Life Cycle Cost, often abbreviated as LCC, is a common tool for comparing the total cost of different alternatives, such as heating and cooling methods. Common heating and cooling methods in Sweden are geothermal energy, district heating and district cooling. This report aims to evaluate how different heating and cooling methods differ from each other while being applied on three different types of buildings, using selected LCC-models. Information about the selected LCC-models wasretrieved from each separate model and its website. Reports and agencies were used as sources for information about the heating and cooling methods. Tendersby established energy companies in Sweden were used as input data to form different alternatives for each building. From the comparison between the selected LCC-models, both similarities and differences were identified. The differences vary both in scale and how they affect the result. Nonetheless two of the models show the same results for some of the alternatives. In order to approximate the environmental effects for each heating and cooling method, carbon dioxide emissions were compared. The conclusion of this report is that while there are significant differences between the different LCC-models, the results only differ marginally for most models. / Life Cycle Cost, ofta förkortadsom LCC, är ett vanligt använt verktyg vid jämförelse av olika alternativs, exempelvis olika uppvärmnings- och kylmetoder, totala livscykelkostnad. I Sverige är vanliga uppvärmnings- och kylmetoder bergvärme, fjärrvärme och fjärrkyla. Denna rapport syftar till att med hjälp av utvalda LCC-modeller utvärdera hur dessa olika metoder skiljer sig för olika typfall, samt att redogöra för vilka skillnader det finns mellan de utvalda LCC-modellerna. De typfall som undersöktes var tre olika fastigheter med varierande storlek och alternativ. Information om de valda LCC-modellerna hämtades från respektive modell samt vid behov från tillhörande hemsida. Olika rapporter och myndigheter ligger till grund för information för hur de olika uppvärmnings- och kylmetoderna fungerar. Indata för LCC-beräkningarna inhämtades från offerter givna av etablerade energiföretag i Sverige. Genom rena jämförelser mellan de valda LCC-modellerna hittades både likheter och skillnader. Skillnadernas inverkan varierar i både grad och vilken effekt de har på resultaten. Däremot får två av modellerna samma resultat för vissa typfall. För att uppskatta miljöpåverkan jämfördes även typfallens koldioxidutsläpp för de olika uppvärmnings- och kylmetoderna. Slutsatser som kan dras från studien är att det finns klara skillnader mellan olika LCC- modeller, men resultaten skiljer sig ofta endast marginellt.

The Long-term changes in the climate conditions have increased the need foradequate thermal comfort systems. These alternations influence extremeevents, which their intensity and frequency have increased over the past years.Moreover, this study focuses on space cooling and parameters that the systemshould have to be considered as resilient. Literature study was done to presentthe concept of resilience as well as the different methods used to provide spacecooling. In addition, the cooling systems suggested in this study, which aredistrict cooling and absorption cooling, were presented and explained.Furthermore, the study focuses on cooling demand in a group of residentialbuildings based on different thermal characteristics, which were implementedbased on building regulations from late 1960s to early 1980s. The buildingthermal properties were used as input to obtain their cooling demand by usingbuilding energy simulation tool. Based on the acquired results, an evaluationhas been made for the cooling demand of those buildings. Further analysispresented a correlation between the cooling demand and thermal properties ofthe buildings and aided in the determination of the required cooling capacity.The selection of the capacities was based on the resilience criterion as the systemhas to be able to provide adequate performance and safety for the occupantsduring extreme events. Furthermore, an assessment was done to compare thesuggested system based on their capacities and the primary energy use.

Indiana University-Purdue University Indianapolis (IUPUI) / The internal and external interactions between the complex structural and behavioral characteristics of the system of interest and the surrounding environment result in unpredictable emergent behaviors. These emergent behaviors are not well understood, especially when modeled using the traditional top-down systems engineering approach. The intrinsic nature of current complex systems has called for an elegant solution that provides an integrated framework in Model-Based Systems Engineering. A considerable gap exists to integrate system engineering activities and engineering analysis, which results in high risk and cost. This thesis presents a framework that incorporates indefinite and definite modeling aspects that are developed to determine the complexity that arises during the development phases of the system. This framework provides a workflow for modeling complex systems using Systems Modeling Language (SysML) that captures the system’s requirements, behavior, structure, and analytical aspects at both problem definition and solution levels. This research introduces a new level/dimension to the framework to support engineering analysis integrated with the system architecture model using FMI standards. A workflow is provided that provides the enabling methodological capabilities. It starts with a statement of need and ends with system requirement verification. Detailed traceability is established that glues system engineering and engineering analysis together. Besides, a method is proposed for predicting the system’s complexity by calculating the complexity index that can be used to assess the complexity of the existing system and guide the design and development of a new system. To test and demonstrate this framework, a case study consisting of a complex district cooling system is implemented. The case study shows the framework’s capabilities in enabling the successful modeling of a complex district cooling system. The system architecture model was developed using SysML and the engineering analysis model using Modelica. The proposed framework supports system requirements verification activity. The analysis results show that the district chiller model developed using Modelica produces chilled water below 6.6 degrees Celsius, which satisfies the system requirement for the district chiller system captured in the SysML tool. Similarly, many such requirement verification capabilities using dynamic simulation integration with the high-level model provides the ability to perform continuous analysis and simulation during the system development process. The systems architecture complexity index is measured for the district cooling case study from the black-box and white box-perspective. The measured complexity index showed that the system architecture’s behavioral aspect increases exponentially compared to the structural aspect. The systems architecture’s complexity index at black-box and white-box was 4.998 and 67.3927, respectively.

