Integration of Fuel Cell Technologies in Renewable-Energy-Based Microgrids Optimizing Operational Costs and Durability

In this paper, a Model Predictive Control (MPC) approach is proposed to manage a grid-tied hydrogen microgrid (μG) . The μG testbed is equipped with a 1-kW polymer electrolyte membrane (PEM) electrolyzer and a 1.5-kW PEM fuel cell as main equipment. In particular, we present a formulation that includes the cost of the electricity exported/imported, the aging of the components, and the operational constraints. The control objective is to satisfy user demand, as well as extend the lifespan of expensive equipment, as is the case of the fuel cell or the electrolyzer. μG performance is investigated under realistic scenarios in three experiments. The experimental results illustrate how the proposed control system is able to manage the fuel cell and the electrolyzer through smooth power references, as well as to satisfy the power demanded. Finally, benchmarking is carried out between hysteresis band (HB) control and the proposed MPC in regard to efficiency and cost of the operation. The results obtained show that the MPC approach is more effective than HB for this type of μG , with a reduction in operation cost of up to 30%

On the Comparison of Stochastic Model Predictive Control Strategies Applied to a Hydrogen-based Microgrid

In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.Ministerio de Economía y Competitividad DPI2013-46912-C2-1-RMinisterio de Economía y Competitividad DPI2013-482443-C2-1-

Reliability and energy costs analysis of a rural hybrid microgrid using measured data and battery dynamics: a case study in the coast of Perú

Hybrid microgrids constitute a promising solution for filling the electricity access gap that currently exists in rural areas; however, there is still relatively little information about their reliability and costs based on measured data in real working conditions. This article analyzes data obtained from the operation of a 9 kW hybrid microgrid in the fishermen’s cove of Laguna Grande, Paracas, in the Ica region of Perú, which has been running for 5 years. This microgrid has been equipped with data acquisition systems that measure and register wind speed, solar radiation, temperatures, and all the relevant electric parameters. Battery dynamics considerations are used to determine the depth of discharge in a real-time operative situation. The collected data are used to optimize the design using the specialized software HOMER, incorporating state-of-the-art technology and costs as a possible system upgrade. This work aims to contribute to better understanding the behavior of hybrid rural microgrids using data collected under field conditions, analyzing their reliability, costs, and corresponding sensitivity to battery size as well as solar and wind installed power, as a complement to a majority of studies based on simulations.Peer ReviewedPostprint (published version

Greenhouse electrification via transactive energy management strategy

Distributed energy resources have grown significantly in Canada and the world over the past decade, particularly in the agricultural sector. As P2P (peer-to-peer) energy trading plays a fundamental role in renewable energy uptake and system flexibility for the low-carbon energy transition, this paper provides an overview of this approach from a techno-economic standpoint for two greenhouses located in Leamington, Ontario. The real-time site solar irradiation, ambient temperature, and load demand over 8760 h have been utilized to drive the designs. In this investigation, two cases are assessed for pepper greenhouse: Case I: energy purchase from the grid and Case II: energy purchase from excess energy of neighbor which is cucumber-tomato greenhouse. The integration of 50 kW PV/1 kWh battery/35 kW converter achieves the feasibility criteria by recording net present cost (NPC) and cost of energy (COE), which are $29.6k and$0.044/kWh, respectively

Optimal integration of wind energy with a renewable based microgrid for industrial applications.

Wind energy in urban environments is a rapidly developing technology influenced by the terrain specifications, local wind characteristics and urban environments such as buildings architecture. The urban terrain is more complex than for open spaces and has a critical influence on wind flow at the studied site. This approach proposes an integration of the surrounding buildings in the studied site and then simulating the wind flow, considering both simple and advanced turbulence models to quantify and simulate the wind flow fields in an urban environment and evaluate the potential wind energy. These simulations are conducted with an accessible computational fluid dynamic tool (Windsim) implementing available commercial wind turbines and performed on a case study at Agder county in the southern part of Norway for an industrial facility specialized in food production. Several simulations were considered and repeated to achieve a convergence after adding the buildings to the domain, which mainly simulates the wind flow patterns, power density, and annual energy production. These simulations will be compared with previous results, which adapted different manipulation techniques applied on the same site where the elevation and roughness data were manipulated to mimic the actual conditions in the studied urban site. The current approach (adding the buildings) showed a reduction in the average wind speed and annual energy production for certain levels with increased turbulence intensity surrounding the buildings. Moreover, a feasibility study is conducted to analyze the techno-economic of the facility's hybrid system, including the planned installation of a wind energy system using commercial software (HOMER). The simulation results indicated that HOMER is conservative in estimating the annual energy production of both wind and solar power systems. Nevertheless, the analysis showed that integrating a wind turbine of 600 kW would significantly reduce the dependence on the grid and transform the facility into a prosumer with more than 1.6 GWh traded with the grid annually. However, the proposed system's net present cost would be 1.43 M USD based on installation, maintenance, and trading with the grid, without including self-consumption, which counts for approximately 1.5 GWh annually. Moreover, the proposed system has a low levelized cost of energy of 0.039$ per kWh, which is slightly above the levelized cost of wind energy but 2 to 4 times less than the installed solar panels

