Das Ziel dieses Projektes ist, die bestehende tägliche Produktionsablaufplanung in der Handgalvanik bei dem Lohngalvanikbetrieb C. Jentner GmbH mit Hilfe eines mathematischen Modells zu optimie-ren. Hierfür wurde das Flexible-Job-Shop-Modell von Ziaee ([1], S. 91-95) ausgewählt und auf die Gegebenheiten vor Ort angepasst. Es gehört zu den MILP-Problemen (mixed integer linear programming- gemischt ganzzahlige Programmierung). Bei der Verwendung des Modells für die Praxis stellt die Modellgröße, die benötigt wird, um die Vorgänge in der Produktion ausreichend abbilden zu können, ein Problem dar. Diese führt zu langen Lösungszeiten, die für den täglichen Einsatz in der Produktionsablaufplanung ungeeignet sind. Zur Lösung dieses Problems wurde ein problemspezifisches Verfahren basierend auf Aggregations- und Dekompositionstechniken entwickelt. Durch Anwendung dieses Verfahrens kann die Problemgröße für den Solver klein und so die Lösungszeit in einem für die tägliche Produktionsablaufplanung annehmbaren Rahmen gehalten werden.

With a fast-growing electricity demand and a larger proportion of intermittent energy sources follows a greater need for flexible and balancing sources of electricity, such as hydropower. Planning of hydropower production is considered to be a difficult problem to solve due to several nonlinearities, combinatorial properties and the fact that it is a large scale system with spatial-temporal coupling. Optimization approaches are used for solving such problems and a common simplification is to disregard the effect of head variation on the power output. This thesis presents two methods for modeling the head dependency in optimization models for hydropower river systems, the Triangulation method and the Bilinear method. The Triangulation method implements a three-dimensional interpolation technique called triangulation, using a MILP formulation. This is a commonly used method found in the literature. The Bilinear method is a novel approach that applies a piecewise bilinear approximation of the power production function, resulting in a BLP problem. Also, a strategy for selecting which hydropower stations to include head dependence for is provided. The performance of the methods was evaluated on authentic test cases from Lule River and compared to results obtained by Vattenfall's current model without head dependency. The Triangulation method and the Bilinear method give higher accuracy, and are therefore considered more realistic, than the current model. Further, the results indicate that it is sufficient to include head dependence for a subset of stations since the error is significantly reduced. Mid- to long-term scenarios were solved with high accuracy when a subset of the stations was modeled as head dependent. Overall, the Bilinear method had a significantly shorter computational time than the Triangulation method.

PLAS is a cloud-based software used for planning and scheduling fleets of vehicles for material transport. PLAS consists of two components; the Logistic Flow Solver (LFS) and the Material Transport Scheduler (MTS). Based on transportation requests, the LFS generates a set of logistic flows. The MTS then transforms the logistic flows into tasks that are assigned to the vehicles. The LFS is implemented with Mixed Integer Linear Programming (MILP). Currently, the LFS and the MTS are decoupled from each other and there is information that is not considered in the LFS. Thus, the choice of logistic flows generated with the current formulation may negatively impact the final transport plan. The objective of this thesis is to investigate how the generation of logistic flows can be improved. Two alternative mathematical models for the LFS were developed using MILP formulation. Compared to the current model, more information is taken into account in the two new models. Three different objective functions were considered. Scheduling of the vehicles were modelled as pickup and delivery problems, where pickup and delivery pairs correspond to the generated logistic flows. The models were implemented using Google OR-Tools, an open-source software suite for optimization. The different mathematical formulations were evaluated based on their performance for test problems with different fleet compositions. The results show that problem characteristics influence the performance of the models and that there is no model that gives the best result for every type of problem. Therefore, it is necessary to analyse problem characteristics in order to choose a suitable model for generation of logistic flows. / PLAS är en molnbaserad mjukvara som används för planering och schemaläggning av fordonsflottor för materialtransport. PLAS består av två komponenter; Logistic Flow Solver (LFS) and Material Transport Scheduler (MTS). Baserat på transportbehov genererar LFS ett antal logistikflöden. MTS omvandlar sedan logistikflödena till uppdrag som är tilldelade till fordonen. LFS är implementerad med blandad heltalsprogrammering. För närvarande är LFS och MTS frikopplade från varandra och det finns information som inte tas hänsyn till i LFS. Därför kan valet av logistikflöden genererade med den nuvarande formuleringen negativt påverka den slutliga transportplanen. Målet med detta examensarbete är att undersöka hur genereringen av logistikflöden kan förbättras. Två alternativa matematiska modeller utvecklades med MILP-formulering. Jämfört med den nuvarande modellen, tar de två nya modellerna hänsyn till mer information. Tre olika målfunktioner beaktades. Modellerna implementerades med Google OR-Tools, en öppen programvara för optimering. De matematiska formuleringarna utvärderades baserat på deras prestation på testproblem med olika kompositioner av fordonsflottor. Resultaten visar att problemegenskaper påverkar modellernas prestationer och att det inte finns någon modell som ger bäst resultat för varje problemtyp. Därför är det nödvändigt att analysera problemegenskaper för att kunna välja en lämplig modell för generering av logistikflöden.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24938号 / 情博第849号 / 新制||情||142(附属図書館) / 京都大学大学院情報学研究科数理工学専攻 / (主査)准教授 原口 和也, 教授 山下 信雄, 教授 阿久津 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