The average global temperature is rising due to climate change. This leads to an increase in cooling demand along with higher usage of electricity to operate cooling processes. One way to decrease the electricity usage is to introduce absorption cooling which uses heat instead of electricity as its main source of power. To further increase resource efficiency in urban areas centralized district cooling can substitute independent cooling units. In a district cooling network, a mixture of absorption and compressor cooling units, as well as free cooling, can be included. This enables the ability to coordinate which cooling technology is to be used based on profitability at the current time. By introducing an optimization-based plan, the operation of a district cooling network in a smart energy system can incorporate important factors for the interaction between different sectors, such as electricity and district heating prices. The usage of optimization-based tools to plan the operation of energy systems has previously shown promising results. However, further studies are needed to investigate how they perform in different scenarios. There is also a need to develope more reliable forecasts which motivated this study; a case study on the district cooling network "City" in Linköping.  The study aimed to develope a method for forecasting the cooling demand in a district cooling network, investigating how the coordination of absorption and compressor cooling units, as well as free cooling, can be improved. This has been done from a system perspective that encompasses the district heating and electricity network by developing an optimization-based operational plan. In this study an explorative method has been used to develope a forecasting tool based on an algorithm and a Mixed Integer Linear Programming (MILP) model with appertaining constraints and coefficients which can solve an Unit Commitment problem for a district cooling network. The forecasting tool and MILP model resulted in an optimization-based operational plan that enabled the ability to coordinate the usage between absorption and compressor cooling units as well as free cooling. The method can be divided into five distinct iterative steps; (1) data collection for the parameters that affect the cooling demand, (2) forecasting of the cooling demand based on the identified parameters, (3) pressure simulations of Linköping's district cooling network in the software NetSim, (4) operational optimization via MILP modeling, and (5) evaluation of the optimization-based operational plan from the perspective of operational cost, electricity and heat usage, as well as greenhouse gas emissions. Six different algorithms were developed to forecast the cooling demand. All of the algorithms were based on the retrospective operation the previous day through linear regressions. The algorithm that best followed a historical operational period on the district cooling network City had a margin of error of 14\%. The algorithm was based on the time of the day and either solar irradiation or outside temperature based on the difference between the forecasted outdoor temperature and the measured temperature the previous day. The MILP model that was developed had an objective function that minimized the operational cost which included the cost of electricity and heat usage, distribution, maintenance, and start-up and shut-down costs. The constraints that was constructed in the MILP model to define a district cooling network included balancing the cooling demand, specifications for the operation of cooling units and distribution flows. Furthermore, the coefficients that defined the City network were estimated dynamically. These included power limitations, operational costs, and start-up costs for each cooling unit, as well as distribution costs for each cooling plant.  During this case-study, it was observed that by using optimization-based operational planning produced from a MILP model solving an UC problem, the operational costs, electricity and heat usage can decrease by 27\%, 22\%, and 2\% respectively for this case-study of the City network in Linköping during a seven-month period. In addition, a decrease in greenhouse gases by 16\% was observed when applying the perspective "avoided global emissions". For the calculations an emission factor of 702 $gram \, CO_2-eq/kWh_{el}$ and 130, 72, or 3 $gram \, CO_2-eq/kWh_{heat}$ depending on if waste, bio-oil, or recycled waste wood were used as fuel for the marginal production of district heating. When there was excess heat in the district heating network the emission factor for heat usage was instead assumed to be 0 $gram \, CO_2-eq/kWh_{heat}$. Lastly, this case-study emphasizes the importance of solid operational planning as a foundational pillar in satisfying the increase of future cooling demand in a resource-efficient way for local energy systems in sustainable societies.

