Electric Power Conversion and Micro-Grids

This edited volume is a collection of reviewed and relevant research chapters offering a comprehensive overview of recent achievements in the field of micro-grids and electric power conversion. The book comprises single chapters authored by various researchers and is edited by a group of experts in such research areas. All chapters are complete in themselves but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on electric power conversion, micro-grids, and their up-to-the-minute technological advances and opens new possible research paths for further novel developments

Modeling, Simulation and Control of Wind Diesel Power Systems

Wind diesel power systems (WDPSs) are isolated microgrids that combine diesel generators (DGs) with wind turbine generators (WTGs). Often, WDPS are the result of adding WTGs to a previous existing diesel power plant located in a remote place where there is an available wind resource. By means of power supplied by WTGs, fuel consumption and CO2 emissions are reduced. WDPSs are isolated power systems with low inertia where important system frequency and voltage variations occur. WDPS dynamic modeling and simulation allows short-term simulations to be carried out to obtain detailed electrical variable transients so that WDPS stability and power quality can be tested. This book includes papers on several subjects regarding WDPSs: the main topic of interest is WDPS dynamic modeling and simulation, but related areas such as the sizing of the different WDPS components, studies concerning the control of WDPSs or the use of energy storage systems (ESSs) in WDPSs and the benefits that ESSs provide to WDPS are also discussed. The book also deals with related AC isolated microgrids, such as wind-hydro microgrids or wind-photovoltaic-diesel microgrids

Robust fuzzy-sliding mode based UPFC controller for transient stability analysis in autonomous wind-diesel-PV hybrid system

This study presents a comparative study of transient stability and reactive power compensation issues in an autonomous wind–diesel-photovoltaic based hybrid system (HS) using robust fuzzy-sliding mode based unified power flow controller (UPFC). A linearised small-signal model of the different elements of the HS is considered for the transient stability analysis in the HS under varying loading conditions. An IEEE type 1 excitation system is considered for the synchronous generator in the HS, with negligible saturation characteristic, for detailed voltage stability analysis. It is noted from the simulation results that the performance of UPFC is superior to static VAR compensator and static synchronous compensator in improving the voltage profile of the HS. Further, fuzzy and fuzzy-sliding mode based UPFC controller is designed in order to improve the transient performance. Simulation results reflect the robustness of the proposed fuzzy-sliding mode controller for better reactive power management to improve the voltage stability in comparison with the conventional PI and fuzzy-PI controllers. In addition to this, system stability analysis is performed based on eigenvalue, bode and popov for supporting the robustness of the proposed controller

Power Flow Control of the Grid-Integrated Hybrid DG System using an ARFMF Optimization

A power flow control scheme for a grid-integrated Hybrid DG System (HDGS) is presented in this work, utilizing an advanced random forest algorithm combined with the moth-flame optimization (ARFMF) approach. The proposed control scheme combines the random forest algorithm (RFA) and moth-flame optimization algorithm (MFO) for consolidated execution. The random forest algorithm (RFA), an AI technique, is well-suited for nonlinear systems due to its accurate interpolation and extrapolation capabilities. It is an ensemble learning method that combines multiple decision trees to make predictions. The algorithm constructs a forest of decision trees and aggregates their predictions to produce the final output. The moth-flame optimization (MFO) process is a meta-heuristic optimization procedure inspired by the transverse orientation of moths in nature. It improves initial random solutions and converges to superior positions in the search area. Similarly, the MFO is effective in nonlinear systems as it accurately interpolates and extrapolates arbitrary information. In the proposed technique, the RFA performs the calculation process to determine precise control gains for the HDGS through online implementation based on power variation between the source side and the load side. The recommended dataset is used to implement the AI approach for online execution, reducing optimization process time. The learning process of the RFA is guided by the MFO optimization algorithm. The MFO technique defines the objective function using system information based on equal and unequal constraints, including the accessibility of renewable energy sources, power demand, and state of charge (SOC) of storage systems. Storage devices such as batteries stabilize the energy generated by renewable energy systems to maintain a constant, stable output power. The proposed model is implemented on the MATLAB/Simulink platform, and its execution is compared to previous approaches

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

Emerging Technologies for the Energy Systems of the Future

Energy systems are transiting from conventional energy systems to modernized and smart energy systems. This Special Issue covers new advances in the emerging technologies for modern energy systems from both technical and management perspectives. In modern energy systems, an integrated and systematic view of different energy systems, from local energy systems and islands to national and multi-national energy hubs, is important. From the customer perspective, a modern energy system is required to have more intelligent appliances and smart customer services. In addition, customers require the provision of more useful information and control options. Another challenge for the energy systems of the future is the increased penetration of renewable energy sources. Hence, new operation and planning tools are required for hosting renewable energy sources as much as possible

Fuzzy logic control of hybrid systems including renewable energy in microgrids

With a growing demand for more energy from subscribers, a traditional electric grid is unable to meet new challenges, in the remote areas remains the extension of the conventional electric network very hard to do make prohibitively expensive. Therefore, a new advanced generation of traditional electrical is inevitable and indispensable to move toward an efficient, economical, green, clean and self-correcting power system. The most well-known term used to define this next generation power system is Micro Grid (MG) based on renewable energy sources (RES). Since, the energy produced by RES are not constant at all times, a wide range of energy control techniques must be involved to provide a reliable power to consumers. To solve this problem in this paper we present a Fuzzy Logic Control of isolated Hybrid Systems (HRES) Including Renewable Energy in Micro-Grids to maintain a stability in voltage and frequency output especially in the standalone application. The considered HRES combine a wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on battery as a backup solution. Simulation results obtained from MATLAB/Simulink environment demonstrate the effectiveness of the proposed algorithm in decreasing the electricity bill of customer