Microgrid Installation Research Articles

Multi-Criteria Decision Support System for Automatically Selecting Photovoltaic Sets to Maximise Micro Solar Generation

Technological advancements have improved solar energy generation and reduced the cost of installing photovoltaic (PV) systems. However, challenges such as low energy-conversion efficiency and the unpredictability of electricity generation due to shading or climate conditions persist. Despite decreasing costs, access to solar energy generation technologies remains limited. This paper proposes a multi-criteria decision support system (MCDSS) for selecting the most suitable PV set (comprising PV modules, inverters, and batteries) for microgrid installations. The MCDSS employs two multi-criteria decision-making methods (MCDM) for analysis and decision-making: AHP and TOPSIS. The system was tested in two case studies: Barreiras, with a global efficiency of 14.4% and an internal rate of return (IRR) of 56.0%, and Curitiba, with a worldwide efficiency of 14.8% and an IRR of 52.0%. The research provided a framework for assessing and selecting PV sets based on efficiency, cost, and return on investment. Methodologically, it integrates multiple MCDM techniques, demonstrating their applicability in renewable energy. Managerially, it offers a practical tool for decision-makers in the energy sector to enhance the feasibility and attractiveness of microgeneration projects. This research highlights the potential of MCDSS to improve the efficiency and accessibility of solar energy generation.

Optimal Electrification Using Renewable Energies: Microgrid Installation Model with Combined Mixture k-Means Clustering Algorithm, Mixed Integer Linear Programming, and Onsset Method

Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

Conversion of communal energy systems into microgrids for electricity outages of very long durations

This research provides a methodology that addresses the design of microgrids for communities that may include different types of consumers and energy systems. It focuses on outages of very long durations, which have been mostly ignored so far, but are expected to become more common as the impact of climate change increases. The methodology identifies optimal solutions for converting and expanding existing communal energy systems into microgrids, given the widespread installation within communities of renewable energy systems such as photovoltaic systems. The methodology addresses the design and installation of optimal microgrids as a decision-making process, in which end-users must be involved and that starts from an analysis of their needs and requirements. The methodology is applied in a case study of two real-life grid-connected collective communities. It also includes an analysis of the possibility to create an extended system by linking the microgrids. The methodology’s application led to some unexpected results, such as the fact that continued energy supply for domestic consumption was considered more critical than for workplaces and communal facilities, and that there was a clearer justification for the installation of more expensive microgrid systems that can cope with longer outages.

Identification and Analysis of Technical Impacts in the Electric Power System Due to the Integration of Microgrids

In a modern and technological world that has a great demand for energy, a versatile energy market, and a renewed electric infrastructure capable of expanding the electric power system under the premise of universal access to electricity, that seeks to minimize the effects of climate change, and that requires an improvement in its reliability, security, and resilience, microgrids are born as one of the systems that have the potential to supply each of these requirements in order to guarantee an adequate decarbonization, decentralization, digitalization, diversification, and democratization of the future grid. However, the integration of microgrids into the electric power system will generate impacts that are currently under study. This paper identifies and analyzes the technical impacts in the electric power system due to the implementation of microgrids, based on what has been recognized in the literature, so that those who have purposes of installation, creation, innovation, and research of microgrids, such as grid operators, technology providers, companies, and researchers, can establish criteria and indicators through which the feasibility of projects involving microgrids can be determined. The concept, importance, and characteristics of microgrids are given, along with a technical justification of the impacts. In addition, technical impacts on some study cases of real microgrids around the globe are identified. Finally, an analysis of the identified technical impacts is offered, and conclusions are drawn.

Understanding the community in community microgrids: A conceptual framework for better decision-making

A community microgrid comes with the introduction of non-conventional distributed renewable energy infrastructure, affecting the behaviour of community members and their relationship with energy. The aspects of ownership, trust, collaboration and its often-discursive structure will be reflected in the cultural and social factors, such as norms and values in a community. The success of specific community microgrids is widely dependent on the community's ability to engage in various activities connected to the microgrid installation and operation. This paper conceptualises existing literature on community microgrids, focusing on the representation and inclusion of community preferences, needs and behaviour across the development stages. From this analysis, a conceptual-theoretical framework is proposed based on social capital theory for identifying community characteristics to determine key needs and considerations for microgrid adoption. The framework is divided into four components: social capital, community capability, community type and microgrid impact. Social capital, including its dimensions such as structural, cognitive, and relational capital forms the foundation of the framework and serves to evaluate the community capability and determine its type, which in turn affects its impact on the community microgrid. Finally, we present an initial step in operationalising our conceptual framework as a practical tool to guide further research in the development of community microgrids. Ultimately, this research can benefit both academia and industry by providing a comprehensive and practical approach to understanding the importance of social factors in community microgrid success.

