Optimization of energy storages in microgrid for power generation uncertainties

Microgrid is a cluster of distributed generation units, energy storages, and loads which can operate grid-connected and islanded. This research focuses on selecting an economic standalone supply system for small and remote off-grid towns in Western Australia. Existing power systems of such towns have adverse environmental impacts due to the utilization of diesel and gas. The suitable electricity supply system is a hybrid system composed of generators, renewables, and energy storages

Optimal Configuration and Sizing of Seaport Microgrids including Renewable Energy and Cold Ironing—The Port of Aalborg Case Study

Microgrids are among the promising green transition technologies that will provide enormous benefits to the seaports to manage major concerns over energy crises, environmental challenges, and economic issues. However, creating a good design for the seaport microgrid is a challenging task, considering different objectives, constraints, and uncertainties involved. To ensure the optimal operation of the system, determining the right microgrid configuration and component size at minimum cost is a vital decision at the design stage. This paper aims to design a hybrid system for a seaport microgrid with optimally sized components. The selected case study is the Port of Aalborg, Denmark. The proposed grid-connected structure consists of renewable energy sources (photovoltaic system and wind turbines), an energy storage system, and cold ironing facilities. The seaport architecture is then optimized by utilizing HOMER to meet the maximum load demand by considering important parameters such as solar global horizontal irradiance, temperature, and wind resources. Finally, the best configuration is analyzed in terms of economic feasibility, energy reliability, and environmental impacts

Operational Cost Minimization of Grid Connected Microgrid System Using Fire Fly Technique

oai:oai.jieee.a2zjournals.com:article/1Present time, green energy sources interfacing to the utility grid by utilizing microgrid system is very vital to satisfy the ever increasing energy demand. Optimal operation of the microgrid system improved the generation from the distributed renewable energy sources at the lowest operational cost. Large amount of constraints and variables are associated with the microgrid economic operation problem. Thus, this problem is very complex and required efficient technique for handing the problem adequately. This research utilized the fire fly optimization technique for solving the formulated microgrid operation problem. Fire fly algorithm is based on the behaviour and nature of the fire flies. A microgrid system modelling which incorporated various distributed energy sources such as solar photo voltaic, wind turbine, micro tur-bine, fuel cell, diesel generator, electric vehicle technology, etc.. Energy storage system is utilized in this research for supporting renewable energy sources’ integration in more reliable and qualitative way. Further, the electric vehicle technology i.e. battery electric vehicle, plug-in hybrid electric vehicle and fuel cell electric vehicle are utilized to support the microgrid and utility grid systems with respect to variable demands. Optimal operational cost-minimization problem of the developed microgrid system is solved by fire fly algorithm and compared with the grey wolf opti-mization and particle swarm optimization techniques. By comparative analysis it is clear that the fire fly algorithm provides the minimum operational cost of microgrid system as compared to the GWO and PSO. MATLAB software is utilized to model the microgrid system and implementation of the optimization techniques

Performance Optimisation of Standalone and Grid Connected Microgrid Clusters

Remote areas usually supplied by isolated electricity systems known as microgrids which can operate in standalone and grid-connected mode. This research focus on reliable operation of microgrids with minimal fuel consumption and maximal renewables penetration, ensuring least voltage and frequency deviations. These problems can be solved by an optimisation-based technique. The objective function is formulated and solved with a Genetic Algorithm approach and performance of the proposal is evaluated by exhaustive numerical analyses in Matlab

Thermoeconomic and environmental optimization of polygeneration systems for small-scale residential buildingsintegrating thermal and electric energy storage, renewable energy and legal restrictions.

