Document Type : Original Article

Authors

Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Evin, Tehran, Iran

Abstract

Using hybrid renewable energy is one of the best alternatives to supply the electrical energy at remote areas. Renewable energy sources are depended to weather conditions or other factors, so for supplying load with renewable sources appropriate capacity of these sources should be selected. In determining the capacity of renewable energy such as wind and solar, considering the stochastic nature of wind speed and solar radiation is very impressive.one of the problems of using energies like Wind and PV in micro-grid is their Intrinsic uncertainty and their random stochastic which made programming and predicting of such resources complicated.
In this Project, stochastic programming and probability scenarios are used in order to model uncertainty in both Wind and PV resources. Optimum programming of micro-grid which is connected to the main grid is considered by mixed integer programming in Gams software in which Virtual Power Producer manages optimum producing and load control by using main control system.
In order to solve the economic distribution of power in a micro-grid with different constraints, such as load and generation balancing, generation constraints, charging of storage resources in different scenarios and also the issue of unit commitment for sources of generation, the mixed integrated programming approach in this paper has been used.

Keywords

[1]     Agrawal M, Mittal A, Azad M (2011). “Micro grid technological activities across the globe: a review.” International Journal of Research & Reviews in Applied Sciences 7.

[2]     Anvari Moghaddam A, Seifi A, Niknam T (2012) “Multi-operation management of a typical micro-grids using particle swarm optimization: a comparative study.” Renewable and Sustainable Energy Reviews 16:1268. doi: 0.1016/j.rser.2011 .10.002.

[3] Bhadoria A, Kamboj V.K, Sharma M. et al. (2018). “A Solution to Non‑convex/Convex and Dynamic Economic Load Dispatch Problem Using Moth Flame Optimizer.” INAE Lett 3: 65.doi:10.1007/s41403-018-0034-3

[4]    Fadlullah Z.M, Kato N (2015). “On Optimally Reducing Power Loss in Micro-Grids with Power Storage Devices.” In: Evolution of Smart Grids. Springer Briefs in Electrical and Computer Engineering. Springer, Cham. doi:10.1007/978-3-319-25391-6_6

[5]   Gupta P, Bhatia R.S, Jain D.K, Ruchika (2018). “Active Islanding Detection Technique for Distributed Generation.” INAE Lett 3: 243. doi: 10.1007/s41403-018-0054-z.

[6]   Gu W, Wu Z, Bo R. et al. (2014). “Modeling, planning and optimal energy management of combined cooling, heating and power microgrid: A review.” International Journal of Electrical Power & Energy Systems 54:26. doi: 10.1016/j.ijepes.2013.06.028.

[7]   Hussain A, Amin M, Khan R.D. et al. (2018). “Optimal Allocation of Flexible AC Transmission System Controllers in Electric Power Networks.” INAE Lett 3: 41. doi:10.1007/s41403-018-0035-2

[8]  Kamboj V.K, Bhadoria A, Gupta N (2018). “A Novel Hybrid GWO‑PS Algorithm for Standard Benchmark Optimization Problems.” INAE Lett 3: 217. doi:10.1007/s41403-018-0051-2

[9] Mohamed F.A, Koivo H.N (2010). “System modelling and online optimal management of microgrid using mesh adaptive direct search.” International Journal of Electrical Power & Energy Systems 32:398. doi: 10.1016/j.ijepes .2009.11.003

[10]  Mohammadi M, Hosseinian S.H, Gharehpetian G.B (2011). “GA-based optimal sizing of microgrid and DG units under pool and hybrid electricity markets.” International Journal of Electrical Power & Energy Systems 35. doi:  10.1016/j.ijepes.2011.09.015

[11]  Morais H, Kadar P, Faria P. et al. (2010). “Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming.” Renewable Energy 35:151. doi: 10.1016/j.renene.2009.02.031

[12]   Niknam T, Azizipanah-Abarghooee R, Narimani M.R (2012). “An efficient scenariobased stochastic programming framework for multi-objective optimal microgrid operation.” Applied Energy 99:455. doi: 10.1016/j.apenergy.2012. 04.017

[13]   Niknam T, Kavousifard A, Tabatabaei S. et al. (2011). “Optimal operation management of fuel cell /wind /photovoltaic power sources connected to distribution networks.” Journal of Power Sources 196. doi: 10.1016/j.jpowsour.2011.05.081

[14]   Roofegari Nejad R, Moghaddas Tafreshi S.M (2014). “Operation Planning of a Smart Microgrid Including Controllable Loads and Intermittent Energy Resources by Considering Uncertainties.” Arab J Sci Eng 39: 6297. doi:10.1007/s13369-014-1267-4

[15]   Seo J.T (2016). “Towards the advanced security architecture for Microgrid systems and applications.” The Journal of Supercomputing 72: 3535. doi:10.1007/s11227-016

[16] Sharma S, Bhattacharjee S, Bhattacharya A (2016). “Grey wolf optimization for optimal sizing of battery energy storage device to minimize operation cost of microgrid.” IET Generation, Transmission & Distribution 10. doi: 10.1049/iet-gtd.2015.0429

[17]   Shukla A, Singh SN (2016). “Multi-Objective Unit Commitment with Renewable Energy Using GSA Algorithm.” INAEL 1: 21. doi:10.1007/s41403-016-0004-6

[18]  Tsikalakis A.G, Hatziargyriou N. D (2008). “Centralized Control for Optimizing Microgrids Operation.” IEEE Transactions on Energy Conversion 23:1. doi:10.1109/PES.2011.6039737