District cooling supply is vital for service, commercial and industrial sectors like hospitals, data centers, supermarkets and sensitive laboratory facilities. The main cooling demand in the case of Sweden also originates from these sectors. The cooling demand in Stockholm is expanding mainly because of demand for comfort cooling, and data centers are rising. To cover the existing cooling demand and rising cooling demand, different cooling strategies have to be employed for optimal production of cold. This project concerns the optimization of such a district cooling system with primarily cold storage. This is achieved by choosing a case study network, namely considering the district cooling network of Norrenergi AB, in Sweden. Norrenergi AB is a company involved in supplying district cooling for cold consumers situated around Solna and Sundbyberg regions. The company provides around 70 GWh district cooling per year. The sources for the district cooling supply are free cooling, electrically driven chillers, and cold recovery from heat pumps. Besides these cold sources, currently, the parts of the peak cold demand are shaved using cold storage that is more cost-effectively charged during night-time, adopting the concept of power-to-cold. In running the district cooling system operation, Norrenergi AB’s current electricity mix is 100% renewable. In this thesis work, the existing district cooling network of Norrenergi AB is modeled using BoFiT optimization software (which is the base scenario), and then four future scenarios are developed, considering new, additional cold storages. The scenarios developed were meant to further optimize the existing district cooling grid to cater to the same existing total demand. This is assessed by integrating respective cold storages having larger (i.e., 15 MW capacity) or smaller (i.e., two cold storages each with 3 MW capacity) into the existing district cooling grid. The 15 MW capacity cold storage is integrated into Sundbybergsverket (Scenario 1) and in Frösundaverket (Scenario 2). While, from the smaller cold storages, the first one is integrated into the system in a manner that it supplies cooling for selected cooling customers, that is Scenario 3. The second small cold storage integrated in a way that supplies cooling to the entire grid, which is Scenario 4. Similar to the existing cold storage, in developed scenarios as well, the power-to-cold concept is utilized by charging the cold storage during the time in which the electricity price is lower (i.e., at night). The key outcome of this thesis work reveals that all the developed scenarios lead to cost savings in terms of the consumed electricity for producing DC. The achieved cost saving from each of the four scenarios developed are 23%, 4%, 13%, and 14%, respectively. Among all these scenarios, the first scenario has led to the largest cutback of DC production cost and impliesthat incorporating larger cold storages in cooling production plants results in higher savings. A performed sensitivity analysis also implies that increasing the supply capacity of free cooling results in production cost savings. Besides, an increased cooling capacity by 30% with respect to the base scenario results in a 10.6% cost saving. This saving infers that it is good to utilize free cooling as far as there is an opportunity to increase the use of free cooling. / Tillgången på kyla är i dag avgörande för service, kommersiella och industriella sektorer som sjukhus, serverhallar, kontor, stormarknader och känsliga laboratorieanläggningar. Den huvudsakliga efterfrågan på kyla i Sverige härstammar också från dessa sektorer. Kylbehovet i Stockholm expanderar främst på grund av efterfrågan på komfortkyla och serverhallar stiger. För att täcka det befintliga kylbehovet och den stigande efterfrågan på kyla, kan olika strategier användas för att uppnå en optimal production av kyla. Detta projekt handlar om optimering av ett fjärrkylsystem med kyllager. Detta har genomförts genom en fallstudie baserad på Norrenergis fjärrkylanät i Sverige. Norrenergi AB är ett företag som bl.a levererar fjärrkyla till kunder i Solna och Sundbyberg. Bolaget levererar cirka 70 GWh fjärrkyla per år, med hjälp av frikyla, kylmaskiner och värmepumpar. Förutom ovannämnda produktion används ett fjärrkyllager för att leverera fjärrkyla och jämna ut lasten över dygnet, och detta laddas när behovet av fjärrkyla är lägre. Elen som används för att producera Norrenergis fjärrkyla är helt förnybar. I detta examensarbete har Norrenergis befintliga fjärrkylanät modellerats med hjälp av BoFiT optimeringsprogram och sedan har fyra framtida scenarion utvecklats, med nya, distribuerade kyllager. De scenarierna som utvecklades var tänkta att ytterligare optimera det befintliga fjärrkylanätet, för att tillgodose samma befintliga totala efterfrågan. Detta bedöms genom att integrera kyllager av olika kapacitet i befintligt fjärrkylanät - ett större 15 MW lager eller två kyllager om vadera 3 MW kapacitet. Ett 15 MW fjärrkyllager integreras i Sundbybergsverket (scenario 1) och i Frösundaverket (scenario 2). De mindre fjärrkyllagren integreras i systemet så att kylning levereras till utvalda kunder (scenario 3). I scenario 4 integreras de mindre lagren så att kylning levereras till hela nätet. Precis som med det existerande kyllagret, ska dessa nya lager i de olika scenariona laddas under natten då elpriset är lägre, därav namnet kraftkyla. De viktigaste resultaten ur detta examensarbete visade att alla utvecklade scenarion ledde till kostnadsbesparingar med hänsyn till elförbrukningen. De uppnådda kostnadsbesparingarna från de fyra scenariona var 23%, 4%, 13% respektive 14%. Bland alla scenarier, leder det första scenariot den största besparingen av produktionskostnaden och medför att integrering av kyllager vid produktionsanläggningarna resulterar i högre besparingar. Den känslighetsanalys som genomfördes innebar också att en ökning av leveranskapaciteten för frikyla leder till besparingar i produktionskostnaderna. En ökad frikylkapacitet med 30% med avseende på basscenariot resulterade i 1% kostnadsbesparing. Denna kostnadsbesparing visar också att det är bra att använda frikyla så länge möjligheten finns att öka användandet av frikyla.