El sector residencial, responsable del 27% del consumo energético mundial y 17% de emisiones de gases de efecto invernadero aproximadamente, desempeña un papel clave para combatir el cambio climático. Por esto, el uso de sistemas de poligeneración resulta una alternativa apropiada para cubrir las demandas energéticas de los edificios, ya que permiten un uso eficiente de los recursos naturales con un bajo impacto ambiental. En este sentido, esta tesis ha desarrollado un modelo de programación lineal entera mixta (MILP) para investigar estos sistemas de forma sistemática, integrando tecnologías renovables, como la solar y eólica, con almacenamiento de energía térmica y eléctrica, considerando equipos comerciales, teniendo en cuenta aspectos económicos y ambientales en el diseño. La investigación comienza por la forma de abordar el proceso de optimización, partiendo por la elección del método para seleccionar días representativos. Comparando diferentes métodos, se demuestra que su idoneidad depende en gran medida de la variabilidad de las series temporales involucradas en el sistema analizado. Además, se ha desarrollado un nuevo método que mejora los resultados del proceso de optimización. Por otro lado, se ha estudiado la viabilidad del uso de edificios residenciales como microrred. El estudio muestra que resultan rentables con respecto a los sistemas energéticos convencionales actuales, pero es necesario la aplicación de incentivos o permitir la venta de electricidad a un precio razonable para que sean competitivos. Adicionalmente, se han estudiado e identificado sinergias entre los componentes del sistema energético gracias al desarrollo de un modelo termoeconómico, que muestran la importancia de abordar el diseño de los sistemas energéticos considerando conjuntamente tecnologías térmicas y eléctricas, destacando la bomba de calor y los acumuladores de energía como tecnologías claves para lograr soluciones más económicas y sostenibles. Finalmente, se han aplicado las últimas regulaciones españolas de autoconsumo para evaluar su impacto económico y ambiental en el diseño de sistemas energéticos. Además, a través de la aplicación de la optimización multiobjetivo, se analizó si la reciente regulación de autoconsumo se ajusta a las metas europeas e internacionales para combatir el cambio climático. Asimismo, se estudia cómo podría abordarse la regulación para promover el desarrollo de sistemas energéticos sostenibles para el sector residencial. Los resultados sugieren actuar sobre la regulación de autoconsumo para reducir el impacto ambiental de forma efectiva. En general, esta tesis proporciona metodologías e ideas útiles para el diseño de sistemas energéticos sostenibles capaces de cubrir las demandas de energía de los edificios residenciales.The residential sector, responsible of about 27% of the global energy consumption and 17% of the greenhouse gas emissions, plays a key role in the action to combat climate change. In this sense, polygeneration systems could be considered a suitable alternative to attend the energy demands of residential buildings since they enable an efficient use of natural resources with a low environmental impact. This thesis developed a Mixed Integer Linear Programming (MILP) model to research these kind of systems in a systematic way to integrate renewable energy such as solar and wind energy with thermal and electric energy storage, considering commercial equipment for small-medium scale residential buildings, taking into account both economic and environmental aspects for the optimal design of such systems. The research starts from the suitable way to address the optimization process focused on the selection of the method to select representative days. Through the comparison of different methods, it was demonstrated that its right selection strongly depends on the variability of the time series involved in the analysed system. Besides, a new method was developed in order to improve the results of the optimization process. The developed MILP model was applied to study the feasibility of residential buildings as a microgrid. This innovative approach was found profitable with respect to the current conventional energy systems but it is necessary the application of feed-in tariff schemes or allowing the sale of electricity at reasonable price in order to make them competitive. Further, a thermoeconomic analysis was carried out to evaluate synergies between the components of the energy system. It was shown the importance of considering both thermal and electrical parts in the design of energy systems, highlighting the role of heat pumps and energy storage as key technologies, to achieve more cost-effective and sustainable solutions. Finally, the recent Spanish self-consumption regulations were applied to evaluate its impact on the design of energy systems. Moreover, through the application of multiobjective optimization and the analysis of different trade-off solutions was evaluated if this regulation aligned with European and international goals to combat climate change, and how it could be addressed in order to promote the design of affordable sustainable energy supply systems for the residential buildings. The obtained results suggest to act on the self-consumption regulation in order to achieve more significant reduction of greenhouse gas emissions. Overall, this thesis provided methodologies and useful insights for the design of sustainable energy systems for residential buildings.<br /

Inter-Microgrid Operation: Power Sharing, Frequency Restoration, Seamless Reconnection and Stability Analysis

