Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

  • Authors

    • Mohd Effendi Amran
    • Mohd Nabil Muhtazaruddin
    2018-08-13
    https://doi.org/10.14419/ijet.v7i3.15.17404
  • Green Building Rating System (GBRS), Artificial Bee Colony (ABC), Power Loss Minimization, Solar Photovoltaic (PV), and Distributed Generation (DG).

  • This paper presents an optimization solution for renewable Distributed Generation (DG), as imposed in the Green Building Rating System (GBRS) for a public hospital. Solar photovoltaic DG unit (PV-DG) is identified as a type of DG used in this paper. The proposed optimization via PV-DG coordination will improve the sustainable energy performance of the green building by power loss reduction within accepted lower losses region using Artificial Bee Colony (ABC) algorithm. The setup input data from one of Malaysian public hospitals’ power distribution system is been adopted and simulation results via MATLAB programming show that the optimization of DG forming into bigger-scale imposed system provides a better outcome in minimization of total power losses within appropriate voltage profile as compared to current PV-DG imposed in GBRS. The objective function representing total power losses which also supported by related literature give a measure that forming sufficient and optimal PV-DG assessment criteria is highly important, thus, current PV-DG assessment in GBRS is proposed to be reviewed into new parameter setting for public hospital due to its’ high energy demand and distinctive electrical load profile.

     

     

  • References

    1. [1] Alnaser, N., R. Flanagan, and W. Alnaser, Model for calculating the sustainable building index (SBI) in the kingdom of Bahrain. Energy and buildings, 2008. 40(11): p. 2037-2043.

      [2] Moghimi, S., et al. Building energy index (BEI) in large scale hospital: case study of Malaysia. in 4th WSEAS International Conference on Recent Reseaches in Geography Geology, Energy, Environment and Biomedicine, Corfu Island, Greece. 2011.

      [3] Tenaga Nasional, B., Electricity Supply Application Handbook Third (3rd) Edition. Kuala Lumpur: Nur Johan Sdn Bhd, 2015.

      [4] EMEER 2008, E., Efficient Management of Electrical Energy Regulation 2008 (EMEER 2008).

      [5] Sahamir, S.R. and R. Zakaria, Green assessment criteria for public hospital building development in Malaysia. Procedia Environmental Sciences, 2014. 20: p. 106-115.

      [6] Unit, E.P., Eleventh Malaysia plan, 2016-2020: Anchoring growth on people. Malaysia: Prime Minister’s Department, 2015.

      [7] Lund, H., A. Marszal, and P. Heiselberg, Zero energy buildings and mismatch compensation factors. Energy and Buildings, 2011. 43(7): p. 1646-1654.

      [8] Mwasha, A., R.G. Williams, and J. Iwaro, Modeling the performance of residential building envelope: The role of sustainable energy performance indicators. Energy and buildings, 2011. 43(9): p. 2108-2117.

      [9] GhaffarianHoseini, A., et al., Sustainable energy performances of green buildings: A review of current theories, implementations and challenges. Renewable and Sustainable Energy Reviews, 2013. 25: p. 1-17.

      [10] Morrissey, J. and R. Horne, Life cycle cost implications of energy efficiency measures in new residential buildings. Energy and buildings, 2011. 43(4): p. 915-924.

      [11] Index, G.B. and G. Malaysia, Green Building Index. 2013, Retrieved.

      [12] LEED, U.v., LEED v4 for Building Operations and Maintenance. Acedido em: http://www. usgbc. org/resources/leed-v4-building-operations-and-maintenance-current-version, 2016.

      [13] Glavinich, T.E. and T.A. Taylor, Contractor's guide to green building construction: management, project delivery, documentation, and risk reduction. 2008: Wiley Online Library.

      [14] Shi, Q., Strategies of implementing a green building assessment system in mainland China. Journal of Sustainable Development, 2009. 1(2): p. 13.

      [15] Hill, R., P. Bowen, and L. Opperman, Sustainable building assessment methods in South Africa: an agenda for research. 2002.

      [16] Rahardjati, R., M.F. Khamidi, and A. Idrus, The level of importance of criteria and sub criteria in green building index malaysia. 2010.

      [17] Bahaudin, A.Y., et al., Construction Sustainability & Awareness amongst Contractors in the Northern Region of Malaysia. International Journal of Supply Chain Management, 2017. 6(2): p. 259-264.

      [18] Xia, C., Y. Zhu, and B. Lin, Renewable energy utilization evaluation method in green buildings. Renewable Energy, 2008. 33(5): p. 883-886.

      [19] Shi, L. and M.Y.L. Chew, A review on sustainable design of renewable energy systems. Renewable and Sustainable Energy Reviews, 2012. 16(1): p. 192-207.

