On the Design of a Novel Solid Oxide Fuel Cell Combined Cooling, Heating and Power System for UK Residential Needs

Combined cooling, heating and power (CCHP) systems have become a topic of increasing research interest especially now that they may offer substantial improvements for conservation of fuel and electrical power in the domestic residential sector. However, only a few of the fuel cell (FC)-based CCHP systems have considered the inclusion of other power sources as part of their design with respect to diverse criteria for system optimisation. Most of the research undertaken thus far has focused on the performance improvement of CCHP systems when operated as a single energy source and has not considered the operation when connected to the electrical power distribution grid or under dynamic load conditions. The aim of this research project is to design a solid oxide fuel cell (SOFC)-based CCHP hybrid system that maximises system efficiency and minimises emissions and system costs in an objective manner with minimal operator and customer intervention. A new system structure has been designed to improve the flexibility of the system such that its functioning is closer to practical applications in both island and grid-connected modes, and still returns optimised performance with no need for system redesign or reconfiguration. A novel combination of grey relationship analysis (GRA) linked to an entropy weighting approach has been developed to evaluate the sizing values of fuel cells, heat exchangers and absorption chillers to improve the technical, economic and environmental system performance and reduce subjectivity and inaccuracy that could be imported through reliance on subjective human judgement. A new algorithm, denoted as the multi-objective particle swarm optimisation (MOPSO)-GRA has been designed to reduce local optimisation problem caused by standard MOPSO algorithms. The proposed system has been verified with published experimental results and comparative analysis has been carried out to verify the advance and the new algorithms. The main conclusion is that the optimum design of the SOFC-based CCHP hybrid system delivers optimised performance in terms of efficiency, operation and through life economy as well as environmental impact that gives a high degree of flexible compatibility within the energy supply environment in the UK

Optimal operation control of hybrid renewable energy systems

Thesis (D. Tech. (Electrical Engineering)) -- Central University of Technology, Free State, 2014For a sustainable and clean electricity production in isolated rural areas, renewable energies appear to be the most suitable and usable supply options. Apart from all being renewable and sustainable, each of the renewable energy sources has its specific characteristics and advantages that make it well suited for specific applications and locations. Solar photovoltaic and wind turbines are well established and are currently the mostly used renewable energy sources for electricity generation in small-scale rural applications. However, for areas in which adequate water resources are available, micro-hydro is the best supply option compared to other renewable resources in terms of cost of energy produced. Apart from being capital-cost-intensive, the other main disadvantages of the renewable energy technologies are their resource-dependent output powers and their strong reliance on weather and climatic conditions. Therefore, they cannot continuously match the fluctuating load energy requirements each and every time. Standalone diesel generators, on the other hand, have low initial capital costs and can generate electricity on demand, but their operation and maintenance costs are very high, especially when they run at partial loads. In order for the renewable sources to respond reliably to the load energy requirements, they can be combined in a hybrid energy system with back-up diesel generator and energy storage systems. The most important feature of such a hybrid system is to generate energy at any time by optimally using all available energy sources. The fact that the renewable resources available at a given site are a function of the season of the year implies that the fraction of the energy provided to the load is not constant. This means that for hybrid systems comprising diesel generator, renewable sources and battery storage in their architecture, the renewable energy fraction and the energy storage capacity are projected to have a significant impact on the diesel generator fuel consumption, depending on the complex interaction between the daily variation of renewable resources and the non-linear load demand. V This was the context on which this research was based, aiming to develop a tool to minimize the daily operation costs of standalone hybrid systems. However, the complexity of this problem is of an extremely high mathematical degree due to the non-linearity of the load demand as well as the non-linearity of the renewable resources profiles. Unlike the algorithms already developed, the objective was to develop a tool that could minimize the diesel generator control variables while maximizing the hydro, wind, solar and battery control variables resulting in saving fuel and operation costs. An innovative and powerful optimization model was then developed capable of efficiently dealing with these types of problems. The hybrid system optimal operation control model has been simulated using fmincon interior-point in MATLAB. Using realistic and actual data for several case studies, the developed model has been successfully used to analyse the complex interaction between the daily non-linear load, the non-linear renewable resources as well as the battery dynamic, and their impact on the hybrid system’s daily operation cost minimization. The model developed, as well as the solver and algorithm used in this work, have low computational requirements for achieving results within a reasonable time, therefore this can be seen as a faster and more accurate optimization tool

Optimal sizing for a grid-connected hybrid renewable energy system.

