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Development of a Network-location-model for the Economic Optimization of Local Heating Systems in Urban Chile

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Abstract

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.

Zusammenfassung

Die Kraft-Wärme-Kopplung stellt unabhängig vom eingesetzten Energieträger eine sehr effiziente Möglichkeit zur Bereitstellung von Strom und Wärme dar und kann dazu beitragen, den Primärenergieverbrauch zu reduzieren. Für eine umfassende Machbarkeitsstudie für die Beheizung von Wohngebäuden mittels Nahwärmenetzen werden geeignete Modelle benötigt, um lokale Nahwärmesysteme adäquat abzubilden und simultan zu optimieren. In diesem Beitrag wird daher ein gemischt-ganzzahliges lineares Programm (MILP – mixed integer linear program) zur simultanen Optimierung von Nahwärmenetzen, Kraftwerkskapazitäten und Standorten vorgestellt. Das entwickelte Modell wird exemplarisch für die Planung der Nahwärmeversorgung von Osorno, einer Großstadt in Chile, angewendet. Entscheidungsträger können das Modell dazu nutzen, um die Auswirkungen variierender Eingangsparameter auf die ökonomische Vorteilhaftigkeit einer Investition zu untersuchen, Break-Even-Preise zu ermitteln und Einsparungen an Treibhausgasemissionen abzuschätzen.

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Notes

  1. It should be noted from a thermodynamic perspective, that the continuity of heat flow must be referred to by the systems boundaries. Within the network, the conservation of thermal energy must be guaranteed.

  2. When it comes to the actual implementation of CHP, the service level is subject to a technical optimization.

  3. http://www.cne.cl/estadisticas/energia/electricidad

  4. 1000 CLP is equal to about 1.40 EUR or 1.50 USD.

  5. The pipeline’s diameter in the network depends on the supplied flow rate, forming an implicit relationship between pipeline cost and supplied heat. Also, heat loss from the distribution system depends on pipe dimensions, which may vary from section to section and on the desired temperature of district heat. For the initial feasibility study, however, we have chosen a typical value suggested by Chilean engineers, which should be further investigated within a subsequent technical optimization during the project realization phase.

  6. The scale factor for CHP is about 0.6 (Peters et al. 2003), which would lead to a non-linear optimization problem.

References

  • Bennett C (2009) Chile to warm up its renewables market. Renew Energy Focus 9(7):79–83

    Article  Google Scholar 

  • Bluemling B, de Visser I (2013) Overcoming the “club dilemma” of village-scale bioenergy projects—the case of India. Energy Policy 63:18–25

    Article  Google Scholar 

  • Börjesson M, Ahlgren EO (2010) Biomass gasification in cost-optimized district heating systems—a regional modelling analysis. Energy Policy 38(1):168–180

    Article  Google Scholar 

  • Bruns E, Futterlieb M, Ohlhorst D, Wenzel B (2012) Erneuerbare Energien in Wärmenetzen – eine realistische Perspektive? Z Energiewirtsch 36(3):159–172

    Article  Google Scholar 

  • Buoro D, Pinamonti P, Reini M (2014) Optimization of a distributed cogeneration system with solar district heating. Appl Energy 124:298–308

    Article  Google Scholar 

  • Casisi M, Pinamonti P, Reini M (2009) Optimal lay-out and operation of combined heat & power (CHP) distributed generation systems. Energy 34:2175–2183

    Article  Google Scholar 

  • Cheng X, Du D (2001) Steiner trees in industry. Kluwer, Dordrecht, Boston

    MATH  Google Scholar 

  • DigitalGlobe (2015) Satellite photos of osorno

    Google Scholar 

  • Dreyfus SE, Wagner RA (1971) The Steiner problem in graphs. Networks 1(3):195–207

    Article  MathSciNet  MATH  Google Scholar 

  • Duan G, Yu Y (2003) Power distribution system optimization by an algorithm for capacitated Steiner tree problems with complex-flows and arbitrary cost functions. Int J Electr Power Energy Syst 25(7):515–523

    Article  Google Scholar 

  • Duran E, Aravena C, Aguilar R (2015) Analysis and decomposition of energy consumption in the Chilean industry. Energy Policy 86:552–561

    Article  Google Scholar 

  • Fonseca JA, Schlueter A (2015) Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts. Appl Energy 142:247–265

    Article  Google Scholar 

  • Ford LR, Fulkerson DR (1962) Flows in networks. Princeton University Press, Princeton

    MATH  Google Scholar 

  • Gebremedhin A, Karlsson B, Björnfot K (2009) Sustainable energy system – a case study from Chile. Renew Energy 34(5):1241–1244

    Article  Google Scholar 

  • Goh CS, Junginger M, Cocchi M, Marchal D, Thrän D, Hennig C, Heinimö J, Nikolaisen L, Schouwenberg P-P, Bradley D, Hess R, Jacobson J, Ovard L, Deutmeyer M (2013) Wood pellet market and trade: a global perspective. Biofuels Bioprod Biorefining 7(1):24–42

