Optimisation of stand-alone hybrid energy systems for power and thermal loads

Stand-alone hybrid energy systems are an attractive option for remote communities without a connection to a main power grid. However, the intermittent nature of solar and other renewable sources adversely affects the reliability with which these systems respond to load demands. Hybridisation, achieved by combining renewables with combustion-based supplementary prime movers, improves the ability to meet electric load requirements. In addition, the waste heat generated from backup Internal Combustion Engines or Micro Gas Turbines can be used to satisfy local heating and cooling loads. As a result, there is an expectation that the overall efficiency and Greenhouse Gas Emissions of stand-alone systems can be significantly improved through waste heat recovery. The aims of this PhD project are to identify how incremental increases to the hardware complexity of hybridised stand-alone energy systems affect their cost, efficiency, and CO2 footprint. The research analyses a range of systems, from those designed to meet only power requirements to others satisfying power and heating (Combined Heat and Power), or power plus both heating and cooling (Combined Cooling, Heating, and Power). The majority of methods used focus on MATLAB-based Genetic Algorithms (GAs). The modelling deployed finds the optimal selection of hardware configurations which satisfy single- or multi-objective functions (i.e. Cost of Energy, energy efficiency, and exergy efficiency). This is done in the context of highly dynamic meteorological (e.g. solar irradiation) and load data (i.e. electric, heating, and cooling). Results indicate that the type of supplementary prime movers (ICEs or MGT) and their minimum starting thresholds have insignificant effects on COE but have some effects on Renewable Penetration (RP), Life Cycle Emissions (LCE), CO2 emissions, and waste heat generation when the system is sized meeting electric load only. However, the transient start-up time of supplementary prime movers and temporal resolution have no significant effects on sizing optimisation. The type of Power Management Strategies (Following Electric Load-FEL, and Following Electric and Following Thermal Load- FEL/FTL) affect overall Combined Heating and Power (CHP) efficiency and meeting thermal demand through recovered heat for a system meeting electric and heating load with response to a specific load meeting reliability (Loss of Power Supply Probability-LPSP). However, the PMS has marginal effects on COE. The Electric to Thermal Load Ratio (ETLR) has no effects on COE for PV/Batt/ICE but strongly affects PV/Batt/MGT-based hybridised CHP systems. The higher thermal than the electric loads lead to higher efficiency and better environmental footprint. Results from this study also indicate that for a stand-alone hybridised system operating under FEL/FTL type PMS, the power only system has lower cost compared to the CHP and the Combined Cooling, Heating, and Power (CCHP) systems. This occurs at the expense of overall energy and exergy efficiencies. Additionally, the relative magnitude of heating and cooling loads have insignificant effects on COE for PV/Batt/ICE-based system configurations, however this substantially affects PV/Batt/MGT-based hybridised CCHP systems. Although there are no significant changes in the overall energy efficiency of CCHP systems in relation to variations to heating and cooling loads, systems with higher heating demand than cooling demand lead to better environmental benefits and renewable penetration at the cost of Duty Factor. Results also reveal that the choice of objective functions do not affect the system optimisation significantly

Cooperative energy management for a cluster of households prosumers

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe increment of electrical and electronic appliances for improving the lifestyle of residential consumers had led to a larger demand of energy. In order to supply their energy requirements, the consumers have changed the paradigm by integrating renewable energy sources to their power grid. Therefore, consumers become prosumers in which they internally generate and consume energy looking for an autonomous operation. This paper proposes an energy management system for coordinating the operation of distributed household prosumers. It was found that better performance is achieved when cooperative operation with other prosumers in a neighborhood environment is achieved. Simulation and experimental results validate the proposed strategy by comparing the performance of islanded prosumers with the operation in cooperative modePeer ReviewedPostprint (author's final draft