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The United States is facing a rising average age of principal farm operators and a decline in number of beginning farmers. With numerous barriers and challenges resulting in many farm failures, a majority of beginning farmers are relying on off-farm income to support their households. Decision-making and farm business planning are difficult skills to develop and improve, and the ability to develop a plan to balance on- and off-farm labor could allow farmers to make more profitable decisions. In this study, a General Algebraic Modeling System (GAMS) is used to develop a labor management planning framework for use by Virginia's beginning vegetable farmers or service providers, such as extension agents, with the goal of improving total (on- and off-farm) profitability and farm viability. Study findings suggest that a willingness to work of 12 hours per day, 365 days per year and hired labor costs of $9.30 per hour, which is the national average for agricultural workers encourage a farmer to maintain an off-farm job, while a relatively lower off-farm wage or salary may encourage a farmer to work on the farm only. Lastly, higher hired labor costs may encourage a farmer to pursue his or her most profitable work opportunity, be it on- or off-farm, without hiring labor to maintain the farm. The model developed in this study may be used to plan multiple years of farm management to include anticipated changes in off-farm employment opportunities, land availability, product mix, and access to farm labor. The author suggests that beginning farmers who use this planning tool are able to make more informed decisions related to allocation of labor time and resources, resulting in lower failure rates for beginning farmers in Virginia. A user-friendly interface may be developed based on the study framework, to strengthen the results and increase the practicality of the tool. / Master of Science

The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress on the local voltage control devices. These challenges demand a well-coordinated and power network-aware charging approach for PEVs in a community. This paper formulates a realtime electric vehicle charging scheduling problem as a mixed-integer linear program (MILP). The problem is to be solved by an aggregator that provides charging services in a residential community. The proposed formulation maximizes the profit of the aggregator, enhancing the utilization of available infrastructure. With prior knowledge of load demand and hourly electricity prices, the algorithm uses a moving time horizon optimization approach, allowing an unknown number of arriving vehicles. In this realistic setting, the proposed framework ensures that power system constraints are satisfied and guarantees the desired PEV charging level within the stipulated time. Numerical tests on an IEEE 13-node feeder system demonstrate the computational and performance superiority of the proposed MILP technique. / M.S. / There is an enhanced rate of global warming due to emissions and increased usage of fossil fuels in the transportation sector. As a feasible solution, electrification of transportation has become a necessary step towards an environment-friendly future. The escalation in plug-in electric vehicles (PEVs) has increased the impact on loading and voltage fluctuations in the distribution grid due to uncoordinated charging. This puts on extra stress on the grid system and compromises the system performance. As a measure to control the vehicle charging in a residential setup, a real-time optimal charging scheduling algorithm is developed which is implemented at the neighborhood level. To increase the charging performance with the limited available resources, an aggregator is introduced. The charging profit is maximized as the PEV charging problem is solved optimally by the aggregator. This facilitates the reduction in night-time grid congestion and maximization of number of PEVs getting charged with limited dependency on communication to avoid long delays in charging control. The proposed technique guarantees the complete charging of the selected PEVs in the stipulated time while considering the power grid operational constraints. It also reduces the impact of peak load demand by flattening the base load demand curve. To demonstrate the efficiency of the proposed mixed integer linear programming optimization algorithm, numerical tests for an IEEE 13 node feeder are performed. The results are discussed to give an outlook on the balance between system and user requirements by meeting the demand of the PEV users.