ASSESSING FEASIBILITY STUDIES ON SMART MICROGRID SYSTEMS: A GLOBAL REVIEW AND METHODOLOGICAL COMPARISON FOR IMPLEMENTING MICROGRIDS IN MALAYSIA

This paper serves as a comprehensive review of past feasibility studies conducted worldwide on smart microgrid systems. The primary focus of microgrids lies in the generation of electricity using micro sources, such as micro-hydro, photovoltaic, or biomass gasifiers. These generated power is then distributed through low voltage networks, catering to a relatively small number of consumers. Malaysia, owing to its geographical location, possesses abundant renewable resources, making it highly suitable for the implementation of microgrids. The adoption of microgrids in Malaysia holds significant potential, offering numerous benefits to the nation and its residents. Prior to initiating a feasibility study within Malaysia, it is crucial to conduct a preliminary study to gain insights into the methodologies employed in previous studies. This review paper concentrates on comparing the methodologies utilized in various studies, including the feasibility study of microgrid installation in an educational institution with grid uncertainty, the feasibility study for 100% renewable energy microgrids in Switzerland, the feasibility study of a microgrid village employing renewable energy sources, the feasibility study for a solar PV microgrid in Malawi, and the feasibility study of microgrid applications in Langkawi and Socotra Islands. By thoroughly examining these studies, this review paper aims to identify the most optimal methodology for conducting feasibility studies on microgrids.

Advanced control strategies to manage electric vehicle drivetrain battery health for Vehicle-to-X applications

The demand for local power resilience is promoting the installation of renewable-based microgrids. Plug-in electric vehicles (PEVs) are rapidly increasing and can play a critical role in microgrid service provision. The capability of bi-directional charging and discharging will transition PEVs from a simple means of transportation to multi-purpose value generating assets. They can balance the inherently fluctuating generation of renewable energy resources and shape customer’s electricity demand, while still providing the core service of transportation. Value stacking through those additional services allows PEV owners to draw from a number of revenue streams to offset investment costs. However, accelerated battery degradation is often cited as concern when using PEV batteries for purposes other than driving, which presents a major barrier for broad market adoption. This study seeks to assess the economics and trade-offs of bi-directional use of PEVs when utilized as fleet vehicles. In particular, the usage patterns and benefits for PEV fleet deployment at three U.S. military bases is presented. The results show operational cost benefits for bi-directional application of up to 60.8 % annual return on investment without managing battery health, and up to 106.0 % when actively managing battery health through advanced control strategies. The one year payback period far exceeds the expected installation lifespan of at least ten years. Given the results, utilizing PEV fleets for additional services at U.S. military bases can largely offset the additional cost of bi-directional charging hardware and software compared to standard uni-directional equipment.

A two-way pre-installation assessment framework for microgrids under power systems expansion planning

Many remote areas remain off the grid and are disconnected from the mainstream power network due to congestion in the existing power networks and expensive expansion plans. In recent studies, microgrid installations appeared as one of the most feasible solutions for power system expansion. This research study develops a two-way (M to G), where the existing microgrid is integrated into the distribution network, and (G to M) where distribution system expansion recommends the installation of a microgrid. The proposed framework is based on three steps. The initial assessment is based on a fuzzy assessment tool utilizing social factors, geographic location, and accessibility followed by economic feasibility analyses. These analyses are based on HOMER software and a power flow study of the microgrid to assess the system’s reliability. The proposed framework is implemented on an islanded microgrid in a village in Pakistan. The acquired results have shown that the proposed framework recommends the existing microgrid expansion in M to G mode. The Net Present Cost (NPC) of the grid-connected system is reduced from $11 million to $0.7 million. The cost of energy is also reduced to $4.42 compared to the $65 of the islanded systems, while the payback period is only 1.2 years compared to that of the islanded microgrid which is 8.6 years.

