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.

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.

Due to the increase in electrical demand and renewable penetration, electrical utilities need to improve and optimize the grid infrastructure. Fundamental components in this grid infrastructure are transformers, which are designed conservatively on the base of a static rated power. However, load and weather change continuously and hence, transformers are not used in the most efficient way. For this reason a new technology has been developed: Dynamic transformer rating (DTR). By applying DTR, it is possible to load transformers above the nameplate rating without affecting their life time expectancy. This project goes one step further and uses DTR for the short term and long term wind farm planning. The optimal wind farm is designed by applying DTR to the power transformer of the farm. The optimization is carried out using a Mixed-Integer Linear Programming (MILP) model. In respect of the transformer thermal analysis, the linearized top oil model of IEEE Clause 7 is selected. The model is executed for 4 different types of power transformers: 63 MVA, 100 MVA, 200 MVA and 400 MVA. As result, it is obtained that the net present value for the investment and the capacity of the wind farm increase linearly with respect to the size of the transformer. Then, a sensitivity analysis is carried out by modifying the wind speed, the electricity price, the lifetime of the transformer and the selected weather data. From this sensitivity analysis, it is possible to conclude that wind resources and electricity price are key parameters for the feasibility of the wind farm. / På grund av ökningen av efterfrågan av elektricitet och förnybara energin, elförsörgingsföretag måste förbättras och elnätets infrastruktur måste optimeras. Grundläggande komponenter i elnätet är transformatorer, som är designade konservativt efter en statisk märkeffekt. Laster och vädret ändras dock kontinuerligt, detta betyder att transformatorer inte används på de mest effektiva sätten. Av denna anledning har en ny teknik utvecklats: Dynamisk lastbarhet hos transformatorer (DTR). Genom att applicera DTR, gör det möjligt att belasta en transformator högre än märkdata utan att påverka den förväntade livslängden. Detta projekt går ett steg längre och använder DTR för kort och lång sikts vindkraftparkplaneringar. Den optimala vindkraftparken är designad genom att använda DLT på krafttransformatorn för vindkraftsparken. Optimeringen utförst med hjälp av Mixed-Integer Linear programming (MILP) modell. Gällande transformatorns termiska analys, så valdes den linjäriserade toppoljemodellen av IEEE Clause 7. Modellen var utförd för fyra olika krafttransformatorer: 63 MVA, 100 MVA, 200 MVA och 400 MVA. Resultatet blev att nettonuvärdet för investeringen och kapaciteten av vindkraftsparken ökade linjärt med avseende på storleken på transformatorn. En känslighetsanalys var utförd genom att ändra vindhastigheten, elpriset, livstiden av transformatorn och de valda väderdata. Från känslighetsanalysen så var det möjligt att dra slutsatsen att vindresurser och elpriset är nyckelparametrar för vindkraftsparkens genomförbarhet.

Approved for public release, distribution is unlimited / We optimize long-term project schedules subject to annual budget constraints, where the duration and cost of each task may increase as the project progresses. Initially, tasks are scheduled without regard to budgets and the project completion time is minimized. Treating the task durations as random variables, we then use simulation to describe the distribution of the project completion time. Next, we minimize the completion time under budget constraints with fixed task durations, where budget violations are tolerated albeit with penalties. Annual reviews are then introduced, which allow underway tasks to be delayed or monthly budgets to be increased. We obtain estimates of the completion time of the project and its final cost under each of these scenarios. The U.S. Army Future Combat Systems (FCS) is used for illustration. FCS is a suite of information technologies, sensors, and command systems with an estimated acquisition cost of over $90 billion. The U.S. General Accounting Office found that FCS is at risk of substantial cost overrun and delay. We analyze three schedule plans for FCS to identify which can be expected to deliver the earliest completion time and the least cost. / Major, Australian Army

Approved for public release, distribution is unlimited / Tomahawk cruise missiles (TCM) cost over one million dollars and are in short supply. U.S. Navy ships require TCM and other conventional ammunition be loaded in appropriate amounts prior to deploying to sea. A typical deployment lasts for six months and, when completed, any remaining ammunition must be unloaded and made ready for other deploying ships. For ships under Commander, Naval Surface Force U.S. Pacific Fleet (SURFPAC), about 3,500 tons of ammunition must be loaded and unloaded annually; this currently costs 14 million dollars for just pilots, tugboats and fuel. This thesis formulates and solves an integer linear program, Surface Navy Scheduler (SNSKED), to prescribe an ammunition load and unload schedule for San Diego homeported ships. SNSKED seeks a schedule with minimized costs subject to constraints on ships availability, port capabilities and support assets. We test SNSKED on a realistic quarterly scenario consisting of 19 combatant ships, three weapons stations, two ammunition ships, five mission types, two ammunition types, and three ways of loading ammunition. SNSKED provides optimal schedules that reduce costs by over 16 percent. We also use SNSKED to evaluate different operational policies, ammunition port utilization, and ammunition loading times. / Lieutenant Commander, United States Navy