The building sector is a significant contributor to global greenhouse gas emissions, necessitating the development of energy-efficient measures to address environmental concerns. The availability of building energy data sets enables the application of data analysis techniques to assess building energy conditions, providing greater potential for evaluating building energy demands. This research centers on the evaluation of three distinct Campuses in Stockholm, including KTH, Frescati, and Solna buildings. The analysis encompasses two critical dimensions: the first related to energy performance certificates, while the second leverages data from the Akademiska Hus database. The information gathered from the Akademiska Hus database is obtained by using a web application developed at KTH Energy Technology, which was mainly available for internal usage. Examination of energy performance certificates reveals a crucial distinction among buildings concerning their energy utilization, construction year, and activity areas. Buildings categorized with energy performance levels E, F, and G emerge as critical areas demanding urgent evaluations. By inspecting data from the Akademiska Hus database, the study evaluates district heating, district cooling, and electricity variations in relation to outdoor temperature fluctuations during 2022. This analysis uncovers notable anomalies in buildings' energy demands. KTH and Solna buildings present abrupt district cooling and district heating variations, as well as high district cooling values during winter, and high district heating values during summer. While some Frescati and Solna buildings evidence constant district heating and district cooling values as an anomaly, along with high district cooling and district heating values during winter and summer periods, respectively. In conclusion, this study recommends in-depth assessments and the implementation of energyefficient measures for buildings classified with energy performance levels E, F, and G linked to large energy variation anomalies. The aim is to recognize the sources of these anomalies and enhance overall energy performance. Notably, KTH and Solna Campuses are identified as areas warranting immediate attention / Byggsektorn är en betydande bidragsgivare till globala utsläpp av växthusgaser, vilket kräver utveckling av energieffektiva åtgärder för att hantera miljöproblem. Tillgången till byggnadsenergidatauppsättningar möjliggör tillämpning av dataanalystekniker för att bedöma byggnaders energiförhållanden, vilket ger större potential för att utvärdera byggnaders energibehov. Denna forskning fokuserar på utvärdering av tre distinkta Campus i Stockholm, inklusive KTH, Frescati och Solna-byggnaderna. Analysen omfattar två kritiska dimensioner: den första avser energicertifikat, medan den andra utnyttjar data från Akademiska Hus energiplattform. Granskning av energicertifikat visar en avgörande skillnad mellan byggnader när det gäller deras energianvändning, ålder och verksamhetsområden. Byggnader kategoriserade med energiprestandanivåerna E, F och G framstår som kritiska områden som kräver brådskande utvärderingar. Genom att granska data från Akademiska Hus energiplattform utvärderar studien fjärrvärme-, fjärrkyla- och elvariationer i relation till utomhustemperaturfluktuationer under 2022. Denna analys avslöjar betydande anomalier i byggnaders energibehov. KTH och Solnas byggnader uppvisar abrupta fjärrkyla- och fjärrvärmevariationer, samt höga fjärrkylavärden under vinter noch höga fjärrvärmevärden under sommaren. Medan vissa Frescati- och Solna-byggnader visar konstanta fjärrvärme- och fjärrkylavärden som en anomali, tillsammans med höga fjärrkyla och fjärrvärmevärden under vinter- respektive sommarperioder. Sammanfattningsvis rekommenderar denna studie fördjupade bedömningar och genomförande av energieffektiva åtgärder för byggnader klassificerade med energiprestandanivåer E, F och G kopplade till stora energivariationer. Syftet är att lokalisera källorna till dessa anomalier och förbättra den övergripande energiprestanda. Noterbart är att Campus KTH och Solna har en framträdande plats som områden som kräver omedelbar uppmärksamhet.

