Energy management based on a fuzzy controller of a photovoltaic/fuel cell/Li-ion battery/supercapacitor for unpredictable, fluctuating, high-dynamic three-phase AC load

Introduction. Nowadays, environmental pollution becomes an urgent issue that undoubtedly influences the health of humans and other creatures living in the world. The growth of hydrogen energy increased 97.3 % and was forecast to remain the world’s largest source of green energy. It can be seen that hydrogen is one of the essential elements in the energy structure as well as has great potential to be widely used in the 21st century. Purpose. This paper aims to propose an energy management strategy based a fuzzy logic control, which includes a hybrid renewable energy sources system dedicated to the power supply of a three-phase AC variable load (unpredictable high dynamic). Photovoltaic (PV), fuel cell (FC), Li-ion battery, and supercapacitor (SC) are the four sources that make up the renewable hybrid power system; all these sources are coupled in the DC-link bus. Unlike usual the SC was connected to the DC-link bus directly in this research work in order to ensure the dominant advantage which is a speedy response during load fast change and loads transient. Novelty. The power sources (PV/FC/Battery/SC) are coordinated based on their dynamics in order to keep the DC voltage around its reference. Among the main goals achieved by the fuzzy control strategy in this work are to reduce hydrogen consumption and increase battery lifetime. Methods. This is done by controlling the FC current and by state of charge (SOC) of the battery and SC. To verify the fuzzy control strategy, the simulation was carried out with the same system and compared with the management flowchart strategy. The results obtained confirmed that the hydrogen consumption decreased to 26.5 g and the SOC for the battery was around 62.2-65 and this proves the desired goal.Вступ. В даний час забруднення навколишнього середовища стає актуальною проблемою, яка, безперечно, впливає на здоров’я людини та інших істот, які живуть у світі. Зростання водневої енергетики збільшилося на 97,3 %, і прогнозувалося, що вона залишиться найбільшим у світі джерелом зеленої енергії. Видно, що водень є одним із найважливіших елементів у структурі енергетики, а також має великий потенціал для широкого використання у 21 столітті. Мета. У цій статті пропонується стратегія управління енергоспоживанням, заснована на нечіткому логічному управлінні, яка включає гібридну систему відновлюваних джерел енергії, призначену для живлення трифазного змінного навантаження змінного струму (непередбачувана висока динаміка). Фотоелектричні (PV), паливні елементи (FC), літій-іонні батареї та суперконденсатори (SC) – це чотири джерела, з яких складається відновлювана гібридна енергосистема; всі ці джерела підключені до шини постійного струму. На відміну від звичайних застосувань,ув цій дослідницькій роботі SC був підключений до шини постійного струму безпосередньо, щоб забезпечити домінуючу перевагу, що полягає в швидкому реагуванні при швидкій зміні навантаження та перехідних режимах навантаження. Новизна. Джерела живлення (PV/FC/батареї/SC) координуються на основі їхньої динаміки, щоб підтримувати напругу постійного струму біля свого еталонного значення. Серед основних цілей, досягнутих стратегією нечіткого управління у цій роботі, - зниження споживання водню та збільшення терміну служби батареї. Методи. Це робиться шляхом керування струмом FC та станом заряду (SOC) батареї та SC. Для перевірки стратегії нечіткого управління було проведено моделювання з тією самою системою та порівняння зі стратегією блок-схеми керування. Отримані результати підтвердили, що споживання водню знизилося до 26,5 г, а SOC для батареї становило близько 62,2-65, що доводить досягнення бажаної мети

Fuzzy logic power management for a PV/Wind microgrid with backup and storage systems

This work introduces a power management scheme based on the fuzzy logic controller (FLC) to manage the power flows in a small and local distributed generation system. The stand-alone microgrid (MG) includes wind and PV generators as main power sources. The backup system includes a battery storage system (BSS) and a diesel generator (DG) combined with a supercapacitor (SC). The different energy sources are interconnected through the DC bus. The MG is modeled using MATLAB/Simulink Sim_Power System™. The SC is used to compensate for the shortage of power during the start-up of the DG and to compensate for the limits on the charging/discharging current of the BSS. The power balance of the system is the chief objective of the proposed management scheme. Some performance indexes are evaluated: the frequency-deviation, the stability of the DC bus voltage, and the AC voltage total harmonic distortion. The performance of the planned scheme is assessed by two 24-hours simulation sets. Simulation results confirm the effectiveness of FLC-based management. Moreover, the effectiveness of the FLC approach is compared with the deterministic approach. FLC approach has saved 18.7% from the daily load over the deterministic approach. The study shows that the quality of the power signal in the case of FLC is better than the deterministic approach

Energy management strategies based on fuzzy logic control for grid-tied domestic electro-thermal microgrid

