A microgrid is a subnetwork of power system that consists of a group of distributed energy sources and loads. It is designed to integrate distributed generation, loads, energy storage devices, converters, and monitoring and protection devices. Generally, a successful microgrid could run both in island mode (off-grid) and in grid-connected mode (on-grid), being able to convert between two modes at any time. With continuous development of the power system, distributed renewable generation unit accounts for an increasing proportion, since microgrid could effectively connect these generation units to the main grid, thereby improving the energy efficiency and the energy structure. Microgrid is increasingly playing an important role in the power system. This thesis focuses on reducing the cost of microgrids through economic operation, including both static and dynamic economic operations. Three cases are tested based on these two methods. Also, each case will include four situations including one without ESS and three situations with 2MWh ESS, 3MWh ESS, 4MWh ESS, respectively.

Renewable energy can effectively decrease carbon-dioxide emissions, and alleviate the Greenhouse effect. For consuming huge fossil fuel, Taiwan does have the obligation to reduce carbon-dioxide emissions. For the sunshine abound in the whole island and mature of photovoltaic (PV) industry, Taiwan has the potential to develop PV. This paper based on the Theory of Planned Behavior (TPB) and Multi-perspective on Technological Transition (MLP) focuses on the PV evolution of Taiwan. By empirical study, this paper developed a research framework, and applied questionnaire survey to verify it. Further, this paper also has a longitudinal case study and by historical research method to explore the evolution of Taiwan¡¦s PV policy. This paper found that attitude is the primary factor that affects the household¡¦s attention, and its antecedent factor relative advantage is the most important one. The second factor that affects the household¡¦s intention is perceived behavioral control which has the antecedent factor complexity. Further, perceived behavioral control also has the direct effect to the action which we must pay attention to it. Subjective norm has slight effect to the household¡¦s intention. And, social obligation is the antecedent factor of the subjective norm. Moreover, interfere effect exists between intention and household¡¦s real action. From the macro prospective, MLP depicts the evolution of Taiwan¡¦s PV diffusion, and we found it was resulted from the interaction of socio-technical landscape, socio-technical regime and niche-innovation. The processes were continually developed and form an innovative technology spiral.

Parmi les nouveaux matériaux massifs pour le silicium photovoltaïque (PV), le silicium multicristallin haute performance (HPmc-Si) a émergé en raison de son rendement de conversion supérieur à celui du silicium multi-cristallin (mc-Si) utilisé largement pour le solaire PV. Ce travail de recherche vise à comprendre l'influence des germes et des conditions de croissance sur les lingots HPmc-Si (structure de grains, dislocations, impuretés et propriétés PV). Cinq lingots ont été élaborés par solidification dirigée. Pour l’un d’entre eux, deux types de germes ont été utilisés. Les caractéristiques de la région de croissance initiale (jusqu’à 50 mm) sont directement liées aux propriétés de la couche de germes. Or, celle-ci dépend à la fois des types de germes utilisés et des paramètres de l’étape de fusion. Les paramètres de croissance prennent le contrôle de la structure de grains après la région affectée par la couche initiale de germes. Cependant, les paramètres de croissance étudiés modifient peu les caractéristiques entre lingots HPmc-Si et le rendement de conversion des cellules solaires. Les zones de faible durée de vie des porteurs minoritaires déterminent le rendement de conversion et peuvent être principalement associées aux défauts structuraux et à la taille du grain, en plus des impuretés métalliques. La compétition des grains est un phénomène dynamique qui permet la disparition de certains grains défectueux pendant la croissance et surtout le maintien d’une taille de grains et homogène. Cette homogénéité obtenue pour la gamme de paramètres étudiée est une des caractéristiques principales des lingots HPmc-Si / Among new bulk silicon PV materials, HPmc-Si is one to be considered due its higher conversion efficiency compared to mc-Si solar PV. This research work aims at understanding the influence of the seeding materials and growth conditions on HPmc-Si ingots (dislocations and impurities). Five ingots were grown, and two types of seeding materials are compared to study the grain structure, the electrical properties and the conversion efficiency of solar cells. The initial growth region up to 50 mm is directly linked to the seed layer properties which are dependent on the melting segment parameters. The growth parameters take control on the grain structure after the seed affected region. The growth parameters studied modify little the characteristics of HPmc-Si ingots and the solar cell conversion efficiency. Low carrier lifetimeareas determine the conversion efficiency and they can mainly be associated to the grain size, besides metallic impurities. The grain competition is very dynamic to suppress defective grains and to maintain smaller grain size variation, homogeneous grain size and properties being the most important characteristic of HPmc-Si ingots