A payment is the most fundamental aspect of a trade that involves funds. In recent years, the development of new payment services has accelerated significantly as the world has moved further into the digital era. This transition has led to an increased demand of digital payment solutions that can handle trades across the world. As trades today can be agreed at any time wherever the payer and payee are located, the party that mediates payments must at any time to be available in order to mediate an agreed exchange. This requires the payment service provider to always have funds available in the required countries and currencies in order for trades to always be available. This thesis concerns how a payment service provider can reallocate capital in a cost efficient way in order for trades to always be available. Traditionally, the reallocation of capital is done in a rule-based manner, which discard the cost dimension and thereby only focus on the reallocation itself. This thesis concerns methods to optimally reallocate capital focusing on the cost of transferring capital within the network. Where the concerned methods has the potential of transferring capital in a far more cost efficient way. When mathematically formulating the reallocation decisions as an optimization problem, the cost function is formulated as a linear program with both Boolean and real constraints. This impose non-feasibility of locating the optimal solution using traditional methods for linear programs, why developed traditional and more advanced methods were used. The model was evaluated based on a large number of simulations in comparison with the performance of a rule-based reallocation system. The developed model provides a significant cost reduction compared to the rule-based approach and thereby outperforms the traditional reallocation system. Future work should focus on expanding the model by broadening the available transfer options, by increasing the considered uncertainty via a bayesian treatment and finally by considering all cost aspects of the network. / En betalning är den mest fundamentala aspekten av handel som involverar kapital. De senaste åren har utvecklingen av nya betalmedel ökat drastiskt då världen fortsatt att utvecklas genom digitaliseringen. Utvecklingen har lett till en ökad efterfrågan på digitala betalningslösningar som kan hantera handel över hela världen. Då handel idag kan ske när som helst oberoende av var betalaren och betalningsmottagaren befinner sig, måste systemet som genomför betalningen alltid vara tillgängligt för att kunna förmedla handel mellan olika parter. Detta kräver att betalningssystemet alltid måste ha medel tillgängligt i efterfrågade länder och valutor för att handeln ska kunna genomföras. Den här uppsatsen fokuserar på hur kapital kostnadseffektivt kan omallokeras i ett betalsystem för att säkerställa att handel alltid är tillgängligt. Traditionellt har omallokeringen av kapital gjorts på ett regelbaserat sätt, vilket inte tagit hänsyn till kostnadsdimensionen och därigenom enbart fokuserat på själva omallokeringen. Den här uppsatsen använder metoder för att optimalt omallokera kapital baserat på kostnaderna för omallokeringen. Därigenom skapas en möjlighet att flytta kapital på ett avsevärt mer kostnadseffektivt sätt. När omallokeringsbesluten formuleras matematiskt som ett optimeringsproblem är kostnadsfunktionen formulerad som ett linjärt program med både Booleska och reella begränsningar av variablerna. Detta gör att traditionella lösningsmetoder för linjära program inte är användningsbara för att finna den optimala lösningen, varför vidareutveckling av tradtionella metoder tillsammans med mer avancerade metoder använts. Modellen utvärderades baserat på ett stort antal simuleringar som jämförde dess prestanda med det regelbaserade systemet. Den utvecklade modellen presterar en signfikant kostnadsreduktion i jämförelse med det regelbaserade systemet och överträffar därigenom det traditionellt använda systemet. Framtida arbete bör fokusera på att expandera modellen genom att utöka de potentiella överföringsmöjligheterna, att ta ökad hänsyn till osäkerhet genom en bayesiansk hantering, samt slutligen att integrera samtliga kostnadsaspekter i nätverket.

