Determining the optimum economic insulation thickness of double pipes buried in the soil for district heating systems

Abstract

The insulation thickness (IT) of double pipes buried in the soil (DPBIS) for district heating (DH) systems was optimized to minimize the annual total cost of DPBIS for DH systems. An optimization model to obtain the optimum insulation thickness (OIT) and minimum annual total cost (MATC) of DPBIS for DH systems was established. The zero point theorem and fsolve function were used to solve the optimization model. Three types of heat sources, four operating strategies, three kinds of insulation materials, seven nominal pipe size (NPS) values, and three buried depth (BD) values were considered in the calculation of the OIT and MATC of DPBIS for DH systems, respectively. The optimization results for the above factors were compared. The results show that the OIT and MATC of DPBIS for DH systems can be obtained by using the optimization model. Sensitivity analysis was conducted to investigate the impact of some economic parameters, i.e., unit heating cost, insulation material price, interest rate, and insulation material lifetime, on optimization results. It is found out that the impact of sensitivity factors on the OIT and MATC of DPBIS for DH systems is different.

Keywords

double pipes / optimization model / optimum insulation thickness / minimum annual total cost

References

[1] Åberg M. Investigating the impact of heat demand reductions on Swedish district heating production using a set of typical system models. Applied Energy, 2014, 118: 246–257

[2] Jie P F, Zhu N, Li D Y. Operation optimization of existing district heating systems. Applied Thermal Engineering, 2015, 78: 278–288

[3] Building Energy Research Center of Tsinghua University. 2015 Annual Report on China Building Energy Efficiency. Beijing: China Architecture & Building Press, 2015

[4] Kaynakli O. A study on residential heating energy requirement and optimum insulation thickness. Renewable Energy, 2008, 33(6): 1164–1172

[5] Rocha P, Kaut M, Siddiqui A S. Energy-efficient building retrofits: an assessment of regulatory proposals under uncertainty. Energy, 2016, 101: 278–287

[6] Mikulić D, Bakarić I R, Slijepčević S. The economic impact of energy saving retrofits of residential and public buildings in Croatia. Energy Policy, 2016, 96: 630–644

[7] Walter T, Sohn M D. A regression-based approach to estimating retrofit savings using the Building Performance Database. Applied Energy, 2016, 179: 996–1005

[8] Ciulla G, Galatioto A, Ricciu R. Energy and economic analysis and feasibility of retrofit actions in Italian residential historical buildings. Energy and Buildings, 2016, 128: 649–659

[9] Lund R, Mohammadi S. Choice of insulation standard for pipe networks in 4th generation district heating systems. Applied Thermal Engineering, 2016, 98: 256–264

[10] Berge A, Hagentoft C, Adl-Zarrabi B. Field measurements on a district heating pipe with vacuum insulation panels. Renewable Energy, 2016, 87(Part 3): 1130–1138

[11] Masatin V, Volkova A, Hlebnikov A, Latosov E. Improvement of district heating network energy efficiency by pipe insulation renovation with PUR foam shells. Energy Procedia, 2017, 113: 265–269

[12] Bloomquist R G. Geothermal district energy system analysis, design, and development. Dissertation for the Doctoral Degree. Romania: University of Oradea, 2001

[13] Kalyon M, Sahin A Z. Application of optimal control theory in pipe insulation. Numerical Heat Transfer Part A: Applications, 2002, 41(4): 391–402

[14] Dalla Rosa A, Li H, Svendsen S. Method for optimal design of pipes for low-energy district heating, with focus on heat losses. Energy, 2011, 36(5): 2407–2418

[15] Wojdyga K, Chorzelski M. Chances for Polish district heating systems. Energy Procedia, 2017, 116: 106–118

[16] Berge A, Adl-Zarrabi B, Hagentoft C. Assessing the thermal performance of district heating twin pipes with vacuum insulation Panels. Energy Procedia, 2015, 78: 382–387

[17] Yarahmadi N, Vega A, Jakubowicz I. Determination of essential parameters influencing service life time of polyurethane insulation in district heating pipes. Energy Procedia, 2017, 116: 320–323

[18] Wang X L, Li H, Wang Q L. Influence of insulation layer position on short-time intermittent heating room. Procedia Engineering, 2017, 205: 1484–1493

[19] He P, Sun G, Wang F, Wu H X. Heating Engineering. Beijing: China Architecture & Building Press, 2009

[20] Köfinger M, Basciotti D, Schmidt R R, Meissner E, Doczekal C, Giovannini A. Low temperature district heating in Austria: energetic, ecologic and economic comparison of four case studies. Energy, 2016, 110: 95–104

[21] Tunzi M, Boukhanouf R, Li H W, Svendsen S, Ianakiev A. Improving thermal performance of an existing UK district heat network: a case for temperature optimization. Energy and Buildings, 2018, 158: 1576–1585

[22] Frederiksen S, Werner S. District Heating and Cooling. Lund: Studentlitteratur, 2013

[23] Nord N, Nielsen E K L, Kauko H, Tereshchenko T. Challenges and potentials for low-temperature district heating implementation in Norway. Energy, 2018, 151: 889–902