The rise of disruptive technologies and the rapid growth of innovative initiatives have led to a trend of decentralization, deregulation, and distribution of regulated/centralized services. As a result, there is an increasing number of requests for the connection of distributed generators to distribution networks and the need for power utilities to quickly assess the impacts of distributed generators (DGs) to keep up with these requests. Grid integration of DGs brings about protection issues. Current protection systems were not designed for bi-directional power flow, thus the protective devices in the network lose their ability to perform their main functions. To mitigate the impact of distributed generation (DG), some standards and policies constrain the number of DG that can be connected to the distribution network. The problem with these limits is that they are based only on overload and overvoltage, and do not adequately define the DG size/threshold before the occurrence of a protection issue (NRS 097-2-3). The other problem with distributed generation is the vast difference in the technology, location, size, connection sequence, and protection scheme requirements which results in future DG network planning inadequacies – The Network DG Planning Dilemma. To determine the amount of DG to connect to the network, a detailed analysis is required which often involves the use of a simulation tool such as DIgSILENT to model the entire network and perform load flow studies. Modelling networks on DIgSILENT is relatively easy for simple networks but becomes time-consuming for complex, large, and real networks. This brings about a limitation to this method, planning inadequacies, and longer connection approval periods. Thus, there is a need for a fast but accurate system-wide tool that can assess the amount of DG that can be connected to a network. This research aims to present a technique used for calculating protection-based DG penetration limits on MV networks and develop a model to determine medium voltage opportunity network maps. These maps indicate the maximum amount of DG that can be connected to a network without the need for major protection scheme changes in South Africa. The approach to determining protection-based penetration limits is based on supervised machine learning methods. The aim is to rely on protection features present in the distribution network data i.e. fault level, Inverse Definite Minimum Time (IDMT) curve, pick-up current settings, Time Multiplier Settings (TMS), calculated relay operating times and relay positions to see how the network responds at certain DG penetration levels (‘actual' relay operating times). The dataset represents carefully anonymized distribution networks with accepted protection philosophy applied. A supervised machine learning algorithm is applied after nontrivial data pre-processing through recommendation systems and shuffling. The planning dilemma is cast into three parts: the first part is an automated pattern classification (logistic regression for classification of protection miscoordination), the second part involves regression (predicting operating time after different levels of DG penetration), and the last part involves developing a recommendation system (where, when and how much photovoltaic (PV) DG will be connected). Gradient descent, which is an optimisation algorithm that iterates and finds optimal values of the parameters that correspond to the local or global minimum values of the cost function using calculus was used to measure the accuracy of each model's hypothesis function. The cost function (one half mean squared error) for the models that predict ‘actual' relay operating times before DG penetration, at 35%, 65%, and 75% DG penetration converged to values below 120, 20, 15, and 15 seconds2 , respectively, within the first 100 iterations. A high variance problem was observed (cross-validation error was high and training error was low) for the models that used all the network protection features as inputs. The cross-validation and training errors approached the desired performance of 0.3±0.1 for the models that had second-order polynomials added. A training accuracy of 91.30%, 73.91%, 82.61%, and a validation accuracy of 100%, 55.56%, 66.67% was achieved when classifying loss of coordination, loss of grading and desensitization, respectively. A high bias problem was observed (cross-validation error was high and training error was high) for the loss of grading classification (relay positions eliminated) model. When the models (horizontal network features) were applied to four MV distribution networks, loss of coordination was not predicted, the loss of grading model had one false positive and the de-sensitization model had one false negative. However, when the results were compared to the vertical analysis (comparing the operating times of upstream and downstream relays/reclosers), 28 points indicated a loss of coordination (2 at 35%, 1 at 65% and 25 at 75% DG penetration). Protection coordination reinforcements (against loss of grading and desensitization) were found to be a requirement for DG connections where the MV transformer circuit breaker TMS is between 0.5 and 1.1, and where the network fault level is between 650 and 800A. Distribution networks in affluent neighbourhoods similar to those around the Western CapeSomerset West area and Gauteng- Centurion area need to be reinforced to accommodate maximum DG penetration up to the limit of 75% of the After Diversity Maximum Demand (ADMD). For future work, the collection of more data points (results from detailed analytical studies on the impact of DG on MV feeders) to use as training data to solve the observed high variance problem is recommended. Also, modifying the model by adding upstream and downstream network features as inputs in the classification model to solve the high bias problem is recommended.

