The aim of this work is to research the issue of optimal sizing and location of photovoltaic distributed generation (PVDG) units on radial distribution feeders, and develop new procedures by which the optimal location may be determined. The procedures consider the concept that the PVDG production varies independently from changes in feeder load demand. Based on that, the developed procedures deal with two performance curves; the feeder daily load curve driven by the consumer load demand, and the PVDG daily production curve driven by the solar irradiance. Due to the mismatch in the profile of these two curves the PVDG unit might end up producing only part of its capacity at the time the feeder meets its peak load demand. An actual example of that is the summer peak load demand in Abu Dhabi city that occurs at 5:30 pm, which is 5 hours after the time the PV array yields its peak. Consequently, solving the optimization problem for maximum line power loss reduction (∆PPL) is deemed inappropriate for the connection of PVDG units. Accordingly, the procedures have been designed to solve for maximum line energy loss reduction (∆EL). A suitable concept has been developed to rate the ∆EL at one time interval over the day, namely feasible optimization interval (FOI). The concept has been put into effect by rating the ∆EL in terms of line power loss reduction at the FOI (ΔPLFOI). This application is deemed very helpful in running the calculations with no need to repeat the energy-based calculations on hourly basis intervals or even shorter. The procedures developed as part of this work have been applied on actual feeders at the 11kV level of Abu Dhabi distribution network. Two main scenarios have been considered relating to the avoidance and allowance of reverse power flow (RPF). In this course, several applications employing both single and multiple PVDG units have been solved and validated. The optimization procedures are solved iteratively. Hence, effective sub-procedures to help determine the appropriate number of feasible iterative steps have been developed and incorporated successfully. Additionally, the optimization procedures have been designed to deal with a 3-phase feeder under an unbalanced load condition. The line impedances along the feeder are modeled in terms of a phase impedance matrix. At the same time, the modeling of feeder load curves along with the power flow calculations and the resulting losses in the lines are carried out by phase. The resulting benefits from each application have been evaluated and compared in terms of line power loss reduction at the FOI (∆PLFOI) along with voltage and current flow profile.

For a successful market take-up of plug-in electric vehicles, fast-charging stations along the highway network play a significant role. This paper provides results from a first study on estimating the minimum number of fast-charging stations along the European highway network of selected countries (i.e., France, Germany, the Benelux countries, Switzerland, Austria, Denmark, the Czech Republic, and Poland) and gives an estimate on their future profitability. The combination of a comprehensive dataset of passenger car trips in Europe and an efficient arc-cover-path-cover flow-refueling location model allows generating results for such a comprehensive transnational highway network for the first time. Besides the minimum number of required fast-charging stations which results from the applied flow-refueling location model (FRLM), an estimation of their profitability as well as some country-specific results are also identified. According to these results the operation of fast-charging stations along the highway will be attractive in 2030 because the number of customers per day and their willingness to pay for a charge is high compared to inner-city charging stations. Their location-specific workloads as well as revenues differ significantly and a careful selection of locations is decisive for their economic operation.

Several studies have been carryout on finding optimal locations to minimize CO2 emissions from the last mile distribution perspective. In conjunction with that, there has been no study conducted in Sweden that provides a decision support system to compute the transport consequences of the modifications in the retailer’s store network. This thesis did used the following steps: requirement analysis, system design, implementation and testing to build a prototype decision support system that is to help retailers find optimal locations for a new retail store. This thesis provided a subsequent answer as to which data are needed along with the rightful user interface for said decision support system. Subsequently, this thesis does present a decision support system prototype from which some recommendations were provided as to what skills set and tools are needed for the management and maintenance of said decision support system. The primary data used during this thesis is the Dalarna municipalities, six selected retailer’s stores networks and the Dalarna Road network geo-data (Longitude and latitude). This thesis does conclude that it is possible to integrate an optimization model within the Django framework using a geo data to build a decision support system.