[24] Lund H, Østergaard P A, Chang M, Werner S, Svendsen S, Sorknæs P, Thorsen J E, Hvelplund F, Mortensen B O G, Mathiesen B V, Bojesen C, Duic N, Zhang X L, Möller B. The status of 4th generation district heating: research and results. Energy, 2018, 164: 147–159

[25] Lund H, Duic N, Østergaard P A, Mathiesen B V. Future district heating systems and technologies: on the role of smart energy systems and 4th generation district heating. Energy, 2018, 165 (Part A): 614–619

[26] China Institute of Building Standard Design & Research. National Technical Measures for Design of Civil Construction (Heating, Ventilation and Air Conditioning). Beijing: China Planning Press, 2009

[27] Zhang L Y, Wang Z N, Yang X H, Jin L W, Zhang Q L, Hu W J. Thermo-economic analysis for directly-buried pipes insulation of district heating piping systems. Energy Procedia, 2017, 105: 3369–3376

[28] Keçebaş A. Determination of insulation thickness by means of exergy analysis in pipe insulation. Energy Conversion and Management, 2012, 58: 76–83

[29] Başoğul Y, Demircan C, Keçebaş A. Determination of optimum insulation thickness for environmental impact reduction of pipe insulation. Applied Thermal Engineering, 2016, 101: 121–130

[30] Özel G, Açıkkalp E, Görgün B, Yamık H, Caner N. Optimum insulation thickness for piping system using exergy and environmental methods. International Journal of Global Warming, 2017, 11(1): 107–123

[31] Başoğul Y, Keçebaş A. Economic and environmental impacts of insulation in district heating pipelines. Energy, 2011, 36(10): 6156–6164

[32] Daşdemir A, Ertürk M, Keçebaş A, Demircan C. Effects of air gap on insulation thickness and life cycle costs for different pipe diameters in pipeline. Energy, 2017, 122: 492–504

[33] Kayfeci M, Yabanova İ, Keçebaş A. The use of artificial neural network to evaluate insulation thickness and life cycle costs: pipe insulation application. Applied Thermal Engineering, 2014, 63(1): 370–378

[34] Daşdemir A, Ural T, Ertürk M, Keçebaş A. Optimal economic thickness of pipe insulation considering different pipe materials for HVAC pipe applications. Applied Thermal Engineering, 2017, 121: 242–254

[35] Kayfeci M. Determination of energy saving and optimum insulation thicknesses of the heating piping systems for different insulation materials. Energy and Buildings, 2014, 69: 278–284

[36] Keçebaş A. Variation of insulation thickness and exergetic cost saving with outdoor temperature in pipe insulation. Environmental Progress & Sustainable Energy, 2013, 32(3): 784–789

[37] Keçebaş A, Ali Alkan M, Bayhan M. Thermo-economic analysis of pipe insulation for district heating piping systems. Applied Thermal Engineering, 2011, 31(17–18): 3929–3937

[38] Ucar A. A thermo-economic approach for determination of optimum thickness of thermal insulation applied to piping systems. Journal of Renewable and Sustainable Energy, 2018, 10(3): 035102

[39] Keçebaş A. Determination of optimum insulation thickness in pipe for exergetic life cycle assessment. Energy Conversion and Management, 2015, 105: 826–835

[40] Jie P F, Kong X F, Rong X, Xie S Q. Selecting the optimum pressure drop per unit length of district heating piping network based on operating strategies. Applied Energy, 2016, 177: 341–353

[41] Liu X M. Engineering Economic Analysis. Beijing: Peking University Press, 2014

[42] Li D Y. Heating Engineering. Beijing: China Architecture & Building Press, 2018

[43] Yuan S C, Zhang J H, Zheng J X. MATLAB Language and Applied Technology. Beijing: National Defense Industry Press, 2011

[44] Su J M, Ruan S Y. MATLAB Practical Tutorial. Beijing: Electronic Industry Press, 2008

[45] Zhang L J, Xiao G, Yang D, Xu S B. MATLAB Data Analysis and Data Mining. Beijing: China Machine Press, 2016

[46] China Academy of Building Research. Design Code for Heating Ventilation and Air Conditioning of Civil Buildings (GB 50736–2012). Beijing: China Architecture & Building Press, 2012

[47] Jie P F, Zhang F H, Fang Z, Wang H B, Zhao Y F. Optimizing the insulation thickness of walls and roofs of existing buildings based on primary energy consumption, global cost and pollutant emissions. Energy, 2018, 159: 1132–1147

[48] Beijing Municipal Commission of Development and Reform. Inquiry about price. 2020, available at the website of beijing.gov.cn

[49] Beijing Gas and Heating Engineering Design Institute. Design Code for City Heating Network (CJJ 34–2010). Beijing: China Architecture & Building Press, 2010

Acknowledgments

This work was supported by the Scientific Research Project of Beijing Municipal Education Commission, China (KM201810017004), and the Engineering and Technology R&D Center of Clean Air Conditioning in Colleges of Shandong (Shandong Huayu University of Technology).

RIGHTS & PERMISSIONS

2020 Higher Education Press