160 research outputs found

    Enhanced Intelligent Energy Management System for a Renewable Energy-based AC Microgrid

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    This paper proposes an enhanced energy management system (EEMS) for a residential AC microgrid. The renewable energy-based AC microgrid with hybrid energy storage is broken down into three distinct parts: a photovoltaic (PV) array as a green energy source, a battery (BT) and a supercapacitor (SC) as a hybrid energy storage system (HESS), and apartments and electric vehicles, given that the system is for residential areas. The developed EEMS ensures the optimal use of the PV arrays’ production, aiming to decrease electricity bills while reducing fast power changes in the battery, which increases the reliability of the system, since the battery undergoes fewer charging/discharging cycles. The proposed EEMS is a hybrid control strategy, which is composed of two stages: a state machine (SM) control to ensure the optimal operation of the battery, and an operating mode (OM) for the best operation of the SC. The obtained results show that the EEMS successfully involves SC during fast load and PV generation changes by decreasing the number of BT charging/discharging cycles, which significantly increases the system’s life span. Moreover, power loss is decreased during passing clouds phases by decreasing the power error between the extracted power by the sources and the required equivalent; the improvement in efficiency reaches 9.5%

    Enhacement of microgrid technologies using various algorithms

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    The electric power systems around the globe are gradually shifting from conventional fossil fuel-based generating units to green renewable energy sources. The motivation behind this change is the environmental and economic concerns. Furthermore, the existing power systems are being overloaded day by day due to the continuously increasing population, which consequently led to the overloading of transformers, transmission, and distribution lines. Despite the overwhelming advantages of renewable energy sources, there are few major issues associated with them. For example, the injection and detachment of DGs into the current power system causes disparity among produced power along with connected load, thus distracting system’s equilibrium and causes unwanted voltage and frequency oscillations and overshoots. These oscillations and overshoots may cause the failure of connected equipment or power system if not properly controlled. The investigation as such challenges to improve the frequency and voltage, the islanded’s power regulation and connected MG under source and load changes, which contain classic and artificial intelligence techniques. Moreover, these techniques are used also for economic analysis. To evaluate the exhibitions of microgrid (MG) operations and sizing economic analysis acts as a significant tool. Optimization method is obligatory for sizing and operating an MG as reasonably as feasible. Diverse optimization advances remain pertained to microgrid to get optimal power flow and management

    Homeostatic Control of Sustainable Energy Grid Applied to Natural Disasters

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    According to seismologists Chile has yet to face another big earthquake in the very near future, yet the country remains largely unprepared against massive electric power systems brake-down. The problem lies in the centralized electric power systems and the lack of adequate technologies and back-up/emergency power systems for disas- ter recovery. The flaws that are built into the very fabric of the presently centralized power systems were on full display in the February 27th earthquake in Chile. Nowhere it becomes more evident that hugely centralized power generation and distribution systems are extremely vulnerable and ineffective to disruptions from natural disasters, human error or other calamities. The large power networks that once proved very efficient and secure, are now at the center of discussion fueling the need for decentral- ization and the rapid growth of distributed generation (DG). Highly decentralized, diversified and DG-oriented energy matrix is notoriously much better suited to with- stand these disasters. In centralized electric power grids, servicing large metropolitan areas, albeit with some but limited differentiation in service, can only be on or off, so either everyone gets power or no one does. This makes recovering power service in an emergency situation a much more difficult task. On the other hand, decentralized power systems (DPS) reduce the obstacles to disaster preparation and recovery by allowing the focus to shift first to critical infrastructure and then to flow outward to less integrated outlets. A DG-based model for a smart micro-grid based on hybrid electric power systems (HEPS) using both renewable energy technologies (RET) and conventional power generation units is presented. The hybrid energy system may be portable or fixed in one place, highly reliable, easy to assemble, modular, flexible and cost-effective solution, that is ready-to-run and go to where it is needed to supply power in natural disaster