    Article  Google Scholar 

  • Guinee JB, Heijungs R, Huppes G, Zamagni A, Masoni P, Buonamici R, Ekvall T, Rydberg T (2010) Life cycle assessment: past, present, and future. Environ Sci Technol 45(1):90–96

    Article  Google Scholar 

  • Hendricks AM, Wagner JE, Volk TA, Newman DH, Brown TR (2016) A cost-effective evaluation of biomass district heating in rural communities. Appl Energy 162:561–569

    Article  Google Scholar 

  • Hiete M, Ludwig J, Bidart C, Schultmann F (eds) (2010) Challenges for sustainable biomass utilisation: proceedings of the Chilean-German Biociclo Workshop. Karlsruhe, 26.3.2009. KIT Scientific Publishing, Karlsruhe

    Google Scholar 

  • Jennings M, Fisk D, Shah N (2014) Modelling and optimization of retrofitting residential energy systems at the urban scale. Energy 64:220–233

    Article  Google Scholar 

  • Kaltschmitt M, Thrän D, Bloche-Daub K, Thormann L, Pfeiffer D (2016) Bioenergie – Beitrag zum heutigen und zukünftigen Energiesystem. Z Energiewirtsch 40(4):181–197

    Article  Google Scholar 

  • Karschin I, Geldermann J (2015) Efficient cogeneration and district heating systems in bioenergy villages: an optimization approach. J Clean Prod 104:305–314

    Article  Google Scholar 

  • Keirstead J, Samsatli N, Pantaleo AM, Shah N (2012) Evaluating biomass energy strategies for a UK eco-town with an MILP optimization model. Energy 39:306–316

    Google Scholar 

  • Klöpffer W, Grahl B (1997) Life Cycle Assessment (LCA). A guide to best practice vol. 11. Springer, Boston

    Google Scholar 

  • Liu P, Gerogiorgis DI, Pistikopoulos EN (2007) Modelling, investment planning and optimisation for the design of a polygeneration energy system. In: Pleşu V, Agachi PŞ (eds) 17th European Symposium on Computer Aided Process Engineering. Computer Aided Chemical Engineering, vol 24. Elsevier, Amsterdam, pp 1095–1102

    Chapter  Google Scholar 

  • Lockhart J, Schwartz SB (1983) Early latin america: a short history of colonial Spanish America and Brazil. Cambridge Latin American studies, vol. 46. Cambridge University Press, Cambridge and New York

    Google Scholar 

  • Lund R, Persson U (2016) Mapping of potential heat sources for heat pumps for district heating in Denmark. Energy 110:129. https://doi.org/10.1016/j.energy.2015.12.127

    Article  Google Scholar 

  • Mangoyana RB, Smith TF (2011) Decentralised bioenergy systems: a review of opportunities and threats. Energy Policy 39(3):1286–1295

    Article  Google Scholar 

  • Merkel E, Kunze R, McKenna R, Fichtner W (2017) Modellgestützte Bewertung des Kraft-Wärme-Kopplungsgesetzes (2016) anhand ausgewählter Anwendungsfälle in Wohngebäuden. Z Energiewirtsch 41(1):1–22

    Article  Google Scholar 

  • Morvaj B, Evins R, Carmeliet J (2016) Optimization framework for distributed energy systems with integrated electrical grid constraints. Appl Energy 171:296–313

    Article  Google Scholar 

  • Müller E (2001) Development of a test reference year on a limited data base for simulations on passive heating and cooling in Chile. Building Simulation, Rio de Janeiro, 13.–15. August, pp 135–142

    Google Scholar 

  • Mundaca TL (2013) Climate change and energy policy in Chile: up in smoke? Energy Policy 52:235–248

    Article  Google Scholar 

  • Nussbaumer T, Thalmann S (2016) Influence of system design on heat distribution costs in district heating. Energy 101:496–505

    Article  Google Scholar 

  • Ochoa C, Dyner I, Franco CJ (2013) Simulating power integration in Latin America to assess challenges, opportunities, and threats. Energy Policy 61:267–273

    Article  Google Scholar 

  • OECD (2013) OECD Urban Policy Reviews, Chile. OECD, Paris

    Google Scholar 

  • Omu A, Choudhary R, Boies A (2013) Distributed energy resource system optimisation using mixed integer linear programming. Energy Policy 61:249–266

    Article  Google Scholar 

  • Orasche J, Seidel T, Hartmann H, Schnelle-Kreis J, Chow JC, Ruppert H, Zimmermann R (2012) Comparison of emissions from wood combustion. Part 1: emission factors and characteristics from different small-scale residential heating appliances considering particulate matter and Polycyclic aromatic hydrocarbon (PAH)-related toxicological potential of particle-bound organic species. Energy Fuels 26(11):6695–6704