O objetivo principal deste trabalho foi criar um modelo matemático para determinar, em nível estratégico, os locais no Brasil mais apropriados à instalação de tanques de álcool combustível (anidro e hidratado) e seus respectivos volumes. O modelo de programação inteira-mista desenvolvido baseou-se na organização do sistema de distribuição de álcool, enfocando sua logística, e considerando questões de oferta, demanda, infra-estrutura de transporte e armazenagem, além de custos de transporte, armazenagem e investimentos em tanques. O modelo foi formulado considerando o horizonte temporal dos meses do ano-safra canavieiro de 2006/2007. Essa formulação reflete as sazonalidades de produção, demanda e estoques do álcool. O modelo de transporte foi enfatizado na minimização dos custos logísticos da cadeia distribuição de álcool combustível dos produtores aos consumidores. Dois cenários e a análise de sensibilidade de suas respostas abordaram a questão estocástica do problema. O primeiro analisou o panorama atual do mercado de álcool, logo não considerou a possibilidade de criação de novos tanques. A idéia desse cenário foi apresentar a consistência da modelagem e ressaltar as condições de infra-estrutura existente de transporte e armazenagem para álcool combustível. Foi feita uma análise de sensibilidade em relação a custos de transporte e restrições de armazenagem para checagem das respostas e para a comparação das práticas atuais de mercado. No segundo cenário, considerou-se a possibilidade de criação de novos tanques procurando identificar os locais mais apropriados para construção dessas estruturas e seu dimensionamento. A análise de sensibilidade em relação a custos de transporte e restrições de armazenagem foi feita para confirmar o potencial de cada localização. Os resultados indicaram a localização inapropriada das bases de distribuição de álcool no país. Destacaram-se também os baixos níveis de fretes de transferência em função das limitações de infraestrutura do sistema de distribuição de álcool. Tanto que as principais localizações de novos tanques disseram respeito a bases no interior da região Centro-Sul, destinos cujos custos de transporte de coleta e entrega são mais competitivos. Em relação aos novos tanques de álcool hidratado houve a indicação das cidades de: Cascavel - PR, Umuarama - PR, Maringá - PR, Lages - SC, Sinop - MT, Limeira - SP e Sorocaba - SP. Para o caso do álcool anidro os novos investimentos sugeridos foram nas cidades de: Londrina - PR, Cascavel - PR, Guarapuava - PR, Lajes - SC, Santa Maria - RS, Araçatuba - SP, Sinop - MT, Vilhena - RO, Montes Claros - MT, Dourados - MS, Gurupi - TO e Teresina - PI. Somado a isso houve a alocação de praticamente todo o custo de armazenagem às usinas. Finalmente, as soluções para a localização de novos investimentos dos tanques de álcool foram todas em regiões de bases de distribuição, já que as usinas estão bem servidas em relação à capacidade de armazenagem. / The main purpose of this research is to develop a mathematical model intended for strategic analysis of the optimal location and considering suitable volumes for storage ethanol (anhydrous and hydrous) tanks. The Mixed Integer Program - MIP model was based on Brazilian ethanol distribution system. The model considered market parameters as supply, demand, and infrastructure parameters on transportation, storage values as well as their expenses. New construction ethanol tanks expenses also were considered. The months along the sugarcane crop year period of 2006/2007 were referred into the modeling formulation. This formulation allows a seasonal storage, production and demand patterns analysis. Transportation model is the main concern in the total logistics cost minimization from producers to consumers. The model stochastic formulation was elaborated by creating two simulated scenarios and developing a sensitivity analysis. The purpose of the first scenario was to check the model consistency and explore the current ethanol transport and storage infrastructure without considering the possibility of new tank installation. Based on these results, a sensitivity analysis regarding transportation expenses and storage restrictions was elaborated in order to make a comparison with current market practices. In the second scenario, it was considered the construction of new ethanol tanks and the identification of the most suitable places bearing in mind volume capacities. Based on these results, a sensitivity analysis regarding transportation expenses and storage restrictions was elaborated in order to check each location consistency. Results indicated that mills are mostly responsible for ethanol (anhydrous and hydrous) storages maintenance types and that the existing geographic organization of terminals and fuel distributors is inappropriate for ethanol distribution in Brazil. Transportation low flows among terminals and fuel distributors also indicated lack of a better infrastructure for ethanol distribution. The model indicated that main location results for installation of new tanks would be located especially in the countryside of the centersouth states, where allocation and distribution of ethanol from mills to the consumer market would be more competitive. In relation to the new hydrous ethanol tanks, the model indicated appropriated locations for the cities of: Cascavel - PR, Umuarama - PR, Maringá - PR, Lages - SC, Sinop - MT, Limeira - SP e Sorocaba - SP. In the other hand, for anhydrous ethanol, new investments suggested in: Londrina - PR, Cascavel - PR, Guarapuava - PR, Lajes - SC, Santa Maria - RS, Araçatuba - SP, Sinop - MT, Vilhena - RO, Montes Claros - MT, Dourados - MS, Gurupi - TO e Teresina - PI. Finally, the model indicated that the best locations for the establishment of new ethanol tanks would be located in fuel distributors\' bases, once results confirmed that mills have enough storage capacity.

