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

A comparison of fuzzy-based energy management systems adjusted by nature-inspired algorithms

The growing energy demand around the world has increased the usage of renewable energy sources (RES) such as photovoltaic and wind energies. The combination of traditional power systems and RESs has generated diverse problems due especially to the stochastic nature of RESs. Microgrids (MG) arise to address these types of problems and to increase the penetration of RES to the utility network. A microgrid includes an energy management system (EMS) to operate its components and energy sources efficiently. The objectives pursued by the EMS are usually economically related to minimizing the operating costs of the MG or maximizing its income. However, due to new regulations of the network operators, a new objective related to the minimization of power peaks and fluctuations in the power profile exchanged with the utility network has taken great interest in recent years. In this regard, EMSs based on off-line trained fuzzy logic control (FLC) have been proposed as an alternative approach to those based on on-line optimization mixed-integer linear (or nonlinear) programming to reduce computational efforts. However, the procedure to adjust the FLC parameters has been barely addressed. This parameter adjustment is an optimization problem itself that can be formulated in terms of a cost/objective function and is susceptible to being solved by metaheuristic nature-inspired algorithms. In particular, this paper evaluates a methodology for adjusting the FLC parameters of the EMS of a residential microgrid that aims to minimize the power peaks and fluctuations on the power profile exchanged with the utility network through two nature-inspired algorithms, namely particle swarm optimization and differential evolution. The methodology is based on the definition of a cost function to be optimized. Numerical simulations on a specific microgrid example are presented to compare and evaluate the performances of these algorithms, also including a comparison with other ones addressed in previous works such as the Cuckoo search approach. These simulations are further used to extract useful conclusions for the FLC parameters adjustment for off-line-trained EMS based designs.This work is part of the projects 2019-PIC-003-CTE and 2020-EXT-007 from the Research Group of Propagation, Electronic Control, and Networking (PROCONET) of Universidad de las Fuerzas Armadas ESPE. This work has been developed with the support of VLIR-UOS and the Belgian Development Cooperation (DGD) under the project EC2020SIN322A101. This work has been partially supported by the Spanish Ministry of Industry and Competitiveness under the grant DPI2017-85404 and PID2019-111443RB-100.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version

An energy management system design using fuzzy logic control: smoothing the grid power profile of a residential electro-thermal microgrid

© 2021 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 works.This work deals with the design of a Fuzzy Logic Control (FLC) based Energy Management System (EMS) for smoothing the grid power profile of a grid-connected electro-thermal microgrid. The case study aims to design an Energy Management System (EMS) to reduce the impact on the grid power when renewable energy sources are incorporated to pre-existing grid-connected household appliances. The scenario considers a residential microgrid comprising photovoltaic and wind generators, flat-plate collectors, electric and thermal loads and electrical and thermal energy storage systems and assumes that neither renewable generation nor the electrical and thermal load demands are controllable. The EMS is built through two low-complexity FLC blocks of only 25 rules each. The first one is in charge of smoothing the power profile exchanged with the grid, whereas the second FLC block drives the power of the Electrical Water Heater (EWH). The EMS uses the forecast of the electrical and thermal power balance between generation and consumption to predict the microgrid behavior, for each 15-minute interval, over the next 12 hours. Simulations results, using real one-year measured data show that the proposed EMS design achieves 11.4% reduction of the maximum power absorbed from the grid and an outstanding reduction of the grid power profile ramp-rates when compared with other state-of-the-art studies.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version

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

Electric thermal storage in isolated wind diesel power systems: use of distributed secondary loads for frequency regulation