Masters Degree. University of KwaZulu- Natal, Durban.Hybrid renewable energy systems (HRESs) refer to power generating systems that integrate several sources of energy, including renewables, to provide electricity to consumers. HRESs can either work as standalone or grid-connected systems. Since wind and solar have complementary characteristics and are available in most areas, they are considered as suitable energy sources to be combined in an HRES. Moreover, the maturity of technologies needed for generating electricity from wind and solar has turned them into more economical options in many locations. Many countries, including South Africa, have introduced policies and incentives to increase their renewable energy capacities in order to address environmental concerns and reduce pollutant emissions into the atmosphere. In addition, consumers in South Africa have faced the ever-increasing price of electricity and unreliability of the grid since 2007 due to the lack of sufficient electricity production. As a result, employing HRESs has gained popularity among consumers in different sectors. This research is focused on grid-connected hybrid energy systems based on solar photovoltaic (PV) panels and wind turbines as a potential solution to reduce the dependency of residential sector consumers on the grid in Durban. The aim of the research is to identify the optimal sizing of such a HRES to be cost-effective for consumers over a certain period of time. Since the energy supplied by renewable sources are intermittent and dependent on the geographical location of the system, identifying optimal sizing becomes a challenging task in HRESs. In this research, Durban’s meteorological data and eThekwini municipality tariff rates have been considered. Moreover, two artificial intelligence methods have been used to obtain the optimal sizing for different types of available PV panels, wind turbines and inverters in the market. The results have shown that the combination of PV panels and battery storage (BS) can become a profitable option for Durban area. Moreover, the systems using higher rated power PV panels can start to become profitable in a shorter lifetime. Considering BS in a system can only become a cost-effective choice if we consider a long enough lifespan for the system

Optimal integration of wind energy with a renewable based microgrid for industrial applications.

Wind energy in urban environments is a rapidly developing technology influenced by the terrain specifications, local wind characteristics and urban environments such as buildings architecture. The urban terrain is more complex than for open spaces and has a critical influence on wind flow at the studied site. This approach proposes an integration of the surrounding buildings in the studied site and then simulating the wind flow, considering both simple and advanced turbulence models to quantify and simulate the wind flow fields in an urban environment and evaluate the potential wind energy. These simulations are conducted with an accessible computational fluid dynamic tool (Windsim) implementing available commercial wind turbines and performed on a case study at Agder county in the southern part of Norway for an industrial facility specialized in food production. Several simulations were considered and repeated to achieve a convergence after adding the buildings to the domain, which mainly simulates the wind flow patterns, power density, and annual energy production. These simulations will be compared with previous results, which adapted different manipulation techniques applied on the same site where the elevation and roughness data were manipulated to mimic the actual conditions in the studied urban site. The current approach (adding the buildings) showed a reduction in the average wind speed and annual energy production for certain levels with increased turbulence intensity surrounding the buildings. Moreover, a feasibility study is conducted to analyze the techno-economic of the facility's hybrid system, including the planned installation of a wind energy system using commercial software (HOMER). The simulation results indicated that HOMER is conservative in estimating the annual energy production of both wind and solar power systems. Nevertheless, the analysis showed that integrating a wind turbine of 600 kW would significantly reduce the dependence on the grid and transform the facility into a prosumer with more than 1.6 GWh traded with the grid annually. However, the proposed system's net present cost would be 1.43 M USD based on installation, maintenance, and trading with the grid, without including self-consumption, which counts for approximately 1.5 GWh annually. Moreover, the proposed system has a low levelized cost of energy of 0.039$ per kWh, which is slightly above the levelized cost of wind energy but 2 to 4 times less than the installed solar panels

Transition between stand-alone and grid connected solar photovoltaic microgrids

1 online resource (viii, 59 pages) : charts (some colour)Includes abstract.Includes bibliographical references (pages 52-59).In this study, conversion of Solar Photovoltaic (PV) energy to increase sustainable energy and increase system efficiency is being studied. During the process, both stand-alone mode and grid connected mode microgrid with energy storage system (ESS) have been tested in a simulation environment. Their transition from one mode to another have been discussed for research purpose. Solar photovoltaic PV modules, energy storage devices (Battery), power electronics converters are used to validate the desired results. The study of stand-alone to grid-connected systems will be analyzed and tuned for a stable system performance. During the tuning, the voltage and the frequency are the key driving parameters to be controlled and evaluated. Also, the study of grid connected configurations will be conducted and then both systems will be compiled together using a switching property. The aim is to work on control system for creating the transition in the systems. The study is tested with MATLAB/Simulink platform-based simulations. The major focus will be on the control mechanism of the inverters in both modes, specifically for this study

Development of a multi-objective optimization algorithm based on lichtenberg figures

