A review of optimal operation of microgrids

The term microgrid refers to small-scale power grid that can operate autonomously or in concurrence with the area’s main electrical grid. The intermittent characteristic of DGs which defies the power quality and voltage manifests the requirement for new planning and operation approaches for microgrids. Consequently, conventional optimization methods in new power systems have been critically biased all through the previous decade. One of the main technological and inexpensive tools in this regard is the optimal generation scheduling of microgrid. As a primary optimization tool in the planning and operation fields, optimal operation has an undeniable part in the power system. This paper reviews and evaluates the optimal operation approaches mostly related to microgrids. In this work, the foremost optimal generation scheduling approaches are compared in terms of their objective functions, techniques and constraints. To conclude, a few fundamental challenges occurring from the latest optimal generation scheduling techniques in microgrids are addressed

Energy management in microgrids with renewable energy sources: A literature review

Renewable energy sources have emerged as an alternative to meet the growing demand for energy, mitigate climate change, and contribute to sustainable development. The integration of these systems is carried out in a distributed manner via microgrid systems; this provides a set of technological solutions that allows information exchange between the consumers and the distributed generation centers, which implies that they need to be managed optimally. Energy management in microgrids is defined as an information and control system that provides the necessary functionality, which ensures that both the generation and distribution systems supply energy at minimal operational costs. This paper presents a literature review of energy management in microgrid systems using renewable energies, along with a comparative analysis of the different optimization objectives, constraints, solution approaches, and simulation tools applied to both the interconnected and isolated microgrids. To manage the intermittent nature of renewable energy, energy storage technology is considered to be an attractive option due to increased technological maturity, energy density, and capability of providing grid services such as frequency response. Finally, future directions on predictive modeling mainly for energy storage systems are also proposed

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

Microgrids/Nanogrids Implementation, Planning, and Operation

Today’s power system is facing the challenges of increasing global demand for electricity, high-reliability requirements, the need for clean energy and environmental protection, and planning restrictions. To move towards a green and smart electric power system, centralized generation facilities are being transformed into smaller and more distributed ones. As a result, the microgrid concept is emerging, where a microgrid can operate as a single controllable system and can be viewed as a group of distributed energy loads and resources, which can include many renewable energy sources and energy storage systems. The energy management of a large number of distributed energy resources is required for the reliable operation of the microgrid. Microgrids and nanogrids can allow for better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and technical disruptive events. Microgrid networking with optimal energy management will lead to a sort of smart grid with numerous benefits such as reduced cost and enhanced reliability and resiliency. They include small-scale renewable energy harvesters and fixed energy storage units typically installed in commercial and residential buildings. In this challenging context, the objective of this book is to address and disseminate state-of-the-art research and development results on the implementation, planning, and operation of microgrids/nanogrids, where energy management is one of the core issues

Energy Management of Grid-Connected Microgrids, Incorporating Battery Energy Storage and CHP Systems Using Mixed Integer Linear Programming

In this thesis, an energy management system (EMS) is proposed for use with battery energy storage systems (BESS) in solar photovoltaic-based (PV-BESS) grid-connected microgrids and combined heat and power (CHP) applications. As a result, the battery's charge/discharge power is optimised so that the overall cost of energy consumed is minimised, considering the variation in grid tariff, renewable power generation and load demand. The system is modelled as an economic load dispatch optimisation problem over a 24-hour time horizon and solved using mixed integer linear programming (MILP) for the grid-connected Microgrid and the CHP application. However, this formulation requires information about the predicted renewable energy power generation and load demand over the next 24 hours. Therefore, a long short-term memory (LSTM) neural network is proposed to achieve this. The receding horizon (RH) strategy is suggested to reduce the impact of prediction error and enable real-time implementation of the energy management system (EMS) that benefits from using actual generation and demand data in real-time. At each time-step, the LSTM predicts the generation and load data for the next 24 h. The dispatch problem is then solved, and the real-time battery charging or discharging command for only the first hour is applied. Real data are then used to update the LSTM input, and the process is repeated. Simulation results using the Ushant Island as a case study show that the proposed online optimisation strategy outperforms the offline optimisation strategy (with no RH), reducing the operating cost by 6.12%. The analyses of the impact of different times of use (TOU) and standard tariff in the energy management of grid-connected microgrids as it relates to the charge/discharge cycle of the BESS and the optimal operating cost of the Microgrid using the LSTM-MILP-RH approach is evaluated. Four tariffs UK tariff schemes are considered: (1) Residential TOU tariff (RTOU), (2) Economy seven tariff (E7T), (3) Economy ten tariff (E10T), and (4) Standard tariff (STD). It was found that the RTOU tariff scheme gives the lowest operating cost, followed by the E10T tariff scheme with savings of 63.5% and 55.5%, respectively, compared to the grid-only operation. However, the RTOU and E10 tariff scheme is mainly used for residential applications with the duck curve load demand structure. For community grid-connected microgrid applications except for residential-only communities, the E7T and STD, with 54.2% and 39.9%, respectively, are the most likely options offered by energy suppliers. The use of combined heat and power (CHP) systems has recently increased due to their high combined efficiency and low emissions. Using CHP systems in behind-the-meter applications, however, can introduce some challenges. Firstly, the CHP system must operate in load-following mode to prevent power export to the grid. Secondly, if the load drops below a predefined threshold, the engine will operate at a lower temperature and hence lower efficiency, as the fuel is only half-burnt, creating significant emissions. The aforementioned issues may be solved by combining CHP with a battery energy storage system. However, the dispatch of CHP and BESS must be optimised. Offline optimisation methods based on load prediction will not prevent power export to the grid due to prediction errors. Therefore, a real-time EMS using a combination of LSTM neural networks, MILP, and RH control strategy is proposed. Simulation results show that the proposed method can prevent power export to the grid and reduce the operational cost by 8.75% compared to the offline method. The finding shows that the BESS is a valuable asset for sustainable energy transition. However, they must be operated safely to guarantee operational cost reduction and longer life for the BESS