Given the coinciding growth-trend in the production of consumer electronics and generation of data, the increase in server halls and data centers, as a means for hosting storage capacity for the generated data, has been prominent over the last decades. The establishment of data centers in already existing infrastructure can entail major changes in terms of energy system design. The activity of data processing and storage is power intensive and as the centers demonstrate substantial heat generation, one of the most important fractions of the energy use comes from the need to provide cooling. The study is a techno-economic analysis purposed for determining the feasibility of different cooling systems for a data center in Sweden. The investigated building currently hosts an industrial printing press hall in which paper printing has been conducted for the several decades. This press hall is subject to a refurbishment process to eventually be converted into a data center. In order to achieve the objectives, a data center building model is developed, designated for the estimation of the internal heat generation and demand for cooling. The design and energy requirements of a number of cooling solutions are then investigated and evaluated using a number of performance metrics: Power Usage Effectiveness (PUE), Capital Expenditure (CapEx), Operational Expenditure (OpEx) and Life Cycle Cost (LCC). More specifically the systems incorporate technologies for utilizing air-based free cooling, ground-source free cooling through borehole ground source heat exchangers (GHEs), mechanical cooling through compressor-driven machines as well as District Cooling (DC). The results of the study show that free cooling is a viable solution for covering the vast majority of the yearly cooling requirements, during sufficiently low outdoor temperatures. Free cooling, provided through borehole GHE’s, is feasible as a partial solution from a technical point of view, to provide cooling capacity during warmer periods. However, it can not alone act to provide a major part of the relatively high and constant cooling capacity requirements throughout the year. All of the investigated scenarios display a similar energy performance in terms of total PUE, at values well below the national average of 1.37. It is also seen, that the scenario that displays the lowest LCC includes a combination of free cooling and compressor-driven cooling. This holds for the studied sensitivity cases. It is found that a combined system incorporating borehole GHE’s and compressor cooling machines perform the best in terms of a low PUE. However, the relative difference in energy performance turns out to be lesser than the relative difference in LCC, when substituting the borehole GHE’s for additional cooling machine capacity. / I takt med digitaliseringen och en ökad global användningen- och produktionen av hemelektronik, vilket föranlett en ökad generering av data, har antalet datahallar blivit allt fler de senaste decennierna. Datahallens syfte är att hantera och bereda lagringskapacitet för den data som genereras vilket involverar en rad energikrävande processer. Upprättandet av datahallar i redan befintlig infrastruktur kan medföra förändringar när det kommer till utformningen av byggnadens energisystem. Att bedriva datalagring och informationsbehandling kräver påtagliga mängder elektricitet vilket medför stor intern värmealstring och därtill behov av aktiv kylning.  Denna studie, som valt att benämnas som en tekno-ekonomisk fallstudie, undersöker lämpligheten i implementeringen av olika kylsystem för ett byggnadskomplex i Stockholm. I byggnadens lokaler återfinns idag en industrihall där det sedan flera decennier bedrivits tryckeriverksamhet. Industrihallen är föremål för en konverteringsprocess för att på sikt bli en datahall. Studien är centrerad kring denna konverteringsprocess. För att utvärdera kylbehoven för den framtida datahallen har en modell utvecklats som uppskattar interna värmelaster samt reglerar inomhusklimatet efter rådande krav på inomhuskomfort. Därefter studeras utformning och energibehov för flera olika typer av kylsystemlösningar där en utvärdering av dessa system görs utifrån indikatorerna Power Usage Effectiveness (PUE), Capital Expenditure (CapEx),Operational Expenditure (OpEx) and Life Cycle Cost (LCC). Mer konkret undersöks kombinerade kylsystem som utnyttjar luftburen frikyla, geotermisk frikyla via bergvärmeväxlare (GHEs), mekanisk kyla via kompressordriven kylmaskin samt regional fjärrkyla. Resultaten från studien visar att frikyla från kylmedelskylare är en lämplig lösning för att täcka majoriteten av datahallens kylbehov över ett år, med undantag för årets varmare perioder. Geotermisk frikyla via borrhål är möjlig som partiell lösning ur ett tekniskt perspektiv, men kan inte enskild leverera en majoritet av effekt- eller energibehovet av kyla. Resultatet visar också att alla undersökta scenarier uppvisar en liknande energiprestanda i termer av total PUE, med värden som underskrider det nationella genomsnittet 1,37. Lägst LCC påvisades för ett system som kombinerar luftburen frikyla via kylmedleskylare och mekanisk kyla via kompressordrivna kylmaskiner. Denna låga LCC är signifikant vilket påvisas i utförd känslighetsanalys. Slutligen konstateras att ett system innefattande luftburen och geotermisk frikyla i kombination med kompressordrivna kylmaskiner resulterar i lägst PUE bland de undersökta scenarierna. Den relativa skillnaden i energiprestanda visar sig vara mindre än den relativa skillnaden i LCC, när geotermisk frikyla ersätts med ytterligare kapacitet från kylmaskiner.