The study sets out to review various literatures concerning photovoltaic/thermal (PVT) modules for the extraction of electricity and heat, it also reviews different PVT collectors as well as their performance. The study provides an understanding of a system that fully supports ecological society by promoting the use of solar modules from a different scope in future global resolutions. Furthermore, it looks into renewable energy in Sweden, solar energy and PVT systems, operational principles of hybrid PVT collectors, PVT applications, PVT market and legal face of PVT in Sweden among others. Among other social benefits, PVT system contributes enormously to energy savings and energy consumption which in turn lowers CO2 emissions. The review shows that PVT modules can provide homes and industries with 100% renewable electricity and heat that is affordable. This paper adopts systematic literature review, as it allows thorough cross-examination of various publications regarding the subject.

<p>The purpose of this study is to find potential areas suitable for energy production using renewable sources. For this aim, accurate assessments are necessary. The assessments include geographical suitability, closeness of infrastructure and observing local and regional framework concerning the use of renewable sources together with environmental protection. In addition, economical factor is considered in such an assessment. In this study, the Photovoltaic (PV) production potential for Germany is considered. An accurate and complete data set is necessary in order to achieve reliable results. In addition, a powerful database management and strong analysis tools are required. Geographical Information System (GIS) is a tool for finding suitable sites for the photovoltaic production.Using GIS, energy generation planners are able to visualize solar densities throughout the considered area. In addition, they can find the optimal and most economical sites by the combination of solar potential with the information about land. In this study, data sources consist of meteorological and geographical conditions. Furthermore, all analyses have been performed using Arc GIS Desktop. This study demonstrates the possible places for photovoltaic plants and indicates suitable candidates according to weights and factors in multi criteria analysis. The solar radiation data is from year 1995 to 2005. Land cover data is according to Corine 2000 and the more detailed Raumordnungskataster (Rok) for Weser-Ems. Numerical results are reliable from a comparison point of view. This study demonstrates the sensitivity of the defined criteria with respect to electricity production. In particular, this study is useful to see the capabilities of GIS for site selection regarding photovoltaic plants.The purpose of this study is to find potential areas suitable for energy production using renewable sources. For this aim, accurate assessments are necessary. The assessments include geographical suitability, closeness of infrastructure and observing local and regional framework concerning the use of renewable sources together with environmental protection. In addition, economical factor is considered in such an assessment. In this study, the Photovoltaic (PV) production potential for Germany is considered. An accurate and complete data set is necessary in order to achieve reliable results. In addition, a powerful database management and strong analysis tools are required. Geographical Information System (GIS) is a tool for finding suitable sites for the photovoltaic production.Using GIS, energy generation planners are able to visualize solar densities throughout the considered area. In addition, they can find the optimal and most economical sites by the combination of solar potential with the information about land. In this study, data sources consist of meteorological and geographical conditions. Furthermore, all analyses have been performed using Arc GIS Desktop. This study demonstrates the possible places for photovoltaic plants and indicates suitable candidates according to weights and factors in multi criteria analysis. The solar radiation data is from year 1995 to 2005. Land cover data is according to Corine 2000 and the more detailed Raumordnungskataster (Rok) for Weser-Ems. Numerical results are reliable from a comparison point of view. This study demonstrates the sensitivity of the defined criteria with respect to electricity production. In particular, this study is useful to see the capabilities of GIS for site selection regarding photovoltaic plants.</p>