Energy Storage Systems for Traction and Renewable Energy Applications

Energy storage systems are the set of technologies used to store various forms of energy, and by necessity, can be discharged. Energy storage technologies have a wide range of characteristics and specifications. Like any other technology, each type of energy storage has its pros and cons. Depending on the application, it is crucial to perform a tradeoff study between the various energy storage options to choose the optimal solution based on the key performance objectives and various aspects of those technologies. The purpose of this thesis is to present a thorough literature review of the various energy storage options highlighting the key tradeoffs involved. This thesis focuses on evaluating energy storage options for traction and renewable energy applicationsHybrid Electric Vehicles (HEVs) is one key application space driving breakthroughs in energy storage technologies. The focus though has been typically on using one type of energy storage systems. This thesis investigates the impact of combining several types of batteries with ultracapacitor. A case study of integrating two energy storage systems in a series-parallel hybrid electric vehicle is simulated by using MATLAB-SIMULINK software.The other key application space is renewable energy especially wind and solar. Due to the intermittent nature of renewable energy sources, energy storage is a must to achieve the required power quality. Therefore, this thesis aims to investigate different cases of combining different types of energy storage with wind and solar. Hybrid Optimization Model for Electric Renewables (HOMER) software is utilized to study the economic and sizing aspects in each case

Modular Supply Network Optimization of Renewable Ammonia and Methanol Co-production

To reduce the use of fossil fuels and other carbonaceous fuels, renewable energy sources such as solar, wind, geothermal energy have been suggested to be promising alternative energy that guarantee sustainable and clean environment. However, the availability of renewable energy has been limited due to its dependence on weather and geographical location. This challenge is intended to be solved by the utilization of the renewable energy in the production of chemical energy carriers. Hydrogen has been proposed as a potential renewable energy carrier, however, its chemical instability and high liquefaction energy makes researchers seek for other alternative energy carriers. Ammonia and methanol can serve as promising alternative energy carriers due to their chemical stability at room temperature, low liquefaction energy, high energy value. The co-production of these high energy dense energy carriers offers economic and environmental advantages since their synthesis involve the direct utilization of CO2 and common unit operations. This problem report aims to review the optimization of the co-production of methanol and ammonia from renewable energy. Form this review, research challenges and opportunities are identified in the following areas: (i) optimization of methanol and ammonia co-production under renewable and demand uncertainty, (ii) impacts of the modular exponent on the feasibility of co-production of ammonia and methanol, and (iii) development of modern computational tools for systems-based analysis

Green Principles, Parametric Analysis, and Optimization for Guiding Environmental and Economic Performance of Grid-scale Energy Storage Systems

The development and deployment of grid-scale energy storage technologies have increased recently and are expected to grow due to technology improvements and supporting policies. While energy storage can help increase the penetration of renewables, reduce the consumption of fossil fuels, and increase the grid sustainability, its integration into the electric grid poses unique sustainability challenges that need to be investigated through systematic sustainability assessment frameworks. The main objective of this dissertation is to develop principles and models to assess the environmental and economic impacts of grid-scale energy storage and guide its development and deployment. The first study of this dissertation is an initial case study of energy storage to examine the role of cost-effective energy storage in supporting high penetration of wind energy and achieving emissions targets in an off-grid configuration. In this study, the micro-grid system includes wind energy integrated with vanadium redox flow battery (VRFB) as energy storage, and natural gas engine. Life cycle greenhouse gas (GHG) emissions and total cost of delivered electricity are evaluated and generation mixes are optimized to meet emissions targets at the minimum cost. The results demonstrate that while incorporating energy storage consistently reduces life cycle GHG emissions in the system by integrating more wind energy, its integration is cost-effective only under very ambitious emission targets. The insights from this case study and additional literature review led to the development of a set of twelve principles for green energy storage, presented in the second study. These principles are applicable to the wide range of energy storage technologies and grid applications, and are developed to guide the design, maintenance, and operation of energy storage systems for grid applications. The robustness of principles was tested through a comprehensive literature review and also through in-depth quantitative analyses of the VRFB off-grid system. An in-depth parametric analysis is developed in the third study to evaluate the impacts of six key parameters (e.g. energy storage service-life) that influence the environmental performance of six energy storage technologies within three specific grid applications (including time-shifting, frequency regulation, and power reliability). This study reveals that round-trip efficiency and heat rate of charging and displaced generation technologies are dominant parameters in time-shifting and regulation applications, whereas energy storage service life and production burden dominate in power reliability. Finally, an optimization model is developed in the fourth study to examine the real-world application of energy storage in bulk energy time-shifting in California grid under varying renewable penetration levels. The objective was to find the optimal operation and size of energy storage in order to minimize the system total costs (including monetized GHG emissions), while meeting the electricity load and systems constraints. Simulations were run to investigate how the operation of nine distinct storage technologies impacted system cost, given each technology’s characteristics. The results show that increasing the renewable capacity and the emissions tax would make it more cost-effective for energy storage deployment. Among storage technologies, pumped-hydro and compressed-air energy storage with lower capital costs, are deployed in more scenarios. Overall, this research demonstrates how sustainability performance is influenced by storage technology characteristics and the electric grid conditions. The systematic principles, model equations, and optimizations developed in this dissertation provide specific guidance to industry stakeholders on design and deployment choices. The targeted audience ranges from energy storage designers and manufacturers to electric power utilities.PHDNatural Resources & EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143942/1/marbab_1.pd