    Development of Microgrid Test Bed for Testing Energy Management System

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    Today the world population has reached 7.5 billion, and this number is expected to grow at the rate of 1.13% every year [1]. With this increase in population, the total demand for electricity has also increased. More people means the need for more power: electricity to power homes, schools, industries, hospitals, and so on. In today’s world, where most of the daily activities are dependent on electricity, demand for electricity, therefore, continues to rise. Currently, managing this growing need for electricity is one of the challenges the world is facing. In addition to this, approximately 1.2 billion people live in remote parts of the world where the electricity supply is either limited or non-existent [2]. Providing an affordable and easily available source of electricity to this population is another challenge. In response to these challenges, a significant number of countries are investing in the integration of renewable resources for energy production. Renewable resources such as the sun, wind, and water are free, clean, and readily available. Remote and poor parts of the world can also benefit by utilizing these available energy sources for electricity generation. The use of renewables helps to decrease the overall cost of electricity generation as well. This need for clean and safe energy has contributed to creating and promoting the concept of microgrids around the world. Microgrids are defined as small-scale power distribution networks with distributed energy sources, loads, and storage. They can operate in either grid-connected or islanded mode. Renewable sources are intermittent in nature, and uncertainties are always present in the microgrid operation when using these resources. The Energy Management technique is required for the coordination of these resources in order to mitigate the potential risks. Some studies have been conducted in the area of microgrid operation, stability, and control, and various types of laboratory-based microgrid test beds have been developed. A microgrid test bed allows testing of scaled down systems in order to test and simulate large real-world microgrid projects. The objective of this study is to develop a reconfigurable microgrid test bed. This test bed is created on a laboratory scale and is capable of testing energy management algorithms to validate real-time operation. A novel approach to automatic microgrid operation is proposed with the use of commercial off-the-shelf equipment and the Controller Area Network (CAN) protocol. The OPAL-RT 5600 real-time simulator is used as a central controller for controlling and scheduling microgrid sources to supply the load, charge the battery and, read a state of charge values. The CAN communication protocol is used by the controller to control and coordinate different components. Different cases are studied in order to support the reconfigurability, automatic operation, and energy management in the microgrid test bed using the CAN bus

    Komponentenbasierte dynamische Modellierung von Energiesystemen und Energiemanagement-Strategien für ein intelligentes Stromnetz im Heimbereich

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    The motivation of this work is to present an energy cost reduction concept in a home area power network (HAPN) with intelligent generation and flexible load demands. This study endeavors to address the energy management system (EMS) and layout-design challenges faced by HAPN through a systematic design approach. The growing demand for electricity has become a significant burden on traditional power networks, prompting power engineers to seek ways to improve their efficiency. One such solution is to integrate dispersed generation sources, such as photovoltaic (PV) and storage systems, with an appropriate control mechanism at the distribution level. In recent years, there has been a significant increase in interest in the installation of PV-Battery systems, due to their potential to reduce carbon emissions and lower energy costs. This research proposes an optimal economic power dispatch strategy using Model Predictive Control (MPC) to enhance the overall performance of HAPN. A hybrid AC/DC microgrid concept is proposed to address the control choices made by the appliance scheduling and hybrid switching approaches based on a linear programming optimization framework. The suggested optimization criteria improve consumer satisfaction, minimize grid disconnections, and lower overall energy costs by deploying inexpensive clean energy generation and control. Various examples from actual case study demonstrate the use of the established EMS and design methodology.Die Motivation dieser Arbeit besteht darin, ein Konzept zur Senkung der Energiekosten in einem Heimnetzwerk (HAPN) mit intelligenter Erzeugung und exiblen Lastanforderungen vorzustellen. Im Rahmen dieser Forschungsarbeit wird ein Entwurf für ein HAPN entwickelt, indem das Energiemanagementsystem (EMS) und der Entwurf des Layouts auf der Grundlage des Systemmodells und der betrieblichen Anforderungen gelöst werden. Die steigende Nachfrage nach Elektrizität ist für traditionelle Stromnetze kostspielig und infrastrukturintensiv. Daher konzentrieren sich Energietechniker darauf, die Effizienz der derzeitigen Netze zu erhöhen. Dies kann durch die Integration verteilter Erzeugungsanlagen (z. B. Photovoltaik (PV), Speicher) mit einem geeigneten Kontrollmechanismus für das Energiemanagement auf der Verteilungsseite erreicht werden. Darüber hinaus hat das Interesse an der Installation von PV-Batterie-basierten Systemen aufgrund der Reduzierung der CO2-Emissionen und der Senkung der Energiekosten erheblich zugenommen. Es wird eine optimale wirtschaftliche Strategie für den Energieeinsatz unter Verwendung einer modellprädiktiven Steuerung (MPC) entwickelt. Es wird zudem ein hybrides AC/DC-Microgrid-Konzept vorgeschlagen, um die Steuerungsentscheidungen, die von den Ansätzen der Geräteplanung und der hybriden Umschaltung getroffen werden, auf der Grundlage eines linearen Programmierungsoptimierungsrahmens zu berücksichtigen. Die vorgeschlagenen Optimierungskriterien verbessern die Zufriedenheit der Verbraucher, minimieren Netzabschaltungen und senken die Gesamtenergiekosten durch den Einsatz von kostengünstiger und sauberer Energieerzeugung. Verschiedene Beispiele aus einer Fallstudie demonstrieren den Einsatz des entwickelten EMS und der Entwurfsmethodik

