Wang, C, Guo, L. Operation Optimization of Standalone Microgrids Considering Lifetime Characteristics of Battery Energy Storage System. IEEE Transactions on Sustainable Energy 2013; 4: 934-943.
30. Soroudi, A, Mohammadi-Ivatloo, B, Rabiee, A. Energy Hub Management with Intermittent Wind Power. Large Scale Renewable Power Generation. In: J. Hossain and A. Mahmud. Large Scale Renewable Power Generation, Green Energy and Technology. Cham, Switzerland: Springer International Publishing Switzerland, 2014. pp. 413-438.
31. Thang, VV, Zhang, Y, Ha, TT, Liu, S. Optimal operation of energy hub in competitive electricity market considering uncertainties. International Journal of Energy and Environmental Engineering 2018; 9: 351-362.
32. Liu, Z, Wen, F, Ledwich, G. Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Uncertainties. IEEE Transactions on Power Delivery 2011; 26: 2541-2551.
33. Catalogue of European Urban Wind Turbine Manufacturers, Wind Energy Integration in the Urban Environment (WINEUR) 2018, http://www.urbanwind.net/wineur.html.
34. IRENA, Renewable Power Generation Costs in 2017, International Renewable Energy Agency, Abu Dhabi, pp. 1-158.
35. Sollatek Solar Catalogue 2018, https://www.sollatek.com/product-category/solar-products/.
36. Bayod-Rújula, AA, Yuan, Y, Martínez-Gracia, A, Wang, J, Uche, J, Chen, H. Modelling and Simulation of a Building Energy Hub. Proceedings 2018; 2: 1-6.
37. Amir, V, Jadid, S, Ehsan, M. Optimal Planning of a Multi-Carrier Microgrid Considering Demand-Side Management. International Journal of Renewable Energy Research 2018; 8: 238-249.
38. Gong, Q, Lei, J, Ye, J. Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Cost of Operation Risk. Energies 2016; 9: 1-18.
39. Deng, S, Wu, Q, Jing, Z, Wu, L, Wei, F, Zhou, X. Optimal Capacity Configuration for Energy Hubs Considering Part-Load Characteristics of Generation Units. Energies 2017; 10: 2-19.
40. Chen, Z, Yan, Z. Scenario tree reduction methods through clustering nodes. Computers and Chemical Engineering 2018; 109: 96-111.
41. Xu, D, Chen, Z, Yang, L. Scenario tree generation approaches using K-means and LP moment matching methods. Journal of Computational and Applied Mathematics 2012; 236: 4561-4579.