This doctoral dissertation presents the most important concepts of multi-objective optimization and a systematic review of the most cited articles in the last years of this subject in mechanical engineering. The State of the Art shows a trend towards the use of metaheuristics and the use of a posteriori decision-making techniques to solve engineering problems. This fact increases the demand for algorithms, which compete to deliver the most accurate answers at the lowest possible computational cost. In this context, a new hybrid multi-objective metaheuristic inspired by lightning and Linchtenberg Figures is proposed. The Multi-objective Lichtenberg Algorithm (MOLA) is tested using complex test functions and explicit contrainted engineering problems and compared with other metaheuristics. MOLA outperformed the most used algorithms in the literature: NSGA-II, MOPSO, MOEA/D, MOGWO, and MOGOA. After initial validation, it was applied to two complex and impossible to be analytically evaluated problems. The first was a design case: the multi-objective optimization of CFRP isogrid tubes using the finite element method. The optimizations were made considering two methodologies: i) using a metamodel, and ii) the finite element updating. The last proved to be the best methodology, finding solutions that reduced at least 45.69% of the mass, 18.4% of the instability coefficient, 61.76% of the Tsai-Wu failure index and increased by at least 52.57% the natural frequency. In the second application, MOLA was internally modified and associated with feature selection techniques to become the Multi-objective Sensor Selection and Placement Optimization based on the Lichtenberg Algorithm (MOSSPOLA), an unprecedented Sensor Placement Optimization (SPO) algorithm that maximizes the acquired modal response and minimizes the number of sensors for any structure. Although this is a structural health monitoring principle, it has never been done before. MOSSPOLA was applied to a real helicopter’s main rotor blade using the 7 best-known metrics in SPO. Pareto fronts and sensor configurations were unprecedentedly generated and compared. Better sensor distributions were associated with higher hypervolume and the algorithm found a sensor configuration for each sensor number and metric, including one with 100% accuracy in identifying delamination considering triaxial modal displacements, minimum number of sensors, and noise for all blade sections.Esta tese de doutorado traz os conceitos mais importantes de otimização multi-objetivo e uma revisão sistemática dos artigos mais citados nos últimos anos deste tema em engenharia mecânica. O estado da arte mostra uma tendência no uso de meta-heurísticas e de técnicas de tomada de decisão a posteriori para resolver problemas de engenharia. Este fato aumenta a demanda sobre os algoritmos, que competem para entregar respostas mais precisas com o menor custo computacional possível. Nesse contexto, é proposta uma nova meta-heurística híbrida multi-objetivo inspirada em raios e Figuras de Lichtenberg. O Algoritmo de Lichtenberg Multi-objetivo (MOLA) é testado e comparado com outras metaheurísticas usando funções de teste complexas e problemas restritos e explícitos de engenharia. Ele superou os algoritmos mais utilizados na literatura: NSGA-II, MOPSO, MOEA/D, MOGWO e MOGOA. Após validação, foi aplicado em dois problemas complexos e impossíveis de serem analiticamente otimizados. O primeiro foi um caso de projeto: otimização multi-objetivo de tubos isogrid CFRP usando o método dos elementos finitos. As otimizações foram feitas considerando duas metodologias: i) usando um meta-modelo, e ii) atualização por elementos finitos. A última provou ser a melhor metodologia, encontrando soluções que reduziram pelo menos 45,69% da massa, 18,4% do coeficiente de instabilidade, 61,76% do TW e aumentaram em pelo menos 52,57% a frequência natural. Na segunda aplicação, MOLA foi modificado internamente e associado a técnicas de feature selection para se tornar o Seleção e Alocação ótima de Sensores Multi-objetivo baseado no Algoritmo de Lichtenberg (MOSSPOLA), um algoritmo inédito de Otimização de Posicionamento de Sensores (SPO) que maximiza a resposta modal adquirida e minimiza o número de sensores para qualquer estrutura. Embora isto seja um princípio de Monitoramento da Saúde Estrutural, nunca foi feito antes. O MOSSPOLA foi aplicado na pá do rotor principal de um helicóptero real usando as 7 métricas mais conhecidas em SPO. Frentes de Pareto e configurações de sensores foram ineditamente geradas e comparadas. Melhores distribuições de sensores foram associadas a um alto hipervolume e o algoritmo encontrou uma configuração de sensor para cada número de sensores e métrica, incluindo uma com 100% de precisão na identificação de delaminação considerando deslocamentos modais triaxiais, número mínimo de sensores e ruído para todas as seções da lâmina

Hourly Dispatching Wind-Solar Hybrid Power System with Battery-Supercapacitor Hybrid Energy Storage