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.Peer ReviewedPostprint (author's final draft

Role of Metaheuristics in Optimizing Microgrids Operating and Management Issues::A Comprehensive Review

The increased interest in renewable-based microgrids imposes several challenges, such as source integration, power quality, and operating cost. Dealing with these problems requires solving nonlinear optimization problems that include multiple linear or nonlinear constraints and continuous variables or discrete ones that require large dimensionality search space to find the optimal or sub-optimal solution. These problems may include the optimal power flow in the microgrid, the best possible configurations, and the accuracy of the models within the microgrid. Metaheuristic optimization algorithms are getting more suggested in the literature contributions for microgrid applications to solve these optimization problems. This paper intends to thoroughly review some significant issues surrounding microgrid operation and solve them using metaheuristic optimization algorithms. This study provides a collection of fundamental principles and concepts that describe metaheuristic optimization algorithms. Then, the most significant metaheuristic optimization algorithms that have been published in the last years in the context of microgrid applications are investigated and analyzed. Finally, the employment of metaheuristic optimization algorithms to specific microgrid issue applications is reviewed, including examples of some used algorithms. These issues include unit commitment, economic dispatch, optimal power flow, distribution system reconfiguration, transmission network expansion and distribution system planning, load and generation forecasting, maintenance schedules, and renewable sources max power tracking

Design and implementation of rural microgrids : Laguna Grande case study

In 2015 the United Nations established the 17 Sustainable Development Goals: a set of interrelated objectives and a guide to reach a more sustainable and higher quality future for all humanity. The goals were set with a timeline for 2030, the seventh goal refers specifically to the universal access to “affordable and clean energy”. Taking account the considerable fraction of world population that do not have access to electricity, especially in rural areas, this goal still requires a great effort and investment. Rural hybrid microgrids, that integrate and manage solar and wind energy resources to provide electric service to remote locations, are a promising solution to reach this “last mile” scenario. However, as is reported in the literature, there is still scarce information about the performance of these systems based on measured data obtained in real working field conditions. This work aims to contribute to this aspect mainly by analyzing the data obtained in the 9 kW Laguna Grande community hybrid microgrid, which is cooperative since 2016 in the coast of Perú, and has been equipped with sensors and data acquisition systems that measure and register solar radiation, wind speed, temperatures, and all the relevant electric parameters. As a preliminary study, the rural electrification gap and costs are assessed, as well as the availability of solar and wind resources in the area of interest. A literature and state of the art review is undertaken followed by the definition of the microgrid concept and the different ways in which a rural microgrid can be configured. The particular way in which the Laguna Grande microgrid is configured and instrumented is described. Measured meteorological conditions as solar radiation, wind speed and temperature are analyzed and related to the power generated by the photovoltaic arrays and wind turbine. This in turn leads to a balance with respect to the power delivered to the community and consequently to the voltage levels of the battery bank. Battery dynamics concepts are used to determine the depth of discharge (DOD) of the batteries in a real time regime. The statistics of the DOD values allows for the duration of the battery to be estimated which is a key factor to the microgrid economics and reliability. A parametric study is done to assess the effect of varying battery size on the technical and economic performance of the microgrid; similarly, with generating capacity in both photovoltaic arrays and wind turbines. Complementarily, a commercial software is used to optimize the microgrid, introducing state of the art components as lithium-ion batteries, power electronics and photovoltaic modules for a future upgrade. Finally, this study would not be complete without emphasizing the importance and adequate consideration of the human factor for the success and long-term sustainability of rural electrification projects.En el año 2015 las Naciones Unidas estableció los 17 Objetivos de Desarrollo Sostenible: un conjunto de objetivos interrelacionados y una guía para alcanzar un futuro más sostenible y de mayor calidad para toda la humanidad. Las metas se establecieron con una línea de tiempo para el 2030, la séptima meta se refiere específicamente al acceso universal a “energía limpia y asequible”. Teniendo en cuenta la fracción considerable de la población mundial que no tiene acceso a la electricidad, especialmente en las zonas rurales, este objetivo aún requiere un gran esfuerzo e inversión. Las microrredes híbridas rurales, que integran y gestionan los recursos de energía solar y eólica para proporcionar servicio eléctrico a lugares remotos, son una solución prometedora para llegar a este escenario de “última milla”. Sin embargo, como se reporta en la literatura, aún existe poca información sobre el desempeño de estos sistemas basada en datos medidos y obtenidos en condiciones operativas, reales de campo. Este trabajo busca contribuir en este aspecto principalmente mediante el análisis de los datos obtenidos en la microrred híbrida comunitaria de 9 kW en Laguna Grande, que está operativa desde 2016 en la costa de Perú. Esta microrred ha sido equipada con sensores y sistemas de adquisición de datos que miden y registran la energía solar, radiación, velocidad del viento, temperaturas y todos los parámetros eléctricos relevantes. Como estudio preliminar se evalúa la brecha y costos de electrificación rural, así como la disponibilidad de recurso solar y eólico en la zona de interés. Se realiza una revisión bibliográfica y del estado del arte, seguida de la definición del concepto de microrred y las diferentes formas en que se puede configurar una microrred rural. Se describe la forma particular en que se configura e instrumenta la microrred de Laguna Grande. Las condiciones meteorológicas medidas como la radiación solar, la velocidad del viento y la temperatura se analizan y relacionan con la energía generada por los arreglos fotovoltaicos y la turbina eólica. Esto a su vez conduce a realizar un balance con respecto a la potencia entregada a la comunidad y consecuentemente a los niveles de voltaje del banco de baterías. Los conceptos de dinámica de batería se utilizan para determinar la profundidad de descarga (DOD) de las baterías en un régimen a tiempo real. Las estadísticas de los valores DOD permiten estimar la duración de la batería, lo cual es un factor clave para la economía y confiabilidad de la microrred. Se realiza un estudio paramétrico para evaluar el efecto de variar el tamaño de la batería en el desempeño técnico y económico de la microrred; de igual forma, con la capacidad de generación tanto en arreglos fotovoltaicos como turbinas eólicas. Complementariamente, se utiliza un software comercial para optimizar la microrred, introduciendo componentes de última generación como baterías de iones de litio, electrónica de potencia y módulos fotovoltaicos para una futura actualización. Finalmente, este estudio no estaría completo sin enfatizar la importancia y la adecuada consideración del factor humano para el éxito y la sostenibilidad a largo plazo de los proyectos de electrificación rural.Postprint (published version