The environmental and economic benefits related to the reduction of both carbon dioxide emission and transmission losses have made distributed renewable generation systems became a competitive solution for future power systems. In this context, Microgrids (MG) are considered as the key building blocks of smart grids and have aroused great attention in the last decade for their potential and the impact they may have in the coming future. The MG concept has captured great attention in the last years since it can be considered one of the most suitable alternatives for integration of distributed generation units in the utility grid. However, this integration involves some challenges to deal with especially when penetration of Renewable Energy Sources (RES) into the distribution network is increased. Therefore, an effective Energy Management System (EMS) is required to ensure optimal energy utilization within the MG, consequently, facilitating both the grid integration and operator control. In this regard, the EMS strategy design depends on the application, MG power architecture, and the power management capability of the MG elements. This dissertation research focuses on the design of different EMS strategies based on Fuzzy Logic Control (FLC) for a residential grid-connected electro-thermal MG including renewable power generation (i.e. photovoltaic and wind turbine generators) and storage capability (i.e. battery bank and water storage tank). The main goal of the FLC-based EMS strategies is to minimize the grid power fluctuations while keeping the battery State-of-Charge (SOC) within secure limits. In order to accomplish this goal, the controller design parameters, such as membership functions and rule-base, of the FLC-based EMS strategies, are adjusted to optimize a pre-defined set of quality criteria of the MG behavior. The analysis and design of the FLC-based EMS strategies for electrical and electro-thermal MG power architectures are developed considering two different scenarios. A first scenario where the MG power forecasting is not provided and a second scenario where the forecast of generation power and load demand are considered. A comparison with the different EMS strategies is presented in simulation level, whereas the features of the enhanced FLC-based EMS strategies are experimentally tested on a real residential microgrid implemented at the Public University of Navarre (UPNa)Este estudio presenta el diseño de diferentes estrategias de gestión energética basadas en un controlador difuso para una microrred electro-térmica residencial conectada a la red eléctrica compuesta por generadores de energía renovable (solar y eólico) y elementos de almacenamiento de energía (banco de baterías y tanque de almacenamiento de agua). El objetivo principal de las estrategias de gestión es reducir los picos y fluctuaciones de potencia en el perfil de potencia intercambiado con la red eléctrica y preservar la vida útil del sistema de almacenamiento. Se presenta una revisión del estado del arte de estudios anteriores que buscan este objetivo. Se muestra el análisis de dos arquitecturas de microrred. La primera arquitectura consiste en una microrred eléctrica compuesta fuentes de energía renovables, sistema de almacenamiento de energía y el consumo eléctrico de una vivienda. La segunda arquitectura consiste en una microrred electro-térmica que contiene los elementos de la microrred eléctrica e incluye adicionalmente generadores térmicos y el consumo térmico de la vivienda. Con el objetivo de medir la eficiencia de las diferentes estrategias de gestión, se presenta un conjunto de criterios de evaluación que analizan la calidad del perfil de potencia intercambiado con la red eléctrica obtenido mediante las diferentes estrategias de gestión energética. Estos criterios de calidad son utilizados adicionalmente para la optimización de parámetros de los controladores difusos, lo cual se realiza mediante un proceso de aprendizaje fuera de línea que considera los datos históricos del comportamiento de la microrred. La comparación entre las diferentes estrategias de gestión energética se realiza mediante simulación, utilizando los datos reales de generación y consumo adquiridos en la Universidad Pública de Navarra durante el período comprendido entre Julio 2013 y Julio 2014. El diseño de las estrategias de gestión energética para la arquitectura de microrred eléctrica supone dos posibles escenarios, el primer escenario no considera la previsión de consumo y generación de la microrred, y el segundo escenario si considera esta previsión. Las prestaciones de las estrategias basadas en control difuso para cada uno de estos escenarios son validadas experimentalmente en condiciones reales en la microrred de la Universidad Pública de Navarra. Finalmente, se presenta el análisis de las estrategias de gestión basadas en control difuso empleadas a la arquitectura de microrred electro-térmica. La comparación, mediante simulación, con otras estrategias de gestión aplicadas a la misma arquitectura ha demostrado el correcto desempeño de las estrategias desarrolladas basadas en control difuso.Postprint (published version

Energy Management Strategy Using ANFIS Approach for Hybrid Power System

Renewable Energy Sources are the promising hopes of upcoming years as they are abundant in nature and available free of cost. In addition to this, these sources are pollution-free which makes them a perfect substitute for fossil fuels. A Hybrid Power System (HPS) is one that has multiple power generating sources like Photo Voltaic (PV) system, Wind turbine, Fuel cell, etc. interconnected to supply electric power for varying demand requirements with / without energy storage backup. This paper concentrates on the automation for control and integration of Renewable energy systems Viz. PV system, Solid Oxide Fuel Cell (SOFC) with Nickel-Metal-Hydride (Ni-MH) battery together with a variable load. The Proposed HPS mainly focuses on the use of PV which is 100% clean in nature with no toxic emissions on power generation. Here, the solar photovoltaic system with power extracting maximum by algorithm used as the major supply contributor in the HPS to meet with variable load demands. If there is a deficit of power supply from PV, the power from the Ni-MH battery / SOFC is utilized to meet the varying load demands. On the other hand, if there is excess supply from PV system, the excess energy will be stored in the Ni-MH battery. For efficient supply-demand balance, the HPS makes use of various control strategies namely Proportional Integral (PI) and Adaptive Neuro Fuzzy Inference System (ANFIS)

Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting

This paper presents the design of an energy management strategy based on a low complexity Fuzzy Logic Control (FLC) for grid power profile smoothing of a residential grid-connected microgrid including Renewable Energy Sources (RES) and battery Energy Storage System (ESS). The proposed energy management strategy uses generation and demand forecasting to anticipate the future behavior of the microgrid. Accordingly to the microgrid power forecast error and the Battery State-of-Charge (SOC) the proposed strategy performs the suitable control of the grid power. A simulation comparison with previous energy management strategies highlights the advantages of the proposed work minimizing fluctuations and power peaks in the power profile exchanged with the grid while keeping the energy stored in the battery between secure limits. Finally, the experimental validation in a real residential microgrid implemented at Public University of Navarre (UPNa, Spain) demonstrates the proper operation of the proposed strategy achieving a smooth grid power profile and a battery SOC center close to the 75% of the rated battery capacity.Peer ReviewedPostprint (author's final draft

Switched Capacitor Nine-level inverter with reduced components for Grid connected PV systems using Fuzzy logic controller

The novel use of a three-phase switched capacitor SC nine-level inverter in a PV system is described in this article. It has a low input voltage, fewer components, and is grid-connected. The primary benefit of the suggested inverter is high voltage gain, which is attained by switching capacitors in series and parallel to raise the output voltage with the proper switching management. It is simpler to design a fuzzy logic controller to increase the infusion of solar energy into the electrical network. The MATLAB/Simulink environment's findings demonstrate that the suggested fuzzy logic controller performs well under a range of illumination levels. In comparison to the traditional PI controller, the total harmonic distortion (THD) obtained is less than the limit of 0.67 %. Good spectrum analysis and strong performance with fewer components are made possible by the nine-level SC inverter

Fuzzy logic-based energy management system for grid-connected residential DC microgrids with multi-stack fuel cell systems: A multi-objective approach

Hybrid energy storage systems (HESS) are considered for use in renewable residential DC microgrids. This architecture is shown as a technically feasible solution to deal with the stochasticity of renewable energy sources, however, the complexity of its design and management increases inexorably. To address this problem, this paper proposes a fuzzy logic-based energy management system (EMS) for use in grid-connected residential DC microgrids with HESS. It is a hydrogen-based HESS, composed of batteries and multi-stack fuel cell system. The proposed EMS is based on a multivariable and multistage fuzzy logic controller, specially designed to cope with a multi-objective problem whose solution increases the microgrid performance in terms of efficiency, operating costs, and lifespan of the HESS. The proposed EMS considers the power balance in the microgrid and its prediction, the performance and degradation of its subsystems, as well as the main electricity grid costs. This article assesses the performance of the developed EMS with respect to three reference EMSs present in the literature: the widely used dual-band hysteresis and two based on multi-objective model predictive control. Simulation results show an increase in the performance of the microgrid from a technical and economic point of view.Thisresearchwasfundedby‘‘H2Integration&Control.IntegrationandControlofahydrogen-basedpilotplantinresidentialapplicationsforenergysupply’’SpanishGovernment,grant Ref:PID2020-116616RB-C31’’,‘‘SALTES:SmartgridwithreconfigurableArchitecturefortestingcontroLTechniquesandEnergy Storagepriority’’byAndalusianRegionalProgramofR+D+i,grant Ref:P20-00730,andbytheproject‘‘Thegreenhydrogenvector. Residentialandmobilityapplication’’,approvedinthecallfor researchprojectsoftheCepsaFoundationChairoftheUniversity ofHuelva.Fundingforopenaccesscharge:UniversidaddeHuelva /CBUA

Energy management control strategy for renewable energy system based on spotted hyena optimizer

Hydrocarbons, carbon monoxide and other pollutants from the transportation sector harm human health in many ways. Fuel cell (FC) has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy. The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand. Therefore, adding energy storage systems is necessary. However, to manage and distribute the power-sharing among the hybrid proton exchange membrane (PEM) fuel cell (FC), battery storage (BS), and supercapacitor (SC), an energy management strategy (EMS) is essential. In this research work, an optimal EMS based on a spotted hyena optimizer (SHO) for hybrid PEM fuel cell/BS/SC is proposed. The main goal of an EMS is to improve the performance of hybrid FC/BS/SC and to reduce the amount of hydrogen consumption. To prove the superiority of the SHO method, the obtained results are compared with the chimp optimizer (CO), the artificial ecosystem-based optimizer (AEO), the seagull optimization algorithm (SOA), the sooty tern optimization algorithm (STOA), and the coyote optimization algorithm (COA). Two main metrics are used as a benchmark for the comparison: the minimum consumed hydrogen and the efficiency of the system. The main findings confirm that the minimum amount of hydrogen consumption and maximum efficiency are achieved by the proposed SHO based EMS