Autonomous coordination among multiple aerial vehicles to ensure a collision free airspace is a critical aspect of today’s airspace. With the rise of Unmanned Aerial Vehicles (UAVs) in the military and commercial sectors, obstacle avoidance in a densely populated airspace is necessary. This thesis investigates finding optimal or near-optimal trajectories in real-time for aircraft in complex airspaces containing a large number of obstacles. The solution for the trajectories is described as a linear program subject to mixed integer constraints, known as a Mixed Integer Linear Program (MILP). The resulting MILP problem is solved in real time using a well-known, public domain MILP solver. In addition, an Exhaustive, Breadth-First Search algorithm was implemented and is used for comparison in terms of execution time and flight path optimality. The Exhaustive Search algorithm is comprised of a multi-branch tree structure that iterates through all possible flight paths from source to target. The MILP solution was implemented in both PC based and embedded system environments. The embedded system environment was implemented on an onboard processor to develop trajectories for each individual aircraft in real time.

[pt] O aumento da produção de petróleo brasileiro e o consequente aumento na demanda por transporte marítimo levaram a PETROBRAS a buscar ferramentas para aumentar a eficiência de seu transporte marítimo. Neste sentido, a atividade de programação de navios busca alocar os navios a um conjunto de cargas definido a priori, respeitando as restrições comerciais e operacionais, a fim de transportá-las com o menor custo possível. Com o intuito de auxiliar o programador nesta atividade, esta dissertação propõe um sistema de suporte à decisão (SSD) baseado em otimização para a programação de navios. O SSD proposto foi desenhado especificamente para a atividade de longo curso de navios de petróleo da PETROBRAS, sendo este gerado a partir da adaptação de modelos disponíveis na literatura acadêmica. Os testes comparativos realizados com o protótipo do SSD na atividade de longo curso de navios de petróleo mostraram que a ferramenta tem um significativo potencial de redução de custo. O SSD proposto se apresentou como uma opção viável para auxiliar a programação de navios da companhia na busca pela redução de custos de transporte marítimo. / [en] The increasing production of Brazilian oil and the consequent increase in the demand for shipping, led PETROBRAS to seek tools to increase the efficiency of its shipping. In this sense, the activity of ship scheduling seeks to assign vessels to a set of cargos, respecting business and operational restrictions in order to transport them with the lowest possible cost. To assist the ship scheduling planner in this activity, this dissertation proposes an optimization based decision support system (DSS) for ship scheduling. The proposed DSS was designed specifically for the long-term tanker scheduling activity at PETROBRAS and it was implemented based on models available in the academic literature. The comparative tests using the DSS prototype proposed in this dissertation showed that it has a potential for significant cost reduction. The proposed DSS was considered a viable tool to assist the ship scheduling planners in reducing shipping costs.

No description available.

Este trabalho trata de um problema de programação da produção em fundições de pequeno porte, que consiste em programar as ligas que devem ser produzidas em cada período do planejamento e como tais ligas devem ser usadas para a produção de itens sob encomenda, de modo que atrasos e custos operacionais sejam minimizados. Devido à certa incerteza nos dados do problema, a estratégia de horizonte rolante foi empregada. Este problema é representado por um modelo matemático de programação linear inteira mista. Neste trabalho foi desenvolvida uma heurística do tipo residual para obter uma boa solução inteira factível do problema, partindo da solução contínua encontrada pelos métodos relaxe-e-fixe e busca local / This work addresses a planning production problem that arises in small market-driven foundries, which consists of programming a number of alloys that have to be produced in each period of the planning horizon and how these alloys should be used to producing ordered items, in such way that delays and operational costs are minimized. Due to uncertainties in the problem data, the strategy of rolling horizon was used. This problem is modeled as a mixed integer linear programe. In this work we developed a residual typed heuristic in order to obtain a good feasible integer solution of the problem, which are built from the continuous solution found by relax-and-fix and local search methods. Keywords: Lot-sizing problems, mixed integer linear programming, production planning in foundries