Energy Management System for Hospital Building Using Genetic Algorithm


  • Normazlina Mat Isa Jabatan Kejuruteraan Elektrik, Politeknik Merlimau, KB 1031, Pejabat Pos Merlimau, 71300 Merlimau, Melaka Department of Electrical Power Engineering, Faculty of Electrical Engineering, University Technology Malaysia, 81310 Skudai, Johor
  • Chee Wei Tan Department of Electrical Power Engineering, Faculty of Electrical Engineering, University Technology Malaysia, 81310 Skudai, Johor
  • A.H.M. Yatim Department of Electrical Power Engineering, Faculty of Electrical Engineering, University Technology Malaysia, 81310 Skudai, Johor


Cogeneration, Energy Management System, Genetic Algorithm, Hospital, Microgrid,


Microgrid (MG) as well as energy management system (EMS) is undergoing an immense growth. A cogeneration, as one of MG topologies, needs an efficient controller to manage the supply-demand activity so that both sides can achieve their goals. The EMS plays a role as a supervisory controller to optimally dispatch the energy in order to satisfy the load demand. In this paper, EMS based on optimization approaches to minimize the operating cost of cogeneration system is presented. This study developed a cogeneration system that consists of grid-connected photovoltaic, fuel cell and battery. This system was adopted at hospital building, which was selected as a sample of load profile. An optimization problem was formulated by considering decision variables, input system parameters, objective function and constraints. Furthermore, the problems were solved using Genetic Algorithm. The viability of the optimization approaches was simulated in MATLAB environment.


A. Ipakchi and F. Albuyeh, “Grid of the Future,” IEEE power & energy magazine, no. april, 2009.

S. J. Kang, J. Park, K.-Y. Oh, J. G. Noh, and H. Park, “Schedulingbased real time energy flow control strategy for building energy management system,” Energy Build., vol. 75, pp. 239–248, Jun. 2014.

H. I. Onovwiona and V. I. Ugursal, “Residential cogeneration systems : review of the current technology,” vol. 10, pp. 389–431, 2006.

T. S. Ustun, C. Ozansoy, and A. Zayegh, “Recent developments in microgrids and example cases around the world—A review,” Renew. Sustain. Energy Rev., vol. 15, no. 8, pp. 4030–4041, Oct. 2011.

F. Manzano-agugliaro, F. G. Montoya, C. Gil, A. Alcayde, J. Gómez, and R. Ba, “Optimization methods applied to renewable and sustainable energy : A review,” vol. 15, pp. 1753–1766, 2011.

M. Iqbal, M. Azam, M. Naeem, A. S. Khwaja, and A. Anpalagan, “Optimization classi fi cation , algorithms and tools for renewable energy : A review,” vol. 39, pp. 640–654, 2014.

H. Karami, M. J. Sanjari, a. Tavakoli, and G. B. Gharehpetian, “Optimal Scheduling of Residential Energy System Including Combined Heat and Power System and Storage Device,” Electr. Power Components Syst., vol. 41, no. 8, pp. 765–781, May 2013.

M. Javad, S. Hossein, B. Gharehpetian, and C. Heat, “An Optimal Dispatch Algorithm for Managing Residential Distributed Energy Resources,” 2013.

M. Amer, a. Namaane, and N. K. M’Sirdi, “Optimization of Hybrid Renewable Energy Systems (HRES) Using PSO for Cost Reduction,” Energy Procedia, vol. 42, pp. 318–327, 2013.

P. García-Triviño, F. Llorens-Iborra, C. a. García-Vázquez, A. J. GilMena, L. M. Fernández-Ramírez, and F. Jurado, “Long-term optimization based on PSO of a grid-connected renewable energy/battery/hydrogen hybrid system,” Int. J. Hydrogen Energy, vol. 39, no. 21, pp. 10805–10816, 2014.

M. Paulitschke, T. Bocklisch, and M. Böttiger, “Sizing Algorithm for a PV-battery-H2-hybrid System Employing Particle Swarm Optimization,” Energy Procedia, vol. 73, pp. 154–162, 2015.