Fernkälte bietet das Potenzial, wirtschaftlich und ökologisch vorteilhaft zur Deckung des stetig zunehmenden Klimakältebedarfs beizutragen. Im Rahmen dieser Arbeit wurde ein dynamisches thermohydraulisches Netzmodell „ISENA“ entwickelt, mit dem während der Planung und des Betriebs von Fernkältesystemen auftretende Fragen, beispielsweise in Bezug auf Wirtschaftlichkeit und Energieeffizienz, beantwortet werden können. Das Netzmodell setzt sich aus einem quasistationären hydraulischen Modell und einem instationären thermischen Modell zusammen, das auf der Verfolgung von Wasserpfropfen durch das gesamte Netz basiert (Lagrange-Ansatz). Mit diesem Modellierungsansatz können numerische Fehler sowie Bilanzungenauigkeiten vermieden werden, sodass sich eine höhere Ergebnisgüte im Vergleich zu bisher bekannten Netzmodellen erreichen lässt. Ebenfalls neu entwickelt wurde das Teilmodell zur Abbildung der Wärmeströme über die Wände unterirdischer Rohrpaare (Kälteverluste und -gewinne). Dieses Modell erlaubt die Bestimmung der instationären Rohrwand-Wärmeströme für wärmegedämmte unterirdische Rohrpaare, Rohrpaare mit gedämmtem Vor- und ungedämmtem Rücklauf sowie ungedämmte Rohrpaare. Anhand von Validierungs- und Verifikationsrechnungen wird gezeigt, dass ISENA verlässliche Ergebnisse liefert und für die praktische Anwendung geeignet ist. Abschließende Beispielrechnungen geben einen Einblick in die Untersuchungsmöglichkeiten, die das neue Modell bietet – unter anderem im Hinblick auf den Vergleich von Pumpenregelungsvarianten, den Einfluss von Rohrdämmung und Erdreicheigenschaften auf Kälteverluste und -gewinne sowie die Einbindung von Hochtemperatur-Kälteverbrauchern in den Netzrücklauf. / District cooling can provide economic and ecological benefits while supplying the increasing cooling demand for air conditioning. In the present thesis, a dynamic thermo-hydraulic model “ISENA” is presented which may be used in order to answer questions arising during design and operation of district cooling networks—e. g., that are related to economic and energy efficiency. The network model consists of a quasi-static hydraulic module and a transient thermal module being based on the tracking of water segments through the entire network (Lagrangian method). With this approach, numerical errors and inaccuracies in the balance of conserved quantities could be avoided, which eventually leads to a better reliability of the results as compared to that obtained from other network models. Additionally, a new sub-model has been developed for predicting the transient heat flux through the walls of buried pipes in order to model thermal gains and losses. This model covers un-insulated, insulated and combinations of insulated as well as un-insulated pipes. Calculations performed for the purpose of validation and verification are presented in order to demonstrate that ISENA provides reliable results and hence is suitable for practical applications. Finally, example simulations show the various possibilities provided by the new model—for example, concerning the comparison of different strategies for pump control, the influence of pipe insulation and soil properties on thermal gains and losses as well as the connection of buildings equipped with high temperature cooling systems to the return line of the network.

Energy consumption rates have been dramatically increasing on a global scale within the last few decades. A significant role in this increase is subjected by the recent high temperature levels especially at summer time which caused a rapid increase in the air conditioning demands. Such phenomena can be clearly observed in developing countries, especially those in hot climate regions, where people depend mainly on conventional air conditioning systems. These systems often show poor performance and thus negatively impact the environment which in turn contributes to global warming phenomena. In recent years, the demand for urban or district cooling technologies and networks has been increasing significantly as an alternative to conventional systems due to their higher efficiency and improved ecological impact. However, to obtain an efficient design for district cooling systems is a complex task that requires considering a wide range of cooling technologies, various network layout configuration possibilities, and several energy resources to be integrated. Thus, critical decisions have to be made regarding a variety of opportunities, options and technologies. The main objective of this thesis is to develop a tool to obtain preliminary design configurations and operation patterns for district cooling energy systems by performing roughly detailed optimizations and further, to introduce a decision-making approach to help decision makers in evaluating the economic aspects and environmental performance of urban cooling systems at an early design stage. Different aspects of the subject have been investigated in the literature by several researchers. A brief survey of the state of the art was carried out and revealed that mathematical programming models were the most common and successful technique for configuring