Public support for community microgrid services

Utility-owned community microgrids can provide communities with decentralized grid access to distributed energy resources and improve reliability and resiliency. However, the feasibility of installing microgrids requires rigorous cost-benefit analysis, which should incorporate social values. Currently, the gap in our understanding of ratepayers' preferences for community microgrid services leaves stakeholders guessing. Using a survey-based contingent valuation method, with a referendum-style elicitation format, this paper provides evidence of public support for community microgrid installations in Arizona, Colorado, New Mexico, and Utah (the Four Corners). The Four Corners region is unique in its potential for renewable electricity capacity as well as heterogeneous state policy objectives regarding the transition to clean energy. A split-sample survey of 4783 Four Corner's ratepayers resulted in between 40 and 45% of respondents voting to support a community microgrid installation (after controlling for hypothetical bias) with a median willingness-to-pay (WTP) of $25.44 (divided among 24 months) if the ratepayer received direct benefits, or $13.92 if they received indirect benefits. Ratepayers in Utah were willing to pay the most relative to the other states. Results highlight the impacts of ideological, institutional, and socioeconomic factors on public support and WTP.

Smooth Integration of Rectifier-Battery Banks Operation in Real-Life Isolated Microgrids Based on Renewable Sources: Theory and Application

Isolated microgrids need dispatchable energy sources to ensure continuity of service during lack of the renewable energy sources. One common source is the diesel generator which is used as a backup and for battery charges. Practical experiences have shown that microgrids have operation problems when diesel generators and rectifiers work together to charge battery banks. This is because of resulting diesel generator voltage distortions caused by the interaction of line currents harmonics with equivalent series reactance of the AC source and the notches introduced during the current commutation between 2 SCRs of the bridge rectifier. These distortions eventually inhibit the rectifier operation, causing malfunctioning of the system. One solution is to use generators with rated power greater than the rectifiers, which results in oversized installation and high operating costs. This work proposes a solution to avoid generator oversizing by using resonant filters, notch filter and a capacitive reactive compensation circuit to avoid self-excitation of the generator. Soft-start operation of the rectifier, and disturbance decoupling in the generator are also proposed. The design allows the use of generators and rectifiers of similar power, reducing the installation and operation costs of microgrids. It has been used successfully in two real-life microgrids.

Energy Analysis of a NZEB Office Building with Rooftop PV Installation: Exploitation of the Employees’ Electric Vehicles Battery Storage

Near zero energy buildings are increasing worldwide, exploiting low-carbon technologies in heating and electricity self-production. Commercial buildings are increasingly considered as candidates for the installation of smart micro-grids, which may profit from the added storage capacity of the batteries of employees electric vehicles, stationed during daytime in their charging lots. Smart exploitation of the interaction of these electricity sources and sinks may prove essential to address the complex electricity network demand patterns in today’s fast changing energy mixture. The interaction of an efficient office building’s energy system with a big rooftop photovoltaic installation and the aggregate storage capacity of 40 electric cars that are connected in the building’s charging lots is studied by means of transient simulation in TRNSYS environment. The 18-zone building’s heating, ventilation, and air conditioning system, the cars’ batteries, and photovoltaic systems’ interactions are analyzed on a monthly, seasonal, and hourly basis, against the respective demand curves of the Greek network. The results suggest that the specific system’s size may profitably support the operation of a smart micro-grid. The total annual electricity consumption of the building is computed to reach 112,000 kWh, or 20 kWh/m2y. The annual electricity needs of the 40 electric cars, amounting to 101,000 kWh, can be fully met with 30% of the photovoltaic electricity production. Thus, the building becomes a net exporter of electricity to the network, with maximum exported electricity occurring daily between 12:00 and 14:00, which is favorable to meeting the demand curve. Thus, the establishment of smart micro-grids in commercial buildings with large rooftop photovoltaic panels’ capacity and a significant number of electric cars in the employees’ car fleet is quite effective in this direction.

Hybrid power-heat microgrid solution using hydrogen as an energy vector for residential houses in Spain. A case study