Electrification in the rural areas sometimes become very challenging due to area accessibility and economic concern. Standalone Microgrids (MGs) play a very crucial role in these kinds of a rural area where a large power grid is not available. The intermittent nature of distributed energy sources and the load uncertainties can create a power mismatch and can lead to frequency and voltage drop in rural isolated community MG. In order to avoid this, various intelligent load shedding techniques, installation of micro storage systems and coupling of neighbouring MGs can be adopted. Among these, the coupling of neighbouring MGs is the most feasible in the rural area where large grid power is not available. The interconnection of neighbouring MGs has raised concerns about the safety of operation, protection of critical infrastructure, the efficiency of power-sharing and most importantly, stable mode of operation. Many advanced control techniques have been proposed to enhance the load sharing and stability of the microgrid. Droop control is the most commonly used control technique for parallel operation of converters in order to share the load among the MGs. But most of them are in the presence of large grid power, where system voltage and frequency are controlled by the stiff grid. In a rural area, where grid power is not available, the frequency and voltage control become a fundamental issue to be addressed. Moreover, for accurate load sharing a high value of droop gain should be chosen as the R/X ratio of the rural network is very high, which makes the system unstable. Therefore, the choice of droop gains is often a trade-off between power-sharing and stability. In the context, the main focus of this PhD thesis is the fundamental investigations into control techniques of inverter-based standalone neighbouring microgrids for available power sharing. It aims to develop new and improved control techniques to enhance performance and power-sharing reliability of remote standalone Microgrids. In this thesis, a power management-based droop control is proposed for accurate power sharing according to the power availability in a particular MG. Inverters can have different power setpoints during the grid-connected mode, but in the standalone mode, they all need their power setpoints to be adjusted according to their power ratings. On the basis of this, a power management-based droop control strategy is developed to achieve the power-sharing among the neighbouring microgrids. The proposed method helps the MG inverters to share the power according to its ratings and availability, which does not restrict the inverters for equal power-sharing. The paralleled inverters in coupled MGs need to work in both interconnected mode and standalone mode and should be able to transfer between modes seamlessly. An enhanced droop control is proposed to maintain the frequency and voltage of the MGs to their nominal value, which also helps the neighbouring MGs for seamless (de)coupling. This thesis also presents a mathematical model of the interconnected neighbouring microgrid for stability and robustness analysis. Finally, a laboratory prototype model of two MGs is developed to test the effectiveness of the proposed control strategies

A Resilient and Optimal Microgrid Scheduling Portfolio in Linear Programming Platform

In recent year, alarming rate of natural disasters around the world have demanded the need for operative solution in field of power generation, to control polluted energy sources which are major cause of global warming. Microgrid facilitates penetration of renewable energy sources into the existing distribution systems to reduce the overall carbon footprint of the globe by reducing the dependency on the main grid. Efficient but linear microgrid resource scheduling algorithms are gaining interest in present time due to its simplicity and fast computation. This research paper aims to serve the purposes by designing a mixed integer linear programming based microgrid scheduling problem while various types of scenario, minimize the electricity cost for the utilities also maintain the generation and load balance. The strategy is implemented on a small microgrid  to prove its efficacy .In this paper mainly optimal scheduling of microgrid has been done in various scenario, and obtained there global minimum electricity cost to the help of mixed integer linear programming (MILP) algorithm.  Microgrid is a small scale type of power grid, which provides the energy locally, its offers integration between distributed energy resources and the locally connected loads. Microgrid able to be operated with the main grid and in standalone mode also ability to transitions between these two modes, the mode of operation of microgrid is depends on the system operating condition. The reliability of power grid is improving more when it’s integrated with the Microgrid and works together. Power exchange with the upper stream grid is done through the point of common coupling (PCC). Microgrid having renewable energy resources i.e. PV, Wind and non-renewable energy resources, DG, FC, and MC connected with the Battery storage type system and locally connected loads. So it is a very reliable scenario, main grid with the microgrid, it is more beneficial, economy and stable types of system. Keywords: Optimal Microgrid Scheduling, Linear Programming DOI: 10.7176/APTA/76-05 Publication date:March 31st 2019

A multivariable optimal energy management strategy for standalone DC microgrids

Due to substantial generation and demand fluctuations in standalone green microgrids, energy management strategies are becoming essential for the power sharing and voltage regulation purposes. The classical energy management strategies employ the maximum power point tracking (MPPT) algorithms and rely on batteries in case of possible excess or deficit of energy. However, in order to realize constant current-constant voltage (IU) charging regime and increase the life span of batteries, energy management strategies require being more flexible with the power curtailment feature. In this paper, a coordinated and multivariable energy management strategy is proposed that employs a wind turbine and a photovoltaic array of a standalone DC microgrid as controllable generators by adjusting the pitch angle and the switching duty cycles. The proposed strategy is developed as an online nonlinear model predictive control (NMPC) algorithm. Applying to a sample standalone dc microgrid, the developed controller realizes the IU regime for charging the battery bank. The variable load demands are also shared accurately between generators in proportion to their ratings. Moreover, the DC bus voltage is regulated within a predefined range, as a design parameter