and designing cooling systems for urban areas. As an outcome of the survey, multi objective optimization models were decided to be utilized to support the decision-making process. Hence, a multi objective optimization model has been developed to address the complicated issue of decision-making when designing a cooling system for an urban area or district. The model aims to optimize several elements of a cooling system such as: cooling network, cooling technologies, capacity and location of system equipment. In addition, various energy resources have been taken into consideration as well as different solar technologies such as: trough solar concentrators, vacuum solar collectors and PV panels. The model was developed based on the mixed integer linear programming method (MILP) and implemented using GAMS language. Two case studies were investigated using the developed model. The first case study consists of seven buildings representing a residential district while the second case study was a university campus district dominated by non-residential buildings. The study was carried out for several groups of scenarios investigating certain design parameters and operation conditions such as: Available area, production plant location, cold storage location constraints, piping prices, investment cost, constant and variable electricity tariffs, solar energy integration policy, waste heat availability, load shifting strategies, and the effect of outdoor temperature in hot regions on the district cooling system performance. The investigation consisted of three stages, with total annual cost and CO2 emissions being the first and second single objective optimization stages. The third stage was a multi objective optimization combining the earlier two single objectives. Later on, non-dominated solutions, i.e. Pareto solutions, were generated by obtaining several multi objective optimization scenarios based on the decision-makers’ preferences. Eventually, a decision-making approach was developed to help decision-makers in selecting a specific solution that best fits the designers’ or decision makers’ desires, based on the difference between the Utopia and Nadir values, i.e. total annual cost and CO2 emissions obtained at the single optimization stages. / Die Energieverbrauchsraten haben in den letzten Jahrzehnten auf globaler Ebene dramatisch zugenommen. Diese Erhöhung ist zu einem großen Teil in den jüngst hohen Temperaturniveaus, vor allem in der Sommerzeit, begründet, die einen starken Anstieg der Nachfrage nach Klimaanlagen verursachen. Solche Ereignisse sind deutlich in Entwicklungsländern zu beobachten, vor allem in heißen Klimaregionen, wo Menschen vor allem konventionelle Klimaanlagensysteme benutzen. Diese Systeme verfügen meist über eine ineffiziente Leistungsfähigkeit und wirken sich somit negativ auf die Umwelt aus, was wiederum zur globalen Erwärmung beiträgt. In den letzten Jahren ist die Nachfrage nach Stadt- oder Fernkältetechnologien und -Netzwerken als Alternative zu konventionellen Systemen aufgrund ihrer höheren Effizienz und besseren ökologischen Verträglichkeit satrk gestiegen. Ein effizientes Design für Fernkühlsysteme zu erhalten, ist allerdings eine komplexe Aufgabe, die die Integration einer breite Palette von Kühltechnologien, verschiedener Konfigurationsmöglichkeiten von Netzwerk-Layouts und unterschiedlicher Energiequellen erfordert. Hierfür ist das Treffen kritischer Entscheidungen hinsichtlich einer Vielzahl von Möglichkeiten, Optionen und Technologien unabdingbar. Das Hauptziel dieser Arbeit ist es, ein Werkzeug zu entwickeln, das vorläufige Design-Konfigurationen und Betriebsmuster für Fernkälteenergiesysteme liefert, indem aureichend detaillierte Optimierungen durchgeführt werden. Zudem soll auch ein Ansatz zur Entscheidungsfindung vorgestellt werden, der Entscheidungsträger in einem frühen Planungsstadium bei der Bewertung städtischer Kühlungssysteme hinsichtlich der wirtschaftlichen Aspekte und Umweltleistung unterstützen soll. Unterschiedliche Aspekte dieser Problemstellung wurden in der Literatur von verschiedenen Forschern untersucht. Eine kurze Analyse des derzeitigen Stands der Technik ergab, dass mathematische Programmiermodelle die am weitesten verbreitete und erfolgreichste Methode für die Konfiguration und Gestaltung von Kühlsystemen für städtische Gebiete sind. Ein weiteres Ergebnis der Analyse war die Festlegung von Mehrzieloptimierungs-Modelles für die Unterstützung des Entscheidungsprozesses. Darauf basierend wurde im Rahmen der vorliegenden Arbeit ein Mehrzieloptimierungs-Modell für die Lösung des komplexen Entscheidungsfindungsprozesses bei der Gestaltung eines Kühlsystems für ein Stadtgebiet oder einen Bezirk entwickelt. Das Modell zielt darauf ab, mehrere Elemente des Kühlsystems zu optimieren, wie beispielsweise Kühlnetzwerke, Kühltechnologien sowie Kapazität und Lage der Systemtechnik. Zusätzlich werden verschiedene Energiequellen, auch solare wie Solarkonzentratoren, Vakuum-Solarkollektoren und PV-Module, berücksichtigt. Das Modell wurde auf Basis der gemischt-ganzzahlig linearen Optimierung (MILP) entwickelt und in GAMS Sprache