      [20] Deng, S., et al., Case study of green energy system design for a multi-function building in campus. Sustainable Cities and Society, 2011. 1(3): p. 152-163.

      [21] Muhtazaruddin, M.N.B., et al. Optimal distributed generation and capacitor coordination for power loss minimization. in T&D Conference and Exposition, 2014 IEEE PES. 2014. IEEE.

      [22] Van Thong, V., J. Driesen, and R. Belmans, Interconnection of distributed generators and their influences on power system. International Energy Journal, 2005. 6.

      [23] Bawan, E.K. Distributed generation impact on power system case study: Losses and voltage profile. in Power Engineering Conference (AUPEC), 2012 22nd Australasian Universities. 2012. IEEE.

      [24] Griffin, T., et al. Placement of dispersed generation systems for reduced losses. in System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on. 2000. IEEE.

      [25] Parizad, A., A. Khazali, and M. Kalantar. Optimal placement of distributed generation with sensitivity factors considering voltage stability and losses indices. in Electrical Engineering (ICEE), 2010 18th Iranian Conference on. 2010. IEEE.

      [26] Acharya, N., P. Mahat, and N. Mithulananthan, An analytical approach for DG allocation in primary distribution network. International Journal of Electrical Power & Energy Systems, 2006. 28(10): p. 669-678.

      [27] Ramesh, L., et al., Minimization of power loss in distribution networks by different techniques. International Journal of Electrical Power and Energy Systems Engineering, 2009. 2(1): p. 1-6.

      [28] Hung, D.Q. and N. Mithulananthan, Multiple distributed generator placement in primary distribution networks for loss reduction. IEEE Transactions on industrial electronics, 2013. 60(4): p. 1700-1708.

      [29] Banos, R., et al., Optimization methods applied to renewable and sustainable energy: A review. Renewable and Sustainable Energy Reviews, 2011. 15(4): p. 1753-1766.

      [30] Bhowmik, C., et al., Optimal green energy planning for sustainable development: A review. Renewable and Sustainable Energy Reviews, 2017. 71: p. 796-813.

      [31] Yasin, Z.M., et al. Optimal sizing of distributed generation by using quantum-inspired evolutionary programming. in Power Engineering and Optimization Conference (PEOCO), 2010 4th International. 2010. IEEE.

      [32] Muhtazaruddin, M.N.B., J.J.B. Jamian, and G. Fujita, Determination of optimal output power and location for multiple distributed generation sources simultaneously by using artificial bee colony. IEEJ Transactions on Electrical and Electronic Engineering, 2014. 9(4): p. 351-359.

      [33] Muhtazaruddin, M.N.B., et al., Distribution Power Loss Minimization via Distributed Generation, Capacitor and Network Reconfiguration. Indonesian Journal of Electrical Engineering and Computer Science, 2017. 5(3): p. 488-495.

      [34] Prabha, D.R. and T. Jayabarathi, Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm. Ain Shams Engineering Journal, 2016. 7(2): p. 683-694.

      [35] Kansal, S., V. Kumar, and B. Tyagi, Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 2013. 53: p. 752-760.

      [36] El-Zonkoly, A., Optimal placement of multi-distributed generation units including different load models using particle swarm optimization. Swarm and Evolutionary Computation, 2011. 1(1): p. 50-59.

      [37] Kansal, S., et al., Optimal placement of distributed generation in distribution networks. International Journal of Engineering, Science and Technology, 2011. 3(3).

      [38] Biswas, S., S.K. Goswami, and A. Chatterjee, Optimum distributed generation placement with voltage sag effect minimization. Energy Conversion and Management, 2012. 53(1): p. 163-174.

      [39] Moradi, M.H. and M. Abedini, A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems, 2012. 34(1): p. 66-74.

      [40] Hussain, I. and A.K. Roy. Optimal distributed generation allocation in distribution systems employing modified artificial bee colony algorithm to reduce losses and improve voltage profile. in Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on. 2012. IEEE.

      [41] Karaboga, D. and B. Basturk, Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. Foundations of fuzzy logic and soft computing, 2007: p. 789-798.

      [42] Lalitha, M.P., N.S. Reddy, and V.V. Reddy, Optimal DG placement for maximum loss reduction in radial distribution system using ABC algorithm. International journal of reviews in computing, 2010. 3: p. 44-52.

      [43] Mahdad, B. and K. Srairi, Adaptive differential search algorithm for optimal location of distributed generation in the presence of SVC for power loss reduction in distribution system. Engineering Science and Technology, an International Journal, 2016. 19(3): p. 1266-1282.

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    Effendi Amran, M., & Nabil Muhtazaruddin, M. (2018). Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital. International Journal of Engineering & Technology, 7(3.15), 40-45. https://doi.org/10.14419/ijet.v7i3.15.17404