This dissertation demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a specific dispatching horizon for an entire day utilizing a hybrid energy storage system (HESS) configured by batteries and supercapacitors. Here, wind speed and solar irradiance are predicted one hour ahead of time using a multilayer perceptron Artificial Neural Network (ANN), which exhibits satisfactory performance with good convergence mapping between input and target output data. Furthermore, multiple state of charge (SOC) controllers as a function of energy storage system (ESS) SOC are developed to accurately estimate the grid reference power (PGrid,ref) for each dispatching period. A low pass filter (LPF) is employed to decouple the power between a battery and a supercapacitor (SC), and the cost optimization of the HESS is computed based on the time constant of the LPF through extensive simulations. Besides, the optimum value of depth of discharge for ESS considering both cycling and calendar expenses has been investigated to optimize the life cycle cost of the ESS, which is vital for minimizing the cost of a dispatchable wind-solar power scheme. Finally, the proposed ESS control algorithm is verified by conducting control hardware-in-the loop (CHIL) experiments in a real-time digital simulator (RTDS) platform

Revisión de la optimización de Bess en sistemas de potencia

The increasing penetration of Distributed Energy Resources has imposed several challenges in the analysis and operation of power systems, mainly due to the uncertainties in primary resource. In the last decade, implementation of Battery Energy Storage Systems in electric networks has caught the interest in research since the results have shown multiple positive effects when deployed optimally. In this paper, a review in the optimization of battery storage systems in power systems is presented. Firstly, an overview of the context in which battery storage systems are implemented, their operation framework, chemistries and a first glance of optimization is shown. Then, formulations and optimization frameworks are detailed for optimization problems found in recent literature. Next, A review of the optimization techniques implemented or proposed, and a basic explanation of the more recurrent ones is presented. Finally, the results of the review are discussed. It is concluded that optimization problems involving battery storage systems are a trending topic for research, in which a vast quantity of more complex formulations have been proposed for Steady State and Transient Analysis, due to the inclusion of stochasticity, multi-periodicity and multi-objective frameworks. It was found that the use of Metaheuristics is dominant in the analysis of complex, multivariate and multi-objective problems while relaxations, simplifications, linearization, and single objective adaptations have enabled the use of traditional, more efficient, and exact techniques. Hybridization in metaheuristics has been important topic of research that has shown better results in terms of efficiency and solution quality.La creciente penetración de recursos distribuidos ha impuesto desafíos en el análisis y operación de sistemas de potencia, principalmente debido a incertidumbres en los recursos primarios. En la última década, la implementación de sistemas de almacenamiento por baterías en redes eléctricas ha captado el interés en la investigación, ya que los resultados han demostrado efectos positivos cuando se despliegan óptimamente. En este trabajo se presenta una revisión de la optimización de sistemas de almacenamiento por baterías en sistemas de potencia. Pare ello se procedió, primero, a mostrar el contexto en el cual se implementan los sistemas de baterías, su marco de operación, las tecnologías y las bases de optimización. Luego, fueron detallados la formulación y el marco de optimización de algunos de los problemas de optimización encontrados en literatura reciente. Posteriormente se presentó una revisión de las técnicas de optimización implementadas o propuestas recientemente y una explicación básica de las técnicas más recurrentes. Finalmente, se discutieron los resultados de la revisión. Se obtuvo como resultados que los problemas de optimización con sistemas de almacenamiento por baterías son un tema de tendencia para la investigación, en el que se han propuesto diversas formulaciones para el análisis en estado estacionario y transitorio, en problemas multiperiodo que incluyen la estocasticidad y formulaciones multiobjetivo. Adicionalmente, se encontró que el uso de técnicas metaheurísticas es dominante en el análisis de problemas complejos, multivariados y multiobjetivo, mientras que la implementación de relajaciones, simplificaciones, linealizaciones y la adaptación mono-objetivo ha permitido el uso de técnicas más eficientes y exactas. La hibridación de técnicas metaheurísticas ha sido un tema relevante para la investigación que ha mostrado mejorías en los resultados en términos de eficiencia y calidad de las soluciones

Fuel Cell Renewable Hybrid Power Systems

Climate change is becoming visible today, and so this book—through including innovative solutions and experimental research as well as state-of-the-art studies in challenging areas related to sustainable energy development based on hybrid energy systems that combine renewable energy systems with fuel cells—represents a useful resource for researchers in these fields. In this context, hydrogen fuel cell technology is one of the alternative solutions for the development of future clean energy systems. As this book presents the latest solutions, readers working in research areas related to the above are invited to read it