A. Ketabi and A. A. Babaee, “Application of the ant colony search algorithm to reactive power pricing in an open electricity market,” Am. J. Appl. Sci., vol. 6, no. 5, pp. 956–963, 2009.

M. Rouholamini and M. Mohammadian, “Heuristic-based power management of a grid-connected hybrid energy system combined with hydrogen storage,” Renew. Energy, vol. 96, pp. 354–365, 2016.

B. Kilkiş, “Energy consumption and CO2 emission responsibilities of terminal buildings: A case study for the future Istanbul International Airport,” Energy Build., vol. 76, pp. 109–118, 2014.

J. H. Braslavsky, J. R. Wall, and L. J. Reedman, “Optimal distributed energy resources and the cost of reduced greenhouse gas emissions in a large retail hopping centre,” Appl. Energy, vol. 155, pp. 120–130, 2015.

R. Napoli, M. Gandiglio, A. Lanzini, and M. Santarelli, “Technoeconomic analysis of PEMFC and SOFC micro-CHP fuel cell systems for the residential sector,” Energy Build., vol. 103, pp. 131–146, 2015.

M. Elsied, A. Oukaour, H. Gualous, R. Hassan, and A. Amin, “An advanced energy management of microgrid system based on genetic algorithm,” 2014 IEEE 23rd Int. Symp. Ind. Electron., pp. 2541–2547, Jun. 2014.

G. A. Mary and R. Rajarajeswari, “SMART GRID COST OPTIMIZATION USING GENETIC ALGORITHM,” Int. J. Res. Eng. Technol., vol. 3, no. 7, pp. 282–287, 2014.

W. Gu, Z. Wu, and X. Yuan, “Microgrid economic optimal operation of the combined heat and power system with renewable energy,” IEEE PES Gen. Meet., pp. 1–6, Jul. 2010.

W. Gu et al., “Electrical Power and Energy Systems Modeling , planning and optimal energy management of combined cooling,heating and power microgrid : A review,” Int. J. Electr. Power Energy Syst., vol. 54, pp. 26–37, 2014.

E. De Santis, A. Rizzi, A. Sadeghian, F. Massimo, and F. Mascioli, “Genetic Optimization of a Fuzzy Control System for Energy Flow Management in Micro-Grids,” pp. 418–423, 2013.

M. Motevasel and T. Niknam, “Multi-objective energy management of CHP (combined heat and power) based micro grid,” vol. 51, 2013.

M. H. Moradi, M. Hajinazari, S. Jamasb, and M. Paripour, “An energy management system ( EMS ) strategy for combined heat and power ( CHP ) systems based on a hybrid optimization method employing fuzzy programming,” Energy, vol. 49, pp. 86–101, 2013.

M. Y. El-Sharkh, M. Tanrioven, a. Rahman, and M. S. Alam, “Cost related sensitivity analysis for optimal operation of a grid-parallel PEM fuel cell power plant,” J. Power Sources, vol. 161, no. 2, pp. 1198–1207, Oct. 2006.

M. Y. El-Sharkh, a. Rahman, and M. S. Alam, “Evolutionary programming-based methodology for economical output power from PEM fuel cell for micro-grid application,” J. Power Sources, vol. 139, no. 1–2, pp. 165–169, Jan. 2005.

“TNB Pricing and Tariff,” TNB, 2014. [Online]. Available: [Accessed: 01-Jul-2016].

L. M. Schmitt, “Theory of genetic algorithms,” vol. 259, pp. 1–61, 2001.

G. Merei, C. Berger, and D. Uwe, “Optimization of an off-grid hybrid PV – Wind – Diesel system with different battery technologies using genetic algorithm,” Sol. Energy, vol. 97, pp. 460–473, 2013.

X.-S. Yang, Engineering Optimization - An introduction with Metaheuristic Applications. 2010.




How to Cite

Mat Isa, N., Tan, C. W., & Yatim, A. (2017). Energy Management System for Hospital Building Using Genetic Algorithm. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-7), 111–118. Retrieved from