Hybrid optimization algorithm for modeling and management of micro grid connected system

doi:10.1007/s11708-014-0308-8

Front. Energy

2014, Vol. 8

Issue (3) : 305-314 https://doi.org/10.1007/s11708-014-0308-8

RESEARCH ARTICLE

Hybrid optimization algorithm for modeling and management of micro grid connected system

Kallol ROY(

),Kamal Krishna MANDAL

Faculty of Electrical Engineering, University Institute of Technology, University of Burdwan, Burdwan 713104, India

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Abstract

In this paper, a hybrid optimization algorithm is proposed for modeling and managing the micro grid (MG) system. The management of distributed energy sources with MG is a multi-objective problem which consists of wind turbine (WT), photovoltaic (PV) array, fuel cell (FC), micro turbine (MT) and diesel generator (DG). Because, perfect economic model of energy source of the MG units are needed to describe the operating cost of the output power generated, the objective of the hybrid model is to minimize the fuel cost of the MG sources such as FC, MT and DG. The problem formulation takes into consideration the optimal configuration of the MG at a minimum fuel cost, operation and maintenance costs as well as emissions reduction. Here, the hybrid algorithm is obtained as artificial bee colony (ABC) algorithm, which is used in two stages. The first stage of the ABC gets the optimal MG configuration at a minimum fuel cost for the required load demand. From the minimized fuel cost functions, the operation and maintenance cost as well as the emission is reduced using the second stage of the ABC. The proposed method is implemented in the Matlab/Simulink platform and its effectiveness is analyzed by comparing with existing techniques. The comparison demonstrates the superiority of the proposed approach and confirms its potential to solve the problem.

Keywords micro grid (MG) multi-objective function artificial bee colony (ABC) fuel cost operation and maintenance cost

Corresponding Author(s): Kallol ROY

Online First Date: 25 July 2014 Issue Date: 09 September 2014

Cite this article:

Kallol ROY,Kamal Krishna MANDAL. Hybrid optimization algorithm for modeling and management of micro grid connected system[J]. Front. Energy, 2014, 8(3): 305-314.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-014-0308-8
https://academic.hep.com.cn/fie/EN/Y2014/V8/I3/305