    Article  Google Scholar 

  • Orasche J, Schnelle-Kreis J, Schön C, Hartmann H, Ruppert H, Arteaga-Salas JM, Zimmermann R (2013) Comparison of emissions from wood combustion, Part 2: Impact of combustion conditions on emission factors and characteristics of particle-bound organic species and polycyclic aromatic hydrocarbon (PAH)-related toxicological potential. Energy Fuels 27(3):1482–1491

    Article  Google Scholar 

  • Persson U, Münster M (2016) Current and future prospects for heat recovery from waste in European district heating systems: a literature and data review. Energy 110:116–128

    Article  Google Scholar 

  • Peters MS, Timmerhaus KD, West RE (2003) Plant design and economics for chemical engineers. McGraw-Hill chemical engineering series, 5th edn. McGraw-Hill, New York

    Google Scholar 

  • Rentizelas AA, Tatsiopoulos IP (2010) Locating a bioenergy facility using a hybrid optimization method. Int J Prod Econ 123(1):196–209

    Article  Google Scholar 

  • Reymond M (2012) Measuring vulnerability to shocks in the gas market in South America. Energy Policy 48:754–761

    Article  Google Scholar 

  • Rezaie B, Rosen MA (2012) District heating and cooling: review of technology and potential enhancements. Appl Energy 93:2–10

    Article  Google Scholar 

  • Rong A, Lahdelma R (2007) An effective heuristic for combined heat-and-power production planning with power ramp constraints. Appl Energy 84(3):307–325

    Article  Google Scholar 

  • Sartor K, Quoilin S, Dewallef P (2014) Simulation and optimization of a CHP biomass plant and district heating network. Appl Energy 130:474–483

    Article  Google Scholar 

  • Schollenberger H, Treitz M, Geldermann J (2008) Adapting the European approach of best available techniques: case studies from Chile and China. J Clean Prod 16(17):1856–1864

    Article  Google Scholar 

  • Schueftan A, González AD (2013) Reduction of firewood consumption by households in south-central Chile associated with energy efficiency programs. Energy Policy 63:823–832

    Article  Google Scholar 

  • Schueftan A, González AD (2015) Proposals to enhance thermal efficiency programs and air pollution control in south-central Chile. Energy Policy 79:48–57

    Article  Google Scholar 

  • Stanislawski D (1947) Early Spanish town planning in the new world. Geogr Rev 37(1):94

    Article  Google Scholar 

  • Steen D, Stadler M, Cardoso G, Groissböck M, DeForest N, Marnay C (2015) Modeling of thermal storage systems in MILP distributed energy resource models. Appl Energy 137:782–792

    Article  Google Scholar 

  • Sun Z, Li L, Bego A, Dababneh F (2015) Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system. Int J Prod Econ 165:112–119

    Article  Google Scholar 

  • Towler GP, Sinnott RK (2013) Chemical engineering design: Principles, practice, and economics of plant and process design, 2nd edn. Butterworth-Heinemann, Oxford, Waltham

    Google Scholar 

  • Uhlemair H, Karschin I, Geldermann J (2012) Optimizing the production and distribution system of bioenergy villages. Int J Prod Econ. https://doi.org/10.1016/j.ijpe.2012.10.003

    Google Scholar 

  • Umweltbundesamt (2014) Emission balance of renewable energy sources in(2013): an analysis by the German federal environment agency. UBA, Dessau-Roßlau

    Google Scholar 

  • Unidad de Desarollo Tecnologico (2013) Calefacción distrital con biomasa en Chile: Evaluación de prefactibilidad técnica, económica y social de proyectos piloto en Osorno. UTD, Ministerio de Engeria, Ministerio del Medio Ambiente, UDT, Concepcion (Chile)

  • Vine E (2005) An international survey of the energy service company (ESCO) industry. Energy Policy 33(5):691–704

    Article  Google Scholar 

  • Wakui T, Kawayoshi H, Yokoyama R, Aki H (2016) Operation management of residential energy-supplying networks based on optimization approaches. Appl Energy 183:340–357

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the German Research Foundation (DFG) for their financial support, as part of the Research Training Group (RTG) 1703 on “Resource Efficiency in Interorganizational Networks”.

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Authors and Affiliations

  1. Chair of Production and Logistics, University of Goettingen, Goettingen, Germany

    Ingo Karschin & Jutta Geldermann

  2. Unidad de Desarollo Tecnologico (UDT), University of Concepcion, Concepción, Chile

    Alex G. Berg

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  1. Ingo Karschin
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  3. Jutta Geldermann
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Correspondence to Jutta Geldermann.

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Karschin, I., Berg, A.G. & Geldermann, J. Development of a Network-location-model for the Economic Optimization of Local Heating Systems in Urban Chile. Z Energiewirtsch 42, 21–33 (2018). https://doi.org/10.1007/s12398-017-0216-9

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