In order to favor a transition to a renewable energy economy, it is necessary to study the possible permeation of renewable energy sources not only in the electric grid or industrial scale, but also in the small householding scale. One of the most interesting technologies available for this purpose is solar energy, since it is a mature technology that can be easily installed in every rooftop. Thus, a techno-economic assessment was carried out to evaluate the installation of a solar-based power-heat hybrid microgrid considering the use of hydrogen as an energy vector in a typical residential house in Spain. Lead-acid batteries plus the photovoltaic and solar thermal energy installation are complemented with a hydrogen system composed of an electrolyzer, two metal hydride bottles, and a fuel cell. A simulation tool has been generated using experimental models developed and validated with real equipment for each one of the electric microgrid component. Three operating modes were tested making use of this tool to better manage the energy consumed/produced and optimize the economic output of the facility. The results show that setting up a hydrogen-based microgrid in a residential house is unviable today, mainly due to the high cost of hydrogen generation and consumption equipment. If only solar energy is considered, the microgrid inversion (12.500 €) is recovered in ten years. On the other hand, selling the electricity output has almost no repercussions considering current electrical rates in Spain. Finally, while using an optimization algorithm to manage energy use, battery life-spam, and economic benefit slightly increase. However, this profit may not be enough to justify the use of a more complex control system. The results of this research will help users, renewable energy companies, investigators, and policymakers to better understand the different factors influencing the spread of renewable smart grids in households and propose solutions to address these.

Estimation of cycling aging of lithium-ion batteries for photovoltaic applications

The installation of photovoltaic microgrids to meet energy needs has had a significant increase in recent years. Likewise, the use of lithium batteries to improve the performance of the microgrid is an issue that is being studied. In this sense, it is important to know the electrical response of the lithium battery under such environment and its degradation. In this sense, this paper presents a methodology developed for the mathematical modelling of the electrical behaviour of a lithium battery. This methodology has been developed from the integration of three mathematical models: dynamic model, thermal model and aging model. During its operation, the lithium battery will be subjected to constant charging and discharging processes (dynamic model), as well as to thermal stress, because of the combined effect of the current flow and the ambient temperature (thermal model), which will generate a lithium battery capacity loss (aging model). For the analysis, real data on photovoltaic production, residential consumption profile, ambient temperature and 48V 100Ah LFP battery datasheet have been used. The developed methodology allows estimating the aging of a lithium battery in real time.

Political-Optimizer-Based Energy-Management System for Microgrids

This paper presents an energy-management strategy based on a recently introduced Political Optimizer (PO) for a microgrid installation at Wroclaw University of Science and Technology. The aim of the study is to check the effectiveness of two recently introduced meta-heuristic algorithms at power-system-operations planning. The optimization algorithms were compared with other conventional meta-heuristics wherein performance tests were carried out by minimizing costs in an IEEE 30-bus system. The best performing algorithm was then used to minimize the Levelized Cost of Energy (LCOE) in a microgrid consisting of renewable energy sources such as solar PV panels, a micro-hydro power plant, a fuel cell with a hydrogen storage tank and a Li-ion storage unit.

Enabling demand response for optimal deployment of multi‐carrier microgrids incorporating incentives

This paper inspects customer multi-carrier microgrid deployments' techno-economic viability and assists investors in deciding whether or not to invest in multi-carrier microgrid installations equipped with smart demand-side technologies. The solution of the proposed model determines the optimal mix and size of distributed energy resources, and identifies the ideal participation rate of potential responsive customers within the multi-carrier microgrid. The objective of the proposed model is to minimize the overall deployment cost comprising the investment and replacement of distributed energy resources, demand-side smart measurement and informing appliances, loan payoff, operation, maintenance, peak demand charge, energy demand shifting reward or penalty, emission, and unserved energy while ensuring the desired levels of reliability and online reserve. The model also considers incentive policies to encourage customers to install demand-side smart technologies to participate in demand response programs actively. The planning problem is formulated by mixed-integer programming. The proposed model is applied to an industrial zone as an aggregate load. Numerical simulations exhibit the model's efficacy and scrutinize in-depth, the effect of a variety of factors on multi-carrier microgrid planning results, including the extents of the capital investment fund and loan in addition to demand response enabling technology cost.

A Framework for Considering Capital Cost Limit in Sizing Microgrid Distributed Energy Resources—Application to Industrial Microgrids

Capital cost limitation is a practical problem in a system installation and single optimal rating may lead to requirement of high capital cost investment. This calls for a need a need to develop a framework which provides alternate system ratings when confronted with capital cost limitation. A framework for sizing microgrid distributed energy resources (DER) considering capital cost limit and inclusion of manufacturer catalog ratings is introduced in this paper. This framework uses a system composite cost metric which combines system capital cost and operating cost and is calculated on monthly basis. The monthly optimization results are transformed to evaluate the feasible DER ratings and annual savings possible. The framework is demonstrated using a case study of sizing microgrid to perform peak shaving at industrial facilities located in the UK and USA. This paper also introduces development of Hardware-in-Loop (HiL) system as a tool to validate microgrid sizing results. The HiL simulation verifies the estimated annual savings possible through the installation of microgrid and verifies no violation of state of charge limits of battery energy storage system in the microgrid operation simulation, thus validating the sizing framework.