Control of Energy Storage

Energy storage can provide numerous beneficial services and cost savings within the electricity grid, especially when facing future challenges like renewable and electric vehicle (EV) integration. Public bodies, private companies and individuals are deploying storage facilities for several purposes, including arbitrage, grid support, renewable generation, and demand-side management. Storage deployment can therefore yield benefits like reduced frequency fluctuation, better asset utilisation and more predictable power profiles. Such uses of energy storage can reduce the cost of energy, reduce the strain on the grid, reduce the environmental impact of energy use, and prepare the network for future challenges. This Special Issue of Energies explore the latest developments in the control of energy storage in support of the wider energy network, and focus on the control of storage rather than the storage technology itself

Energy management in residential hydrogen hybridised renewable microgrids. A multi-objective proposal based on fuzzy logic

[ES] Los sistemas de almacenamiento en microrredes basadas en fuentes de energía renovable (FER) son elementos imprescindibles para adecuar la producción a la demanda, de modo que el exceso de energía renovable presente en la red en periodos determinados, pueda ser almacenado y utilizado en situaciones de déficit de producción. Como es sabido, las FER tienen una producción no constante y no continua. Dada la naturaleza multi componente (elementos de producción y almacenamiento de características y dinámicas diferentes) de las microrredes renovables hibridadas con hidrógeno, resulta necesario implementar sistemas de gestión energética (SGE), los cuales son sistemas de control que persiguen obtener las mejores prestaciones de cada elemento para lograr de forma sinérgica un funcionamiento adecuado de la microrred. Este artículo propone, para una microrred renovable hibridada con hidrógeno de uso residencial, un SGE implementado mediante un controlador lógico borroso (CLB) multivariable y multietapa. Se trata de hacer frente a un problema multiobjetivo, con objeto de aumentar el rendimiento de la microrred en términos de eficiencia, costes operativos y vida útil de sus elementos. Para ello, se tendrá en cuenta el balance de potencia de la microrred, el rendimiento y la degradación de sus elementos, así como los costes/beneficios de la energía intercambiada con la red eléctrica principal. Los resultados obtenidos muestran un mejor rendimiento y mayor beneficio económico en comparación con SGE tradicionales basados en modelos o técnicas heurísticas.[EN] Storage systems in microgrids based on renewable energy sources (RES) are essential elements to match production to demand, so that excess renewable energy present in the grid at given periods can be stored and used in situations of production shortfalls. As is well known, RES have a non-constant and non-continuous production. Given the multi-component nature (production and storage elements with different characteristics and dynamics) of hydrogen-hybridised renewable microgrids, which are control systems that seek to obtain the best performance from each element in order to achieve synergistic operation of the microgrid. This article proposes, for a residential hydrogen-hybridised renewable microgrid, an EMS implemented by means of a multivariable and multistage fuzzy logic controller (FLC). The aim is to address a multi-objective problem in order to increase the performance of the microgrid in terms of efficiency, operational costs and lifespan of its elements. This will take into account the power balance of the microgrid, the performance and degradation of its elements, as well as the costs/benefits of the energy hanged with the main grid. The results obtained show a better performance and higher economic benefit compared to traditional EMSs based on models or heuristic techniques