Hybrid-Microgrid Planning, Sizing and Optimization for an Industrial Demand in Pakistan

Industrial sector is of great significance for the economic growth of every country. The energy crisis in Pakistan has become the prime stumbling block in the economic development of the country. There are many industrial processes that need uninterrupted supply; even a trivial outage can cost millions of dollars. The main cause of "load shedding" in Pakistan is that it produces a major portion of its energy from fossil fuels, whose price and demand is constantly increasing. Most of the customers at industrial and commercial level use Diesel Generator (DiG) as a reliable alternative source of electrical power when grid supply is unavailable. The use of DiG during loading shedding hours would increase the Cost of Energy (COE) per kWh and also enhance environmental emissions. Pakistan has a wide range of renewable power sources like bioenergy, wind, solar, hydel, geothermal etc. The distinct emphasis on the implementation of an industrial microgrid in Faisalabad, Pakistan has been specified in this paper. The prospective benefits of the microgrid fall into three major kinds: cost reduction, fuel saving, and improved environmental emissions. The optimized objective of this work is to maximize these benefits. Moreover while designing the hybrid microgrid system it encounters many design challenges like sizing of the components, system feasibility, COE, system reliability etc. This study contributes to the ongoing studies about hybrid microgrid system and draws attention to the optimal design and sizing considering several techno-economic factors including Net Present Cost (NPC), COE, supply reliability, capacity shortage constraint, battery state of charge (SOC), dispatch strategy, PV power generation and PV array tracking systems. Different cases are studied; microgrid sizing, techno-economic exploration, sensitivity analysis and environmental effects are addressed using (Hybrid Optimization Model for Electric Renewables) HOMER. The results show that COE and environmental emissions have been significantly reduced for the proposed system

Using an intelligent method for microgrid generation and operation planning while considering load uncertainty

The integration of distributed generation (DG), energy storage systems (ESS), and controllable loads near the place of consumption has led to the creation of microgrids. However, the uncertain nature of renewable energy sources (wind and photovoltaic), market prices, and loads have caused issues with guaranteeing power quality and balancing generation and consumption. To solve these issues, microgrids should be managed with an energy management system (EMS), which facilitates the minimization of operating (performance) costs, the emission of pollutants, and peak loads while meeting technical constraints. To this effect, this research attempts to adjust parameters by defining indicators related to the best possible conditions of the microgrid. Generation planning, the storage of generated power, and exchange with the main grid are carried out by defining a dual-purpose objective function, which includes reducing the operating cost of power generation, as well as the pollution caused by it in the microgrid, by means of the SALP optimization algorithm. Moreover, in order to make the process more realistic and practical for microgrid planning, some parameters are considered as indefinite values, as they do not have exact values in their natural state. The results show the effect of using the introduced intelligent optimization method on reducing the objective function value (cost and pollution)

A review on peak load shaving in microgrid—Potential benefits, challenges, and future trend

This study aims to review the potential benefits of peak load shaving in a microgrid system. The relevance of peak shaving for a microgrid system is presented in this research review at the outset to justify the peak load shaving efficacy. The prospective benefits of peak shaving in microgrid systems, including technological, economic, and environmental advantages, are thoroughly examined. This review study also presents a cost–benefit numerical analysis to illustrate the economic viability of peak load shaving for a microgrid system. Different peak shaving approaches are briefly discussed, as well as the obstacles of putting them into practice. Finally, this review study reveals some potential future trends and possible directions for peak shaving research in microgrid systems. This review paper lays a strong foundation for identifying the potential benefits of peak shaving in microgrid systems and establishing suitable projects for practical effectuation