Initial location selection of electric vehicles charging infrastructure in urban city through clustering algorithm

Transportation is one of the critical sectors worldwide, mainly based on fossil fuels, especially internal combustion engines. In a developing country, heightened dependence on fossil fuels affected energy sustainability issues, greenhouse gas emissions, and increasing state budget allocation towards fuel subsidies. Moreover, shifting to electric vehicles (EVs) with alternative energy, primely renewable energy sources, is considered a promising alternative to decreasing dependence on fossil fuel consumption. The availability of a sufficient EV charging station infrastructure is determined as an appropriate strategy and rudimentary requirement to optimize the growth of EV users, especially in urban cities. This study aims to utilize the k-mean algorithm’s clustering method to group and select a potential EV charging station location in Jakarta an urban city in Indonesia. This study proposed a method for advancing the layout location’s comprehensive suitability. An iterative procedure determines the most suitable value for K as centroids. The K value is evaluated by cluster silhouette coefficient scores to acquire the optimized numeral of clusters. The results show that 95 potential locations are divided into 19 different groups. The suggested initial EV charging station location was selected and validated by silhouette coefficient scores. This research also presents the maps of the initially selected locations and clustering

Theoretical and experimental investigation of a CDI injection system operating on neat rapeseed oil - feasibility and operational studies

This thesis presents the work done within the PhD research project focusing on the utilisation of plant oils in Common Rail (CR) diesel engines. The work scope included fundamental experimental studies of rapeseed oil (RSO) in comparison to diesel fuel, the feasibility analysis of diesel substitution with various plant oils, the definition and implementation of modifications of a common rail injection system and future work recommendations of possible changes to the injection system. It was recognised that neat plant oils can be considered as an alternative substitute for diesel fuel offering a natural way to balance the CO2 emissions. However, due to the differences between diesel and plant oils, such as density, viscosity and surface tension, the direct application of plant oils in common rail diesel engines could cause degradation of the injection process and in turn adversely affect the diesel engine’s performance. RSO was chosen to perform the spray characterisation studies at various injection pressures and oil temperatures under conditions similar to the operation of the common rail engine. High speed camera, Phase Doppler Anemometry and Malvern laser techniques were used to study spray penetration length and cone angle of RSO in comparison to diesel. To study the internal flow inside the CR injector the acoustic emission technique was applied. It was found that for oil temperatures below 40°C the RSO viscosity, density and surface tension are higher in comparison to diesel, therefore at injection pressures around 37.50 MPa the RSO spray is not fully developed. The spray penetration and cone angle at these spray conditions exhibit significant spray deterioration. In addition to the lab experiments, KIVA code simulated RSO sprays under CR conditions. The KH-RT and RD breakup models were successfully applied to simulate the non-evaporating sprays corresponding to the experimental spray tests and finally to predict i real in-cylinder injection conditions. Numerical results showed acceptable agreement with the experimental data of RSO penetration. Based on experimental and numerical results it was concluded that elevated temperature and injection pressure could be the efficient measures to overcome operational obstacles when using RSO in the CR diesel engine. A series of modifications of low- and highpressure loops was performed and experimentally assessed throughout the engine tests. The results revealed that the modifications allowed to run the engine at the power and emission outputs very close to diesel operation. However, more fundamental changes were suggested as future work to ensure efficient and trouble-free long-term operation. It is believed that these changed should be applied to meet Euro IV and V requirements