Facility Planning Optimization Platform, GGOD, for Expandable Cluster-type Micro-grid Installations and Operations

This paper describes the architecture and the utilization for a facility planning optimization platform called GGOD, “Grid of Grids Optimal Designer” and applies it to expandable cluster-type micro-grid installations and operations. The expandable cluster-type micro-grid is defined as a group of micro-grids that are connected by bi-directional power transfer networks. Furthermore, power sources are also networked. Especially, by networking among power sources, powers necessary for social activities in-demand areas are secured. The proposed architecture is based on service-oriented architecture, meaning that optimization functions are executed as services. For flexibility, these services are executed by requests based on extensible mark-up language texts. The available optimizations are written in meta-data, which are accessible to end-users from the meta-data database system called clearinghouse. The meta-data are of two types, one for single optimization and the other for combined optimization. The processes in GGOD are conducted by the management function which interprets descriptions in meta-data. In meta-data, the names of optimization functions and activation orders are written. The basic executions follow sequential, branch, or loop flow processes, which execute combined optimizations, compare more than two kinds of optimization processes, and perform iterative simulations, respectively. As an application of the proposed architecture, the power generation sites and transmission networks are optimized in a geospatial integrated-resource planning scenario. In this application, a structure and a method for the combination of component functions in GGOD are exemplified. Moreover, GGOD suggests promotions of a lot of applications by effective combinations of basic optimization functions.

Design and Implementation of Multi-Source and Multi-Consumer Energy Sharing System in Collaborative Smart Microgrid Installation

Many published studies debated electrical energy management. They mainly investigate the multi-source installation to develop energy efficiency during its different phases: production, distribution, and consumption. Although it is rarely discussed, energy sharing is a critical part of the energy management system. In this contribution, a demand-side management algorithm is developed, that incorporates energy consumption scheduler capacity. It provides optimal energy sharing, counting on suitable energy cost parameters and adequate multi-source installation. Using this proposal, the electrical bill decreases thanks to the optimal daily attribution of schedules to households formed by a multi-consumer microgrid. This application guarantees a maximal reduction of electrical cost for the set of energy partners as one prosumer used to consume and produce power. In addition, it maintains energy efficiency as it aids in avoiding breakdowns, and depressing the peak-to-average ratio. It admits that the utility company is, as usual, always reachable non-renewable source. At the same time, renewable energy was engendered by photovoltaic panels concomitant with wind turbines stations. The application is based on the JNET protocol stack. The proposed energy sharing algorithm is implemented by using Arduino board and JN5148 nodes as a star Wireless Sensors Network topology. It is installed as a prototype in the Digital Research Center of Sfax in Tunisia. This proposed incentive-based algorithm managed to reduce the smart microgrid annual cost by almost 55% without harming the public utility. It can even ensure a more significant diminution by selling the surplus of renewable power at the end of each day.

Optimal location of an electrical vehicle charging station in a local microgrid using an embedded hybrid optimizer

This paper presents an investigation into finding an optimal location for a planned Electrical Vehicle Charging Station (EVCS) with coordinated charging within the Microgrid installation at Wroclaw University of Science and Technology. The study uses a hybrid optimization algorithm built to combine the speed of MATPOWER and the search capabilities of a meta-heuristic optimization algorithm based on an extended ant colony which serves as the Energy Management System (EMS) of the Microgrid. The location obtained is based on an analysis of energy savings calculated on representative days of the year obtained through clustering and placing the EVCS on different nodes of the Microgrid consisting of distributed energy sources.

Status of Microgrid Protection and Related Standards and Codes: Protection Supports Integration

Microgrids are becoming a significant aggregation of distributed energy resources (DERs) that improves the reliability and resilience of the power delivery system. Most of the early microgrid experience occurred in behind-themeter applications for installations with critical loads and significant backup power and load prioritization requirements. Very successful systems that include campus and utility applications have been operational for up to and exceeding a decade. For these early systems, available codes and standards consisted mostly of adapted device-level legacy emergency and standby power requirements. Grid interconnection and efficient, safe operating requirements were improvised via programmed computers, and the protection focus was the microgrids themselves. The larger microgrid installations often required qualified staff trained to monitor and operate the systems.