Fig.1 MG architecture

Fig.2 Structure of proposed method

Fig.3 Matlab/simulink diagram of proposed system

Tab.1 MG sources ratings and emission factors

Tab.2 Selection of power generators of MG for various techniques

Fig.4 Load for hours

Fig.5 Power curves for hours

Fig.6 Hourly fuel cost for OM

Fig.7 Hourly fuel cost for ABC technique

Fig.8 Hourly fuel cost for proposed technique

Fig.9 Total cost for different techniques

Fig.10 Total cost comparison for ABC and proposed method

1	Baba J, Numata S, Suzuki S, Kusagawa S, Yonezu T, Denda A, Nitta T, Masada E. Fundamental measurements of a small scale micro grid model system. In: Proceedings of International Conference on Electrical Engineering. Kunming, China, 2005, 1-6
2	Mohamed F A, Koivo H N. System modelling and online optimal management of microgrid using mesh adaptive direct search. International Journal of Electrical Power & Energy Systems, 2010, 32(5): 398-407 doi: 10.1016/j.ijepes.2009.11.003
3	Katiraei F, Iravani M R. Transients of a micro-grid system with multiple distributed energy resources. In: Proceedings of International Conference on Power Systems Transients. Montreal, Canada, 2005, Paper No. IPST05-080
4	Kriett P O, Salani M. Optimal control of a residential microgrid. Energy, 2012, 42(1): 321-330 doi: 10.1016/j.energy.2012.03.049
5	Gerry S. Optimal rural microgrid energy management using HOMER. International Journal of Innovations in Engineering & Technology, 2013, 2(1): 113-118
6	Mohamed F A, Koivo H N. Environmental/Economic power dispatch of microgrid using multiobjective genetic algorithms. In: Proceedings of International Conference on Renewable Energy Congress. Sousse, Tunisia: CMERP, 2010, 495-500
7	Kremers E, Viejo P, Barambones O, de Durana J M G. A complex systems modelling approach for decentralized simulation of electrical microgrids. In: Proceedings of 15th IEEE International Conference on Engineering of Complex Computer Systems. Oxford, UK, 2010, 302-311
8	Zhang Y, Gatsis N, Giannakis G B. Robust energy management for microgrids with high-penetration renewables. IEEE Transactions on Sustainable Energy, 2013, 4(4): 944-953 doi: 10.1109/TSTE.2013.2255135
9	Mashhour E, Moghaddas-Tafreshi S M. Mathematical modeling of electrochemical storage for incorporation in methods to optimize the operational planning of an interconnected micro grid. Journal of Zhejiang University Science, 2010, 11(9): 737-750 doi: 10.1631/jzus.C0910721
10	Lasseter R H, Piagi P. Extended microgrid using (DER) distributed energy resources. In: Proceedings of IEEE Power Engineering Society General Meeting. Tampa, USA, 2007, 1-5
11	Nichols D K, Stevens J, Lasseter R H, Eto J H, Vollkommer H T. Validation of the CERTS microgrid concept the CEC/CERTS microgrid testbed. In: Proceedings of IEEE Power Engineering Society General Meeting. Montreal, QC, Canada, 2006, 1-3
12	Lasseter R H, Piagi P. Extended microgrid using (DER) distributed energy resources. In: Proceedings of IEEE Power Engineering Society and General Meeting. Tampa, USA, 2007, 1-5
13	Kroposki B, Pink C, Lynch J, John V, Meor Daniel S, Benedict E, Vihinen I. Development of a high-speed static switch for distributed energy and microgrid applications. In: Proceedings of IEEE Power Conversion Conference. Nagoya, Japan, 2007, 1418-1423
14	Gerry S. Optimal rural microgrid energy management using HOMER. International Journal of Innovations in Engineering and Technology, 2013, 2(1): 56
15	Mohamed F A, Koivo H N. System modelling and online optimal management of microgrid using multiobjective optimization. In: Proceedings of IEEE International Conference on Clean Electrical Power (ICCEP). Capri, Italy, 2007, 148 -153
16	Alikhani E, Ahmadian M, Salemnia A. Optimal short-term planning of a stand-alone microgrid with wind/PV/fuel cell/diesel/microturbine. Canadian Journal on Electrical and Electronics Engineering, 2012, 3(3): 135-141
17	Olivares D E, Ca?izares C A, Kazerani M. A centralized optimal energy management system for microgrids. In: Proceedings of IEEE Conference on Power Engineering Society General Meeting, 2011, 1-6
18	Kariniotakis G N, Soultanis N L, Tsouchnikas A I, Papathanasiou S A, Hatziargyriou N D. Dynamic modeling of microgrids. In: Proceedings of International Conference on Future Power Systems. Amsterdam, Netherlands, 2005, 1-8
19	Khamis A, Mohamed A, Shareef H, Ayob A. Modeling and simulation of small scale microgrid system. Australian Journal of Basic and Applied Sciences, 2012, 6(9): 412-421
20	Jaganathan S, Palaniswami S, Adithya R, Kumaar M N. Synchronous generator modelling and analysis for a microgrid in autonomous and grid connected mode. International Journal of Computers and Applications, 2011, 13(5): 3-7 doi: 10.5120/1779-2454
21	Chen C, Duan S, Cai T, Liu B, Hu G. Smart energy management system for optimal microgrid economic operation. International Journal of Renewable Power Generation, 2011, 5(3): 258-267 doi: 10.1049/iet-rpg.2010.0052
22	Conti S, Nicolosi R, Rizzo S A, Zeineldin H H. Optimal dispatching of distributed generators and storage systems for MV islanded microgrids. IEEE Transactions on Power Delivery, 2012, 27(3): 1243-1251 doi: 10.1109/TPWRD.2012.2194514
23	Tan K T, Peng X Y, So P L, Chu Y C, Chen M Z Q. Centralized control for parallel operation of distributed generation inverters in microgrids. IEEE Transactions on Smart Grid, 2012, 3(4): 1977-1987 doi: 10.1109/TSG.2012.2205952
24	Chen S X, Gooi H B, Wang M Q. Sizing of energy storage for microgrids. IEEE Transactions on Smart Grid, 2012, 3(1): 142-151 doi: 10.1109/TSG.2011.2160745
25	Dasgupta S, Mohan S N, Sahoo S K, Panda S K. Lyapunov function-based current controller to control active and reactive power flow from a renewable energy source to a generalized three-phase microgrid system. IEEE Transactions on Industrial Electronics, 2013, 60(2): 799-813 doi: 10.1109/TIE.2012.2206356
26	Zhang D, Shah N, Papageorgioua L G. Efficient energy consumption and operation management in a smart building with microgrid. Energy Conversion and Management, 2013, 74: 209-222 doi: 10.1016/j.enconman.2013.04.038
27	Mohammadi M, Hosseinian S H, Gharehpetian G B. GA-based optimal sizing of microgrid and DG units under pool and hybrid electricity markets. International Journal of Electrical Power & Energy Systems, 2012, 35(1): 83-92 doi: 10.1016/j.ijepes.2011.09.015
28	Mohamed F A, Koivo H N. System modeling and online optimal management of microgrid with battery storage. In: International Conference on Renewable Energies and Power Quality. Sevilla, Spain, 2007, 1-5

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