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

The purpose of this study is to find potential areas suitable for energy production using renewable sources. For this aim, accurate assessments are necessary. The assessments include geographical suitability, closeness of infrastructure and observing local and regional framework concerning the use of renewable sources together with environmental protection. In addition, economical factor is considered in such an assessment. In this study, the Photovoltaic (PV) production potential for Germany is considered. An accurate and complete data set is necessary in order to achieve reliable results. In addition, a powerful database management and strong analysis tools are required. Geographical Information System (GIS) is a tool for finding suitable sites for the photovoltaic production.Using GIS, energy generation planners are able to visualize solar densities throughout the considered area. In addition, they can find the optimal and most economical sites by the combination of solar potential with the information about land. In this study, data sources consist of meteorological and geographical conditions. Furthermore, all analyses have been performed using Arc GIS Desktop. This study demonstrates the possible places for photovoltaic plants and indicates suitable candidates according to weights and factors in multi criteria analysis. The solar radiation data is from year 1995 to 2005. Land cover data is according to Corine 2000 and the more detailed Raumordnungskataster (Rok) for Weser-Ems. Numerical results are reliable from a comparison point of view. This study demonstrates the sensitivity of the defined criteria with respect to electricity production. In particular, this study is useful to see the capabilities of GIS for site selection regarding photovoltaic plants.The purpose of this study is to find potential areas suitable for energy production using renewable sources. For this aim, accurate assessments are necessary. The assessments include geographical suitability, closeness of infrastructure and observing local and regional framework concerning the use of renewable sources together with environmental protection. In addition, economical factor is considered in such an assessment. In this study, the Photovoltaic (PV) production potential for Germany is considered. An accurate and complete data set is necessary in order to achieve reliable results. In addition, a powerful database management and strong analysis tools are required. Geographical Information System (GIS) is a tool for finding suitable sites for the photovoltaic production.Using GIS, energy generation planners are able to visualize solar densities throughout the considered area. In addition, they can find the optimal and most economical sites by the combination of solar potential with the information about land. In this study, data sources consist of meteorological and geographical conditions. Furthermore, all analyses have been performed using Arc GIS Desktop. This study demonstrates the possible places for photovoltaic plants and indicates suitable candidates according to weights and factors in multi criteria analysis. The solar radiation data is from year 1995 to 2005. Land cover data is according to Corine 2000 and the more detailed Raumordnungskataster (Rok) for Weser-Ems. Numerical results are reliable from a comparison point of view. This study demonstrates the sensitivity of the defined criteria with respect to electricity production. In particular, this study is useful to see the capabilities of GIS for site selection regarding photovoltaic plants.

Because of the increasing demand for the provision of energy worldwide and the numerous damages caused by a major use of fossil sources, the contribution of renewable energies has been increasing significantly in the global energy mix with the aim at moving towards a more sustainable development. In this context, this work aims at the development of a general methodology for designing PV systems based on ecodesign principles and taking into account simultaneously both techno-economic and environmental considerations. In order to evaluate the environmental performance of PV systems, an environmental assessment technique was used based on Life Cycle Assessment (LCA). The environmental model was successfully coupled with the design stage model of a PV grid-connected system (PVGCS). The PVGCS design model was then developed involving the estimation of solar radiation received in a specific geographic location, the calculation of the annual energy generated from the solar radiation received, the characteristics of the different components and the evaluation of the techno-economic criteria through Energy PayBack Time (EPBT) and PayBack Time (PBT). The performance model was then embedded in an outer multi-objective genetic algorithm optimization loop based on a variant of NSGA-II. A set of Pareto solutions was generated representing the optimal trade-off between the objectives considered in the analysis. A multi-variable statistical method (i.e., Principal Componet Analysis, PCA) was then applied to detect and omit redundant objectives that could be left out of the analysis without disturbing the main features of the solution space. Finally, a decision-making tool based on M-TOPSIS was used to select the alternative that provided a better compromise among all the objective functions that have been investigated. The results showed that while the PV modules based on c-Si have a better performance in energy generation, the environmental aspect is what makes them fall to the last positions. TF PV modules present the best trade-off in all scenarios under consideration. A special attention was paid to recycling process of PV module even if there is not yet enough information currently available for all the technologies evaluated. The main cause of this lack of information is the lifetime of PV modules. The data relative to the recycling processes for m-Si and CdTe PV technologies were introduced in the optimization procedure for ecodesign. By considering energy production and EPBT as optimization criteria into a bi-objective optimization cases, the importance of the benefits of PV modules end-of-life management was confirmed. An economic study of the recycling strategy must be investigated in order to have a more comprehensive view for decision making.