Feeder reconfiguration is performed by changing the open/close status of two types of switches: normally open tie switches and normally closed sectionalizing switches. A whole feeder or part of a feeder may be served from another feeder by closing a tie switch linking the two while an appropriate sectionalizing switch must be opened to maintain the radial structure of the system. Feeder reconfiguration is mainly aiming to reduce the system overall power losses and improve voltage profile. In this dissertation, several approaches have been proposed to reconfigure the radial distribution networks including the potential impact of integrating Distributed Energy Resources (DER) into the grid. These approaches provide a Fast-Genetic Algorithm “FGA” in which the size and convergence speed is improved compared to the conventional genetic algorithm. The size of the population matrix is also smaller because of the simple way of constructing the meshed network. Additionally, FGA deals with integer variable instead of a binary one, which makes FGA a unique method. The number of the mesh/loop is based on the number of tie switches in a particular network. The validity of the proposed FGA is investigated by comparing the obtained results with the one obtained from the most recent approaches. The second the approach is the implementation of the Differential Evolution (DE) algorithm. DE is a population-based method using three operators including crossover, mutation, and selection. It differs from GA in that genetic algorithms rely on crossover while DE relies on mutation. Mutation is based on the differences between randomly sampled pairs of solutions in the population. DE has three advantages: the ability to find the global optimal result regardless of the initial values, fast convergence, and requirement of a few control parameters. DE is a well-known and straightforward population-based probabilistic approach for comprehensive optimization. In distribution systems, if a utility company has the right to control the location and size of distributed generations, then the location and size of DGs may be determined based on some optimization methods. This research provides a promising approach to finding the optimal size and location of the planned DER units using the proposed DE algorithm. DGs location is obtained using the sensitivity of power losses with respect to real power injection at each bus. Then the most sensitive bus is selected for installing the DG unit. Because the integration of the DG adds positive real power injections, the optimal location is the one with the most negative sensitivity in order to get the largest power loss reduction. Finally, after the location is specified, the proposed Differential Evolution Algorithm (DEA) is used to obtain the optimal size of the DG unit. Only the feasible solutions that satisfy all the constraints are considered. The objective of installing DG units to the distribution network is to reduce the system losses and enhance the network voltage profile. Nowadays, these renewable DGs are required to equip with reactive power devices (such as static VAR compensators, capacitor banks, etc.), to provide reactive power as well as to control the voltage at their terminal bus. DGs have various technical benefits such as voltage profile improvement, relief in feeder loading, power loss minimization, stability improvement, and voltage deviation mitigation. The distributed generation may not achieve its full potential of benefits if placed at any random location in the system. It is necessary to investigate and determine the optimum location and size of the DG. Most distribution networks are radial in nature with limited short-circuit capacity. Therefore, there is a limit to which power can be injected into the distribution network without compromising the power quality and the system stability. This research is aiming to investigate this by applying DG technologies to the grid and keeping the system voltage within a defined boundary [0.95 - 1.05 p.u]. The requirements specified in IEEE Standard 1547 are considered. This research considers four objectives related to minimization of the system power loss, minimization of the deviations of the nodes voltage, minimization of branch current constraint violation, and minimization of feeder’s currents imbalance. The research formulates the problem as a multi-objective problem. The effectiveness of the proposed methods is demonstrated on different revised IEEE test systems including 16 and 33-bus radial distribution system.