Thesis (Ph.D.) University of Alaska Fairbanks, 2017Isolated coastal utilities in Arctic villages commonly use a mix of diesel and wind power to provide electrical service to their consumers. It is common for such communities to experience periods of high wind generation for which no immediate demand exists and either waste, curtail, or poorly utilize the surplus. The objective of the present work is to explore (through mathematical and numerical modelling) the technical feasibility of and optimization strategies for distributing this excess wind energy as domestic space heat for use as a cleaner, more economical alternative to fossil fuels. Autonomously controlled Electric Thermal Storage (ETS) devices are considered as a solution to decouple the supply of excess wind power with domestic heat demand without the need for communication infrastructure or a second distribution circuit. First, using numerical heat transfer analysis, it is shown that the performance of an ETS heater core can be generalized and expressed in terms of its physical properties and simple geometric dimensions in such a way as to inform system sizing and economic performance studies for prospective applications. Furthermore, a collection of autonomous ETS units is shown (using a full-scale lab-validated mathematical model) to possess the ability to assume the role of partial and/or sole frequency regulator on a hybrid wind-diesel system. Several design changes are proposed, which render the commercially-available units more amenable to frequency regulation. Ultimately, ETS is shown to be a promising alternative means of utilizing excess renewable energy for domestic space heat while providing additional stability to the electrical grid.Chapter 1 Introduction -- 1.1 Hybrid Wind-Diesel Systems -- 1.2 Frequency Regulation -- 1.3 Voltage Regulation -- 1.4 Energy Storage -- 1.5 Secondary Loads -- 1.6 Electric Thermal Storage -- 1.7 Summary and Organization of Subsequent Chapters -- 1.8 Nomenclature -- 1.9 References -- Chapter 2 Summary of Measurement and Modeling Methodologies -- 2.1 Numerical Heat Transfer - Measurement -- 2.2 Numerical Heat Transfer - Physical Modeling -- 2.3 Electromechanical Dynamics - Measurement -- 2.3.1 Field Measurements -- 2.3.2 Raw Data -- 2.3.3 Post Processing: RMS Values -- 2.3.4 Post Processing: Frequency and Power Factor -- 2.3.5 Post Processing: Impedance, Real Power, and Reactive Power -- 2.4 Electromechanical Dynamics - Modeling -- 2.4.1 Model Structure -- 2.4.2 Equivalent Circuit Simulation Process -- 2.4.3 Solution of Nonlinear Ordinary Differential Equations (ODEs) -- 2.5 References -- Chapter 3 Generalized Heat Flow Model of a Forced Air Electric Thermal Storage Heater Core -- 3.1 Abstract -- 3.2 Introduction -- 3.3 Model -- 3.3.1 Definitions -- 3.3.2 Structure -- 3.3.3 Governing Equations -- 3.3.4 Boundary Conditions -- 3.3.5 Material Properties -- 3.4 Analysis -- 3.4.1 Solution Linearization and Air Velocity Profile -- 3.4.2 Thermal Gradients -- 3.4.3 Parameter Sweep -- 3.5 Results and Discussion -- 3.5.1 One-parameter Model -- 3.5.2 Two-parameter Model -- 3.5.3 Core Energy Balance -- 3.5.4 Stove Modelling -- 3.6 Conclusions -- 3.7 Acknowledgements -- 3.8 Funding -- 3.9 Nomenclature -- 3.10 References -- Chapter 4 Development of a Full-Scale-Lab-Validated Dynamic Simulink© Model for a Stand-Alone -- Wind-Powered Microgrid -- 4.1 Abstract -- 4.2 Introduction -- 4.3 Mathematical Model -- 4.3.1 Diesel Engine/Governor Model -- 4.3.2 Synchronous Generator Model -- 4.3.3 Excitation System Model -- 4.3.4 Induction Generator Model -- 4.4 Data Collection -- 4.5 Results -- 4.5.1 Data Processing -- 4.5.2 Diesel Only (DO) Mode - Laboratory Results -- 4.5.3 Diesel Only (DO) Mode - Simulation Results -- 4.5.4 Wind-Diesel (WD) Mode -- 4.6 Conclusions -- 4.7 Future Work -- 4.8 Acknowledgements -- 4.9 References -- Chapter 5 Frequency Regulation by Distributed Secondary Loads on Islanded Wind-Powered Microgrids -- 5.1 Abstract -- 5.2 Introduction -- 5.3 Mathematical Model -- 5.3.1 Wind-Diesel Hybrid System -- 5.3.2 Individual ETS Units Response -- 5.3.3 Aggregate DSL Response -- 5.4 Analysis -- 5.4.1 Invariant Model Inputs (Machine Parameters) -- 5.4.2 Variable Model Inputs -- 5.4.3 Model Outputs -- 5.5 Results and Discussion -- 5.5.1 Synchronized Switching -- 5.5.2 Staggered Switching -- 5.5.3 Additional Observations and Discussion -- 5.6 Conclusion and Future Work -- 5.7 References -- Chapter 6 Modelling Integration Strategies for Autonomous Distributed Secondary Loads on High Penetration Wind-Diesel Microgrids -- 6.1 Abstract -- 6.2 Introduction -- 6.3 Model -- 6.3.1 System Requirements -- 6.3.2 System Components -- 6.3.3 Control Strategy -- 6.4 Results and Discussion -- 6.4.1 Ramp Simulation -- 6.4.2 Representative Simulation -- 6.4.3 Design Considerations -- 6.5 Conclusions -- 6.6 Acknowledgements -- 6.7 References -- Chapter 7 Results and Observations -- 7.1 Result and Observations of Chapter 3 -- 7.2 Results and Observations of Chapter 4 -- 7.3 Results and Observations of Chapter 5 -- 7.4 Results and Observations of Chapter 6 -- Chapter 8 Conclusions -- 8.1 Conclusions for Generalized Heat Flow Model of a Forced Air Electric Thermal Storage Heater Core -- 8.2 Conclusions for Development of a Full-Scale-Lab-Validated Dynamic Simulink© Model for a Stand-Alone Wind-Powered Microgrid -- 8.3 Conclusions for Frequency Regulation by Distributed Secondary Loads (DSLs) on Islanded Wind-Powered Microgrids -- 8.4 Conclusions for Modeling Integration Strategies for Autonomous Distributed Secondary Loads on High Penetration Wind-Diesel Microgrids -- 8.5 Suggestions for Future Research -- 8.6 Overall Conclusions -- 8.7 Acknowledgements

Recent techniques used in home energy management systems: a review

Power systems are going through a transition period. Consumers want more active participation in electric system management, namely assuming the role of producers–consumers, prosumers in short. The prosumers’ energy production is heavily based on renewable energy sources, which, besides recognized environmental benefits, entails energy management challenges. For instance, energy consumption of appliances in a home can lead to misleading patterns. Another challenge is related to energy costs since inefficient systems or unbalanced energy control may represent economic loss to the prosumer. The so-called home energy management systems (HEMS) emerge as a solution. When well-designed HEMS allow prosumers to reach higher levels of energy management, this ensures optimal management of assets and appliances. This paper aims to present a comprehensive systematic review of the literature on optimization techniques recently used in the development of HEMS, also taking into account the key factors that can influence the development of HEMS at a technical and computational level. The systematic review covers the period 2018–2021. As a result of the review, the major developments in the field of HEMS in recent years are presented in an integrated manner. In addition, the techniques are divided into four broad categories: traditional techniques, model predictive control, heuristics and metaheuristics, and other techniques.info:eu-repo/semantics/publishedVersio

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