The energy transition taking place in various parts of the world will have many effects on the current energy systems as an increasing amount of intermittent power supply gets installed every year. In Sweden, just as many other countries, this will cause both challenges and opportunities for today´s energy producers. Challenges that may arise along with an increasingly fluctuating electricity production include both power deficits at certain times and regions but also hours of over-production which can cause electricity prices to drop significantly. Such challenges will have to be met by both dispatchable power generation and dynamic consumption. Conversely, actors prepared to adapt to the new climate by implementing new technologies or innovative business models could benefit from the transition towards a fully renewable energy system.  This thesis evaluates the techno-economic potential of green hydrogen production at a combined heat and power plant with the objective to provide decision support to a district heat and electricity producer in Sweden. It was in the company’s interest to investigate how hydrogen production could help reduce the production cost of district heat as well as contribute to the reduction of greenhouse gases.  In the project, two separate business models: Power-to-gas and Power-to-power were evaluated on the basis of technical and economic performance and environmental impact. To do this, a mathematical model of the CHP plant and the hydrogen systems was developed in Python which optimizes the operation based on costs. The business models were then simulated for two different years with each year representing a distinctly different electricity market situation.  The main conclusions of the study show that Power-to-gas could already be profitable at a hydrogen retail price of 40 SEK per kg, which is the projected retail price for the transportation sector. The demand today is however limited but is expected to grow fast in the near future, especially within heavy transportation. Another limiting factor for hydrogen production showed to be the availability of storage space, as hydrogen gas even at pressures up to 200 bar require large volumes.  Power-to-power for frequency regulation was found to not be economically justifiable as the revenue for providing grid services could not outweigh the high investment costs for any of the simulated years. This resulted in a high levelized cost of energy at over 3000 SEK per MWh which was mostly due to the low capacity factor of the power-to-power system.  Finally, green hydrogen has the potential of replacing fossil fuels in sectors that is difficult to reach with electricity, for example long-haul road transport or the shipping industry. Therefore, green hydrogen production in large scale could help decarbonize many of society’s fossil-heavy segments. By also serving as a grid-balancer, hydrogen production in a power-to-gas process has the potential of becoming an important part of a renewable energy system. / Energiomställningen som äger rum i olika delar av världen kommer att ha många effekter på de nuvarande energisystemen eftersom en ökande mängd väderberoende kraftproduktion installeras varje år. I Sverige, precis som många andra länder, kommer detta att medföra både utmaningar och möjligheter för dagens energiproducenter. Utmaningar som kan uppstå tillsammans med en alltmer fluktuerande elproduktion inkluderar både kraftunderskott vid vissa tider och regioner men också timmar av överproduktion som kan få elpriserna att sjunka avsevärt. Sådana utmaningar måste mötas av både planerbar kraftproduktion och dynamisk konsumtion. Omvänt kan aktörer som är beredda att anpassa sig till det nya klimatet genom att implementera ny teknik eller innovativa affärsmodeller dra nytta av övergången till ett helt förnybart energisystem.  Denna rapport utvärderar den tekno-ekonomiska potentialen för produktion av grön vätgas vid ett kraftvärmeverk med målet att ge beslutsstöd till en fjärrvärme- och elproducent i Sverige. Det var i företagets intresse att undersöka hur vätgasproduktion kan bidra till att sänka produktionskostnaden för fjärrvärme samt bidra till att minska växthusgaser.  I projektet utvärderades två separata affärsmodeller: Power-to-gas och Power-to-power baserat på teknisk och ekonomisk prestanda samt miljöpåverkan. För att kunna göra detta utvecklades en matematisk modell i Python av kraftvärmeverket och vätgassystemen som optimerar driften baserat på kostnader. Affärsmodellerna simulerades sedan för två olika års elpriser för att undersöka modellens prestanda i olika typer av elmarknader.  De viktigaste slutsatserna i studien visar att Power-to-gas redan kan vara lönsamt till ett vätgaspris på 40 SEK per kg, vilket är det förväntade marknadspriset på grön vätgas for transportsektorn. Efterfrågan är idag begränsad men förväntas växa snabbt inom en snar framtid, särskilt inom tung transport. En annan begränsande faktor för vätgasproduktion visade sig vara tillgången på lagringsutrymme, eftersom vätgas även vid tryck upp till 200 bar kräver stora volymer.  Power-to-power för frekvensreglering visade sig inte vara ekonomiskt försvarbart, eftersom intäkterna för att tillhandahålla nättjänster inte kunde uppväga de höga investeringskostnaderna under några av de simulerade åren. Detta resulterade i en hög LCOE på över 3000 SEK per MWh, vilket främst berodde på Power-to-power-systemets låga utnyttjandegrad.  Slutligen kan det sägas att grön vätgas har stor potential att ersätta fossila bränslen i sektorer som är svåra att elektrifiera, exempelvis tunga vägtransporter eller sjöfart. Därför kan storskalig grön vätgasproduktion hjälpa till att dekarbonisera många av samhällets fossiltunga segment. Genom att dessutom fungera som balansering har väteproduktion i en Power-to-gas-process potential att bli en viktig del av ett system med stor andel förnybar energi.