O objetivo principal deste trabalho foi criar um modelo matemático para determinar, em nível estratégico, os locais no Brasil mais apropriados à instalação de tanques de álcool combustível (anidro e hidratado) e seus respectivos volumes. O modelo de programação inteira-mista desenvolvido baseou-se na organização do sistema de distribuição de álcool, enfocando sua logística, e considerando questões de oferta, demanda, infra-estrutura de transporte e armazenagem, além de custos de transporte, armazenagem e investimentos em tanques. O modelo foi formulado considerando o horizonte temporal dos meses do ano-safra canavieiro de 2006/2007. Essa formulação reflete as sazonalidades de produção, demanda e estoques do álcool. O modelo de transporte foi enfatizado na minimização dos custos logísticos da cadeia distribuição de álcool combustível dos produtores aos consumidores. Dois cenários e a análise de sensibilidade de suas respostas abordaram a questão estocástica do problema. O primeiro analisou o panorama atual do mercado de álcool, logo não considerou a possibilidade de criação de novos tanques. A idéia desse cenário foi apresentar a consistência da modelagem e ressaltar as condições de infra-estrutura existente de transporte e armazenagem para álcool combustível. Foi feita uma análise de sensibilidade em relação a custos de transporte e restrições de armazenagem para checagem das respostas e para a comparação das práticas atuais de mercado. No segundo cenário, considerou-se a possibilidade de criação de novos tanques procurando identificar os locais mais apropriados para construção dessas estruturas e seu dimensionamento. A análise de sensibilidade em relação a custos de transporte e restrições de armazenagem foi feita para confirmar o potencial de cada localização. Os resultados indicaram a localização inapropriada das bases de distribuição de álcool no país. Destacaram-se também os baixos níveis de fretes de transferência em função das limitações de infraestrutura do sistema de distribuição de álcool. Tanto que as principais localizações de novos tanques disseram respeito a bases no interior da região Centro-Sul, destinos cujos custos de transporte de coleta e entrega são mais competitivos. Em relação aos novos tanques de álcool hidratado houve a indicação das cidades de: Cascavel - PR, Umuarama - PR, Maringá - PR, Lages - SC, Sinop - MT, Limeira - SP e Sorocaba - SP. Para o caso do álcool anidro os novos investimentos sugeridos foram nas cidades de: Londrina - PR, Cascavel - PR, Guarapuava - PR, Lajes - SC, Santa Maria - RS, Araçatuba - SP, Sinop - MT, Vilhena - RO, Montes Claros - MT, Dourados - MS, Gurupi - TO e Teresina - PI. Somado a isso houve a alocação de praticamente todo o custo de armazenagem às usinas. Finalmente, as soluções para a localização de novos investimentos dos tanques de álcool foram todas em regiões de bases de distribuição, já que as usinas estão bem servidas em relação à capacidade de armazenagem. / The main purpose of this research is to develop a mathematical model intended for strategic analysis of the optimal location and considering suitable volumes for storage ethanol (anhydrous and hydrous) tanks. The Mixed Integer Program - MIP model was based on Brazilian ethanol distribution system. The model considered market parameters as supply, demand, and infrastructure parameters on transportation, storage values as well as their expenses. New construction ethanol tanks expenses also were considered. The months along the sugarcane crop year period of 2006/2007 were referred into the modeling formulation. This formulation allows a seasonal storage, production and demand patterns analysis. Transportation model is the main concern in the total logistics cost minimization from producers to consumers. The model stochastic formulation was elaborated by creating two simulated scenarios and developing a sensitivity analysis. The purpose of the first scenario was to check the model consistency and explore the current ethanol transport and storage infrastructure without considering the possibility of new tank installation. Based on these results, a sensitivity analysis regarding transportation expenses and storage restrictions was elaborated in order to make a comparison with current market practices. In the second scenario, it was considered the construction of new ethanol tanks and the identification of the most suitable places bearing in mind volume capacities. Based on these results, a sensitivity analysis regarding transportation expenses and storage restrictions was elaborated in order to check each location consistency. Results indicated that mills are mostly responsible for ethanol (anhydrous and hydrous) storages maintenance types and that the existing geographic organization of terminals and fuel distributors is inappropriate for ethanol distribution in Brazil. Transportation low flows among terminals and fuel distributors also indicated lack of a better infrastructure for ethanol distribution. The model indicated that main location results for installation of new tanks would be located especially in the countryside of the centersouth states, where allocation and distribution of ethanol from mills to the consumer market would be more competitive. In relation to the new hydrous ethanol tanks, the model indicated appropriated locations for the cities of: Cascavel - PR, Umuarama - PR, Maringá - PR, Lages - SC, Sinop - MT, Limeira - SP e Sorocaba - SP. In the other hand, for anhydrous ethanol, new investments suggested in: Londrina - PR, Cascavel - PR, Guarapuava - PR, Lajes - SC, Santa Maria - RS, Araçatuba - SP, Sinop - MT, Vilhena - RO, Montes Claros - MT, Dourados - MS, Gurupi - TO e Teresina - PI. Finally, the model indicated that the best locations for the establishment of new ethanol tanks would be located in fuel distributors\' bases, once results confirmed that mills have enough storage capacity.