    Use, Operation and Maintenance of Renewable Energy Systems:Experiences and Future Approaches

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    The aim of this book is to put the reader in contact with real experiences, current and future trends in the context of the use, exploitation and maintenance of renewable energy systems around the world. Today the constant increase of production plants of renewable energy is guided by important social, economical, environmental and technical considerations. The substitution of traditional methods of energy production is a challenge in the current context. New strategies of exploitation, new uses of energy and new maintenance procedures are emerging naturally as isolated actions for solving the integration of these new aspects in the current systems of energy production. This book puts together different experiences in order to be a valuable instrument of reference to take into account when a system of renewable energy production is in operation

    Study of Smart Grid Technology and Its Development in Indian Scenario

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    India is truculent to meet the electric power demands of a fast expanding economy. Restructuring of the power industry has only increased several challenges for the power system engineers. The proposed vision of introducing viable Smart Grid (SG) at various levels in the Indian power systems has recommended that an advanced automation mechanism needs to be adapted. Smart Grids are introduced to make the grid operation smarter and intelligent. Smart grid operations, upon appropriate deployment can open up new avenues and opportunities with significant financial implications. This work presents various Smart grid initiatives and implications in the context of power market evolution in India. Various examples of existing structures of automation in India are employed to underscore some of the views presented in this report. It also reviews the progress made in Smart grid technology research and development since its inception. Attempts are made to highlight the current and future issues involved for the development of Smart Grid technology for future demands in Indian perspective

    Optimised MOPSO with the grey relationship analysis for the multi-criteria objective energy dispatch of a novel SOFC-solar hybrid CCHP residential system in the UK

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    In the quest to achieve home comfort with the highest possible efficiency, there is an increasing interest in combined cooling, heating and power (CCHP) systems. These can be fuelled by natural gas and potentially by hydrogen enriched natural gas and ultimately by hydrogen. The optimised designs largely depend on the energy dispatch algorithms that take into account aspects of economic and environmental impacts as well as system efficiency. This paper details a new algorithm to optimise the operation of a novel hybrid solid oxide fuel cell (SOFC)-solar hybrid CCHP residential system. The proposed algorithm is based on the multi-objective particle swarm optimization (MOPSO) and the grey relationship analysis (GRA) (named as MOPSO-GRA) with the capability of resolving the objective energy dispatch issues within the system by effectively avoiding local optimum problem. More specifically, the grey incidences are first integrated into MOPSO to analyse the degree of closeness between non-ideal solutions and the ideal solution. Then, the relationship of degree is introduced to give objective energy dispatch in order to maximise the efficiency of energy utilization while minimising the system capital cost, operating costs, maintenance costs, fuel costs and emissions. Finally, the new algorithm is validated on the proposed new design of CCHP system. Ten cases are studied to evaluate the technical, economic and environmental performance of the MOPSO-GRA algorithm when being applied to an SOFC-based CCHP system under both the grid-connected and the island modes. A comparison is made with the conventional MOPSO method and system structure, and the impact of a plug-in EV is also evaluated. Based on a detailed cost and emissions analysis, the results indicate the environmental and economic advantages, in addition to the higher efficiency of the proposed methodology and system structure. The impact of these results and observations leads to the promotion of intelligent FC-based multi-energy system technologies for residential use
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