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Study and development of a logical model for an ORC based district heating renewable energy system considering discrete analysis

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  • Acharjee, Ashis
  • Chakraborti, Prasun

Abstract

Renewable energy sources may help build energy-efficient, ecologically friendly communities. District heating systems are crucial for distributed renewable energy. The objective of this study is to establish a theoretical framework for a district heating distribution system capable of accommodating bi-directional flow and effectively serving a large number of consumers. Distinction and continuity are present in District Heating System fuel selection and energy demand determination. Scholarly literature suggests many modeling methods for discrete and continuous consumer decision-making. This method has been used to solve transportation, housing, and water problems. The overall demand for consumer choices can be separated into two components: a discrete component with several possibilities and a continuous component. Energy includes social, economic, security, climate, and environmental factors. This study analyzed previous energy logical modeling methods and examines energy consumption trends and climate change. This study supports its claims on modern conflicts using expert interviews, research expertise, and a thorough literature assessment. The model was used to assess control system architectural improvements and low-cost device integration. This study shows the versatility of using real data and model output under varied boundary conditions by using validation. The research suggests that adding waste heat input may make pressure equilibrium in nearby consumer substations harder. Despite assumptions and simplifications, the results show waste heat source features, benefits, and limitations.

Suggested Citation

  • Acharjee, Ashis & Chakraborti, Prasun, 2024. "Study and development of a logical model for an ORC based district heating renewable energy system considering discrete analysis," Energy, Elsevier, vol. 298(C).
  • Handle: RePEc:eee:energy:v:298:y:2024:i:c:s0360544224009010
    DOI: 10.1016/j.energy.2024.131128
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    1. Nordhaus, William D, 1991. "To Slow or Not to Slow: The Economics of the Greenhouse Effect," Economic Journal, Royal Economic Society, vol. 101(407), pages 920-937, July.
    2. Donald H. Rosenthal & Howard K. Gruenspecht & Emily A. Moran, 1995. "Effects of Global Warming on Energy Use for Space Heating and Cooling in the United States," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 77-96.
    3. William R. Cline, 1992. "Economics of Global Warming, The," Peterson Institute Press: All Books, Peterson Institute for International Economics, number 39, April.
    4. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-771, September.
    5. Vaage, Kjell, 2000. "Heating technology and energy use: a discrete/continuous choice approach to Norwegian household energy demand," Energy Economics, Elsevier, vol. 22(6), pages 649-666, December.
    6. Julie A. Hewitt & W. Michael Hanemann, 1995. "A Discrete/Continuous Choice Approach to Residential Water Demand under Block Rate Pricing," Land Economics, University of Wisconsin Press, vol. 71(2), pages 173-192.
    7. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    8. Harold Hotelling, 1931. "The Economics of Exhaustible Resources," Journal of Political Economy, University of Chicago Press, vol. 39(2), pages 137-137.
    9. Pompelli, Gregory K & Heien, Dale, 1991. "Discrete/Continuous Consumer Demand Choices: An Application to the U.S. Domestic and Imported White Wine Markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 18(1), pages 117-130.
    10. Fred Mannering & Clifford Winston, 1985. "A Dynamic Empirical Analysis of Household Vehicle Ownership and Utilization," RAND Journal of Economics, The RAND Corporation, vol. 16(2), pages 215-236, Summer.
    11. Mervyn A. King, 1980. "An Econometric Model of Tenure Choice and Demand for Housing as a Joint Decision," NBER Chapters, in: Econometric Studies in Public Finance, pages 137-159, National Bureau of Economic Research, Inc.
    12. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    13. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    14. Schmertmann, Carl P., 1994. "Selectivity bias correction methods in polychotomous sample selection models," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 101-132.
    15. Lee, Lung-Fei & Trost, Robert P., 1978. "Estimation of some limited dependent variable models with application to housing demand," Journal of Econometrics, Elsevier, vol. 8(3), pages 357-382, December.
    16. Wang, Dongxiang & Ling, Xiang & Peng, Hao & Liu, Lin & Tao, LanLan, 2013. "Efficiency and optimal performance evaluation of organic Rankine cycle for low grade waste heat power generation," Energy, Elsevier, vol. 50(C), pages 343-352.
    17. Gnutek, Z & Bryszewska-Mazurek, A, 2001. "The thermodynamic analysis of multicycle ORC engine," Energy, Elsevier, vol. 26(12), pages 1075-1082.
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