Power losses are always a cause of worry for any power grid. In India, the situation is even worse. Though recent reports by Ministry of Power shows that Aggregate Technical and Commercial losses (AT &C losses) have come down from 36.64% in 2002-03 to 27% in 2011-12, yet they are much higher than the losses seen in many of the developed nations. The reduction shown in power loss is because of the Electricity Act, 2003 and the amendments made to it in 2007 which controlled the commercial losses rather than the technical losses. According to Ministry of Power, technical losses (Transmission & Distribution losses or T&D losses) in India are reported to be 23.65% in 2011-12. However, according to the study done by EPRI, for systems deployed in developed countries, these losses are estimated to be in the range of 7-15.5%. T & D losses occur in four system components namely step-up transformers and high voltage transmission (0.5-1%), step down to in intermediate voltage, transmission and step down to sub transmission voltage level (1.5-3%), sub-transmission system and step down to low voltage for distribution (2-4.5%), and distribution lines (3-7%). 1% of power loss is approximately equivalent to annual loss of Rs 600 million for a single state. Hence, in a year, loss in distribution line alone causes approximate loss of Rs 1.8-4.2 billion per state. Understanding and reducing power losses in distribution lines which contribute nearly 50% of the total T&D losses assume significance and has formed the motivation for the work reported in the thesis. In recent years, the trend has been to encourage users to generate solar power predominantly at residential complexes and captive power plants at industrial complexes. It has been suggested in the literature that Distributed Generation (DG) can not only reduce the load demanded from the power grid but also the power loss. In this thesis, it has been shown that by the choice of proper size and location of DG, the power loss can be reduced substantially as compared to unplanned deployment of DGs. The objective of the thesis is to design strategy for location of distributed user generated power to maximize the reduction in power loss. The thesis begins with a study of distributed generation in primary distribution networks and proceeds to problem formulation, with the aim being to develop an algorithm that can find out the optimal locations for DG allocation in a network. A greedy approximation algorithm, named OPLODER (i.e. Optimal Locations for Distributed Energy Resources), is proposed for the same and its performance on a benchmark data set is observed, which is found to be satisfactory. The thesis then moves on to describe the actual data of 101,881 commercial, residential and industrial consumers of Bangalore metropolitan area. A loss model is discussed and is used to calculate the line losses in LV part of the grid and loss is estimated for the said actual data. The detailed analysis of the losses in the distribution network shows that in most cases the losses are correlated with the sanctioned load. However there are also some outliers indicating otherwise. The analysis concludes that the distributed generated sources need to be optimally located in order to benefit fully. Also presented thereafter is a study about the impact of electrical properties and the structure of the network on power loss. In the second part of the thesis, OPLODER was again used to process the BESCOM data of 101,881 consumers by modeling them to be connected in three topologies namely Bus (i.e. linear structure), Star (i.e. directly connected) and Hybrid (i.e. tree structure). In case of Bus topology, when DG capacity available is 5% of the demand in substation, OPLODER reduced the loss from 14.65% to 10.75%, from 11.63% to 7.71% and from 13.33% to 9.24% for IISc, Brindavan, and Gokula substations respectively. Similarly, for the same amount of DG in case of star topology, OPLODER reduced loss from 1.75% to 1.26%, from 3.39% to 2.59% and from 2.96% to 1.99% for IISc, Brindavan, and Gokula substations respectively. Thereafter, the available real world data is re-modeled as a tree-type structure which is closer to the real world distribution network and OPLODER is run on it. The results obtained are similar to those presented above and are highly encouraging. When applied to the three substations viz. IISc, Brindavan and Gokula, the power loss dips from 9.95% to 7.42%, from 6.01% to 4.44% and from 8.07% to 5.95%, in case of DG used is 5% of the demand in substation. For the optimal strategies worked out in the thesis, additional overheads will be present. These overheads are studied and it has been found that the present infrastructure and technologies will be sufficient to handle the smart distribution network and the optimal strategy for distributed sources.