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Spatial planning and optimisation for virtual distribution of BioCNG derived from palm oil mill effluent to meet industrial energy demand

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  • Lee, Ming Kwee
  • Hashim, Haslenda
  • Lim, Jeng Shiun
  • Taib, Mohd Rozainee

Abstract

Rise in energy prices and energy security concerns have become more crucial for the industrial sector to opt for an alternative fuel. Biogas could be used as fuel for electricity generation, boilers or upgraded and compressed as bio compressed natural gas (BioCNG) that can be utilised in various applications, such as transportation, fuel for industry and injected into a gas grid (as biomethane). Biogas, produced by anaerobic digestion (AD) of palm oil mill effluent (POME) can be used as a fuel substitute for natural gas in industry while reducing CO2 emission. Virtual distribution of BioCNG, which is from remotely located natural gas pipeline, has become economically attractive to the industry. However, this concept poses some issues concerning logistic due to the scattered spatial distribution of palm oil mills which discharge large quantities of POME for biogas recovery. Addressing these aspect require an integrated spatial planning and optimisation to synthesise location and allocation network of BioCNG virtual transportation to the respective industry. This paper presents the development of integrated spatial planning and optimisation of BioCNG supply and distribution network through virtual pipelines to meet the on-site energy demand of specific industry, while minimising the total operational cost. The data from network analysis of ArcGIS will be coded into the Generalised Algebraic Modelling System (GAMS) model to generate a supply cost curve for multiple sources of energy carrier, i.e., LNG, NG through pipeline network, BioCNG through virtual pipelines with and without upgrading. Two case studies were evaluated to determine the optimal energy supply allocation for demand location. This model is beneficial for BioCNG network management while reducing carbon emissions. Results showed the optimised combination of energy supply to meet energy demand of selected industries, which was 198.9 MW of BioCNG production and 401.1 MW of LNG import. The percentage cost reduction of the optimised energy supply is 36.3%.

Suggested Citation

  • Lee, Ming Kwee & Hashim, Haslenda & Lim, Jeng Shiun & Taib, Mohd Rozainee, 2019. "Spatial planning and optimisation for virtual distribution of BioCNG derived from palm oil mill effluent to meet industrial energy demand," Renewable Energy, Elsevier, vol. 141(C), pages 526-540.
    • Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:526-540
    DOI: 10.1016/j.renene.2019.03.097
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    1. Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
    2. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin & Muis, Zarina Abdul, 2017. "Optimisation of oil palm biomass and palm oil mill effluent (POME) utilisation pathway for palm oil mill cluster with consideration of BioCNG distribution network," Energy, Elsevier, vol. 121(C), pages 865-883.
    3. Foo, Dominic C.Y. & Tan, Raymond R. & Lam, Hon Loong & Abdul Aziz, Mustafa Kamal & Klemeš, Jiří Jaromír, 2013. "Robust models for the synthesis of flexible palm oil-based regional bioenergy supply chain," Energy, Elsevier, vol. 55(C), pages 68-73.
    4. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    5. Steinbuks, Jevgenijs & Neuhoff, Karsten, 2014. "Assessing energy price induced improvements in efficiency of capital in OECD manufacturing industries," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 340-356.
    6. Fadaee, M. & Radzi, M.A.M., 2012. "Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3364-3369.
    7. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    8. Subramanian, K.A. & Mathad, Vinaya C. & Vijay, V.K. & Subbarao, P.M.V., 2013. "Comparative evaluation of emission and fuel economy of an automotive spark ignition vehicle fuelled with methane enriched biogas and CNG using chassis dynamometer," Applied Energy, Elsevier, vol. 105(C), pages 17-29.
    9. Chandra, R. & Vijay, V.K. & Subbarao, P.M.V. & Khura, T.K., 2011. "Performance evaluation of a constant speed IC engine on CNG, methane enriched biogas and biogas," Applied Energy, Elsevier, vol. 88(11), pages 3969-3977.
    10. Paolo Agnolucci, 2010. "Stochastic Trends and Technical Change: The Case of Energy Consumption in the British Industrial and Domestic Sectors," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 111-136.
    11. Agnolucci, Paolo, 2009. "The energy demand in the British and German industrial sectors: Heterogeneity and common factors," Energy Economics, Elsevier, vol. 31(1), pages 175-187, January.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Ng, Denny K.S. & Wong, Sarah L.X. & Andiappan, Viknesh & Ng, Lik Yin, 2023. "Mathematical optimisation for sustainable bio-methane (Bio-CH4) production from palm oil mill effluent (POME)," Energy, Elsevier, vol. 265(C).
    2. Mohd Idris, Muhammad Nurariffudin & Hashim, Haslenda & Leduc, Sylvain & Yowargana, Ping & Kraxner, Florian & Woon, Kok Sin, 2021. "Deploying bioenergy for decarbonizing Malaysian energy sectors and alleviating renewable energy poverty," Energy, Elsevier, vol. 232(C).
    3. Mohd Idris, Muhammad Nurariffudin & Leduc, Sylvain & Yowargana, Ping & Hashim, Haslenda & Kraxner, Florian, 2021. "Spatio-temporal assessment of the impact of intensive palm oil-based bioenergy deployment on cross-sectoral energy decarbonization," Applied Energy, Elsevier, vol. 285(C).
    4. Lee, Ming Kwee & Hashim, Haslenda & Ho, Wai Shin & Muis, Zarina Ab & Yunus, Nor Alafiza & Xu, Huijin, 2020. "Integrated spatial and pinch analysis of optimal industrial energy supply mix with consideration of BioCNG derived from palm oil mill effluent," Energy, Elsevier, vol. 209(C).

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