implementiert. Zwei Fallstudien wurden mit dem entwickelten Modell untersucht. Die erste Fallstudie besteht aus sieben Gebäuden, die ein Wohnviertel darstellen, während die zweite Fallstudie einen Universitätscampus dominiert von Nichtwohngebäuden repräsentiert. Die Untersuchung wurde für mehrere Gruppen von Szenarien durchgeführt, wobei bestimmte Designparameter und Betriebsbedingungen überprüft werden, wie zum Beispiel die zur Verfügung stehende Fläche, Lage der Kühlanlage, örtliche Restriktionen der Kältespeicherung, Rohrpreise, Investitionskosten, konstante und variable Stromtarife, Strategie zur Einbindung der Solarenergie, Verfügbarkeit von Abwärme, Strategien der Lastenverschiebung, und die Wirkung der Außentemperatur in heißen Regionen auf die Leistung des Kühlsystems. Die Untersuchung bestand aus drei Stufen, wobei die jährlichen Gesamtkosten und die CO2-Emissionen die erste und zweite Einzelzieloptimierungsstufe darstellen. Die dritte Stufe war ein Pareto-Optimierung, die die beiden ersten Ziele kombiniert. Im Anschluss wurden nicht-dominante Lösungen, also Pareto-Lösungen, erzeugt, indem mehrere Pareto-Optimierungs-Szenarien basierend auf den Präferenzen der Entscheidungsträger abgebildet wurden. Schließlich wurde ein Ansatz zur Entscheidungsfindung entwickelt, um Entscheidungsträger bei der Auswahl einer bestimmten Lösung zu unterstützen, die am besten den Präferenzen des Planers oder des Entscheidungsträgers enstpricht, basierend auf der Differenz der Utopia und Nadir Werte, d.h. der jährlichen Gesamtkosten und CO2-Emissionen, die Ergebnis der einzelnen Optimierungsstufen sind.

La maîtrise de la demande en climatisation des bâtiments tertiaires peut contribuer à la limitation du réchauffement climatique à 2°C. Les réseaux de froid urbain sont une solution pour répondre à cette demande avec une haute efficacité énergétique. Une conduite performante est cependant essentielle pour maintenir et augmenter leurs avantages compétitifs. L'objectif de la thèse est de contribuer à la construction d'un outil d'aide à la conduite journalière des réseaux de froid. La difficulté réside à deux niveaux : la diversité des décisions et la complexité des phénomènes physiques sous-jacents. L'originalité est de proposer une méthodologie pour aider au pilotage des groupes frigorifiques, des tours aéroréfrigérantes, de la pression différentielle et de la répartition de puissance entre des centrales de production aux performances variables. La méthodologie développée est appliquée au réseau de froid de Paris-Bercy exploité par Climespace. Tout d'abord, un modèle intégrant une représentation physique des centrales de production, du réseau de distribution et des sous-stations, est développé. En particulier, un modèle de type semi-empirique, paramétrable sur des mesures, est modifié pour calculer les performances non-nominales des groupes frigorifiques centrifuges. La validation du modèle complet est réalisée sur un jeu de données indépendant de l'identification. Ensuite, le modèle est exploité pour rechercher une conduite optimisée à partir d'un modèle de prévision de la demande. La méthode proposée est séquentielle : résolution a priori des optimisations locales puis génération de modèles quadratiques de centrales servant à déterminer la répartition optimale. La pression différentielle est minimisée à partir de l'identification, par simulation, de la sous-station défavorisée. Enfin, la réduction de la consommation électrique est évaluée sur une semaine d'été. / Cooling demand management of commercial buildings can contribute to limit global warming below 2°C. District cooling is an energy-efficient option. However, improving operational performance is of great importance to ensure and increase its competitive advantages. The aim of this thesis is to contribute to the development of a decision-support tool for daily operation of district cooling networks. Challenges lie at two levels: diversity of decisions to be taken and complexity of physical phenomena involved. The original aspect of our work is to propose a methodology to improve chillers and cooling towers control, differential pressure management and dispatching between production plants with variable efficiency. Our developments are applied to the district cooling of Paris-Bercy, operated by Climespace. First; a model featuring a physical description of chilled-water production plants, distribution network and buildings substations, is developed. In particular, a semi-empirical model with identified parameters is modified to compute non-nominal characteristics of centrifugal chillers. The system model is validated against an independent dataset. Then, the model is used to find optimized controls from cooling loads forecast. The proposed methodology is sequential: pre-computation of optimal set-points at plant level and then generation of quadratic plant models to solve the dispatching optimization problem at each time step. Differential pressure is minimized with a simulation-based tracking of the critical substation. To conclude, electricity consumption reduction with optimized controls is evaluated during a summer week.