Smart operation of transformers for sustainable electric vehicles integration and model predictive control for energy monitoring and management

The energy transmission and distribution systems existing today are stillsignificantly dependent on transformers,despite beingmore efficient and sustainable than those of decadesago. However, a large numberof power transformers alongwith other infrastructures have been in service for decades and are considered to be in their final ageing stage. Anymalfunction in the transformerscouldaffect the reliability of the entire electric network and alsohave greateconomic impact on the system.Concernsregardingurban air pollution, climate change, and the dependence on unstable and expensive supplies of fossil fuels have lead policy makers and researchers to explore alternatives to conventional fossil-fuelled internal combustion engine vehicles. One such alternative is the introduction of electric vehicles. A broad implementation of such mean of transportation could signify a drastic reduction in greenhouse gases emissions and could consequently form a compelling argument for the global efforts of meeting the emission reduction targets. In this thesis the topic of a high penetration of electric vehicles and their possible integration in insular networksis discussed. Subsequently, smart grid solutions with enabling technologies such as energy management systems and smart meters promote the vision of smart households, which also allows for active demand side in the residential sector.However, shifting loads simultaneously to lower price periods is likely to put extra stress on distribution system assets such as distribution transformers. Especially, additional new types of loads/appliances such as electric vehicles can introduce even more uncertaintyon the operation of these assets, which is an issue that needs special attention. Additionally, in order to improve the energy consumption efficiencyin a household, home energy management systems are alsoaddressed. A considerable number ofmethodologies developed are tested in severalcasestudies in order to answer the risen questions.Os sistemas de transmissão e distribuição de energia existentes hoje em dia sãosignificativamente dependentes dos transformadores, pese embora sejammais eficientes e sustentáveis do que os das décadas passadas. No entanto, uma grande parte dos transformadores ao nível dadistribuição, juntamente com outras infraestruturassubjacentes, estão em serviço há décadas e encontram-se nafasefinal do ciclo devida. Qualquer defeito no funcionamento dos transformadorespode afetara fiabilidadede toda a redeelétrica, para além de terum grande impactoeconómico no sistema.Os efeitos nefastos associadosàpoluição do arem centro urbanos, asmudançasclimáticasea dependência de fontes de energiafósseis têm levado os decisores políticos e os investigadores aexplorar alternativas para os veículos convencionais de combustão interna. Uma alternativa é a introdução de veículos elétricos. Umaampla implementação de tal meio de transporte poderia significar uma redução drástica dos gases de efeito de estufa e poderiareforçar os esforços globais para ocumprimento das metas de redução de emissõesde poluentes na atmosfera.Nesta tese é abordado o tema da elevada penetração dos veículos elétricose a sua eventual integração numarede elétricainsular. Posteriormente, são abordadas soluções de redeselétricasinteligentes com tecnologias específicas, tais como sistemas de gestão de energia e contadores inteligentes que promovamo paradigmadas casas inteligentes, que também permitem a gestão da procura ativano sector residencial.No entanto, deslastrando significativamente as cargaspara beneficiar de preçosmais reduzidosé suscetíveldecolocarconstrangimentosadicionaissobre os sistemas de distribuição, especialmentesobre ostransformadores.Osnovos tipos de cargas tais como os veículos elétricospodem introduzir ainda mais incertezassobre a operação desses ativos, sendo uma questão que suscitaespecial importância. Além disso, com ointuitode melhorar a eficiência do consumo de energia numa habitação, a gestão inteligente daenergia é um assunto que também éabordadonesta tese. Uma pletora de metodologias é desenvolvida e testadaemvários casos de estudos, a fim de responder às questões anteriormente levantadas

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy