Submit to Energies Review for Energies Propose a Special Issue

Journal Browser

Microgrids and the Integration of Energy Storage Systems

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (5 June 2023) | Viewed by 21388

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special issue Microgrids and the Integration of Energy Storage Systems book cover image

Share This Special Issue

Special Issue Editors

Dr. Alexander Micallef

E-Mail Website
Guest Editor

Department of Electrical Engineering, Faculty of Engineering, University of Malta, MSD 2080 Msida, Malta
Interests: microgrids (AC/DC/hybrid); electric transportation technologies; energy management systems; wind and PV grid connected systems; control and management of distributed generation and energy storage systems; smart grids; IoT applied to smart grids
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Zhaoxia Xiao

E-Mail Website
Guest Editor

School of Electrical Engineering, Tiangong University, Tianjin 300387, China
Interests: AC/DC microgrids with renewable energy; maritime power system; planning of distribution network

Special Issue Information

Dear Colleagues,

Decarbonization of the utility grid, market integration, consumer empowerment, and technical innovations all are key objectives in the international energy policy for the coming decades. Grid integration constraints are limiting the deployment potential of renewable energy sources (RESs). Therefore, while RESs are essential components to reach the key objectives, energy storage is the enabler that facilitates the integration of RESs in a cost-effective and flexible manner. The diversification of RES generation and integration of energy storage in modern power systems are also leading to the formation of island microgrids and microgrid clusters/communities for more reliable and sustainable electricity networks.

This Special Issue aims to publish high-quality research and review papers related to microgrids and energy storage systems. Topics of interest for publication include but are not limited to:

Integration of RES;
Behind-the-meter energy storage systems;
Utility-scale storage systems;
AC/DC microgrids;
Island microgrids;
Microgrid clusters/communities;
Ancillary Services under high variable RES penetration;
Maritime microgrids.

Dr. Alexander Micallef
Prof. Dr. Zhaoxia Xiao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

microgrids/microgrid clusters
utility-scale energy storage systems
behind-the-meter energy storage systems
renewable energy sources
ancillary services
maritime microgrids

Published Papers (10 papers)

Download All Papers

Research

Jump to: Review

16 pages, 635 KiB

Open AccessFeature PaperArticle

Optimal Sizing and Operation of Hybrid Renewable Power Plants Participating in Coupled Power Markets with Different Execution Times

by Carlos García-Santacruz, Andrés Alcántara, Juan M. Carrasco and Eduardo Galván

Energies 2023, 16(8), 3432; https://doi.org/10.3390/en16083432 - 13 Apr 2023

Viewed by 1396

Abstract

The increasing limitations in the use of fossil fuels due to their limited availability and pollution have increased the use of renewable energies and storage systems for electricity generation. To achieve the goals of the integration of renewable energy, sizing and management methods for hybrid plants are needed to make investments profitable and attractive in these resources. This work presents an optimization method for the sizing and operation of hybrid plants with storage, choosing the best combination of technologies based on resource availability, installation costs and market prices, maximizing an economic index such as the net present value. One of the main contributions of this work is to reduce the oversizing that occurs in traditional methods through a penalty term for lost energy, encouraging investment in batteries to store excess energy above the point of interconnection (POI). In addition, it is intended to cover gaps such as the operation in coupled markets with different execution periods to maximize the benefits of the investment made and to contemplate different generation alternatives together with storage. The presented method is tested through sizing and operation simulations to demonstrate its potential. The presented method is tested through sizing and operation simulations to demonstrate its potential. In scenario A, the best combination of solar energy, photovoltaic energy and storage, is chosen. In scenario B, it is shown how the curtailment of the oversizing is reduced in some months by more than 5%. In scenario C, for daily operation in coupled markets, it is possible to improve the benefits from 0.7% to 37.04% in the days of the year. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

18 pages, 4209 KiB

Open AccessArticle

Multi-Agent-Based Controller for Microgrids: An Overview and Case Study

by Necmi Altin, Süleyman Emre Eyimaya and Adel Nasiri

Energies 2023, 16(5), 2445; https://doi.org/10.3390/en16052445 - 3 Mar 2023

Cited by 8 | Viewed by 2077

Abstract

A microgrid can be defined as a grid of interconnected distributed energy resources, loads and energy storage systems. In microgrid systems containing renewable energy resources, the coordinated operation of distributed generation units is important to ensure the stability of the microgrid. A microgrid needs a successful control scheme to achieve its design goals. Undesirable situations such as distorted voltage profile and frequency fluctuations are significantly reduced by installing the appropriate hardware such as energy storage systems, and control strategies. The multi-agent system is one of the approaches used to control microgrids. The application of multi-agent systems in electric power systems is becoming popular because of their inherent benefits such as autonomy, responsiveness, and social ability. This study provides an overview of the agent concept and multi-agent systems, as well as reviews of recent research studies on multi-agent systems’ application in microgrid control systems. In addition, a multi-agent-based controller and energy management system design is proposed for the DC microgrid in the study. The designed microgrid is composed of a photovoltaic system consisting of 30 series-connected PV modules, a wind turbine, a synchronous generator, a battery-based energy storage system, critical and non-critical DC loads, the grid and the control system. The microgrid is controlled by the designed multi-agent-based controller. The proposed multi-agent-based controller has a distributed generation agent, battery agent, load agent and grid agent. The roles of each agent and communication among the agents are designed properly and coordinated to achieve control goals, which basically are the DC bus voltage quality and system stability. The designed microgrid and proposed multi-agent-based controller are tested for two different scenarios, and the performance of the controller has been verified with MATLAB/Simulink simulations. The simulation results show that the proposed controller provides constant DC voltage for any operation condition. Additionally, the system stability is ensured with the proposed controller for variable renewable generation and variable load conditions. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

17 pages, 5990 KiB

Open AccessArticle

Sizing of Hybrid Supercapacitors and Lithium-Ion Batteries for Green Hydrogen Production from PV in the Australian Climate

by Tarek Ibrahim, Tamas Kerekes, Dezso Sera, Shahrzad S. Mohammadshahi and Daniel-Ioan Stroe

Energies 2023, 16(5), 2122; https://doi.org/10.3390/en16052122 - 22 Feb 2023

Cited by 2 | Viewed by 2153

Abstract

Instead of storing the energy produced by photovoltaic panels in batteries for later use to power electric loads, green hydrogen can also be produced and used in transportation, heating, and as a natural gas alternative. Green hydrogen is produced in a process called electrolysis. Generally, the electrolyser can generate hydrogen from a fluctuating power supply such as renewables. However, due to the startup time of the electrolyser and electrolyser degradation accelerated by multiple shutdowns, an idle mode is required. When in idle mode, the electrolyser uses 10% of the rated electrolyser load. An energy management system (EMS) shall be applied, where a storage technology such as a lithium-ion capacitor or lithium-ion battery is used. This paper uses a state-machine EMS of PV microgrid for green hydrogen production and energy storage to manage the hydrogen production during the morning from solar power and in the night using the stored energy in the energy storage, which is sized for different scenarios using a lithium-ion capacitor and lithium-ion battery. The mission profile and life expectancy of the lithium-ion capacitor and lithium-ion battery are evaluated considering the system’s local irradiance and temperature conditions in the Australian climate. A tradeoff between storage size and cutoffs of hydrogen production as variables of the cost function is evaluated for different scenarios. The lithium-ion capacitor and lithium-ion battery are compared for each tested scenario for an optimum lifetime. It was found that a lithium-ion battery on average is 140% oversized compared to a lithium-ion capacitor, but a lithium-ion capacitor has a smaller remaining capacity of 80.2% after ten years of operation due to its higher calendar aging, while LiB has 86%. It was also noticed that LiB is more affected by cycling aging while LiC is affected by calendar aging. However, the average internal resistance after 10 years for the lithium-ion capacitor is 264% of the initial internal resistance, while for lithium-ion battery is 346%, making lithium-ion capacitor a better candidate for energy storage if it is used for grid regulation, as it requires maintaining a lower internal resistance over the lifetime of the storage. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

20 pages, 6757 KiB

Open AccessArticle

Handling Computation Hardness and Time Complexity Issue of Battery Energy Storage Scheduling in Microgrids by Deep Reinforcement Learning

by Zeyue Sun, Mohsen Eskandari, Chaoran Zheng and Ming Li

Energies 2023, 16(1), 90; https://doi.org/10.3390/en16010090 - 21 Dec 2022

Cited by 3 | Viewed by 1436

Abstract

With the development of microgrids (MGs), an energy management system (EMS) is required to ensure the stable and economically efficient operation of the MG system. In this paper, an intelligent EMS is proposed by exploiting the deep reinforcement learning (DRL) technique. DRL is employed as the effective method for handling the computation hardness of optimal scheduling of the charge/discharge of battery energy storage in the MG EMS. Since the optimal decision for charge/discharge of the battery depends on its state of charge given from the consecutive time steps, it demands a full-time horizon scheduling to obtain the optimum solution. This, however, increases the time complexity of the EMS and turns it into an NP-hard problem. By considering the energy storage system’s charging/discharging power as the control variable, the DRL agent is trained to investigate the best energy storage control method for both deterministic and stochastic weather scenarios. The efficiency of the strategy suggested in this study in minimizing the cost of purchasing energy is also shown from a quantitative perspective through programming verification and comparison with the results of mixed integer programming and the heuristic genetic algorithm (GA). Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

21 pages, 4099 KiB

Open AccessArticle

Renewable Energy Communities in Islands: A Maltese Case Study

by Alexander Micallef, Cyril Spiteri Staines and John Licari

Energies 2022, 15(24), 9518; https://doi.org/10.3390/en15249518 - 15 Dec 2022

Cited by 2 | Viewed by 1795

Abstract

Renewable energy communities are considered as key elements for transforming the present fossil fuel-based energy systems of islands into renewable-based energy systems. This study shows how renewable energy communities can be deployed in the Maltese context to achieve higher penetration of residential-scale photovoltaic systems. Case studies for five renewable energy communities in the Maltese LV distribution network have been analyzed in detail. A novel community battery energy storage sizing strategy was proposed to determine the optimal storage capacity at each energy community. The main objective of the community battery storage in each REC is to minimize the reverse power injection in the grid (minimize the total reverse energy and reverse peak power values), as well as to reduce the peak evening electricity demand. The optimal sizes for communal BESSs were determined to be of 57 kWh (EC 1), 55 kWh (EC 2), 31 kWh (EC 3), 37 kWh (EC 4) and 10 kWh (EC 5), respectively. The community storage systems were observed to reduce the overall impact of all five energy communities on the grid infrastructure. Power system simulations were performed for a typical spring day to evaluate the impact of communal BESS placement on the node voltages for all five energy communities. The results showed that the community storage was more effective at reducing the node rms voltage magnitudes when deployed at the end of the respective energy communities, rather than at the beginning of the community. During peak generation hours, reductions of up to 0.48% in the node rms voltage magnitudes were observed. This contrasts with reductions of only 0.19% when the community storage was deployed at the beginning of the energy communities. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

23 pages, 4785 KiB

Open AccessArticle

Technical and Economic Assessment of Battery Storage and Vehicle-to-Grid Systems in Building Microgrids

by Alexandre F. M. Correia, Pedro Moura and Aníbal T. de Almeida

Energies 2022, 15(23), 8905; https://doi.org/10.3390/en15238905 - 25 Nov 2022

Cited by 3 | Viewed by 2701

Abstract

In an electrical microgrid, distributed renewable generation is one of the main tools used to achieve energy sustainability, cost efficiency and autonomy from the grid. However, reliance on intermittent power sources will lead to a mismatch between generation and demand, causing problems for microgrid management. Flexibility is key to reducing the mismatch and providing a stable operation. In such a context, demand response and energy storage systems are the main factors that contribute to flexibility in a microgrid. This paper provides an assessment of the technical and economic impacts of a microgrid at the building level, considering photovoltaic generation, battery energy storage and the use of electric vehicles in a vehicle-to-building system. The main novel contributions of this work are the quantification of system efficiencies and the provision of insights into the design and implementation of microgrids using real on-site data. Several tests were conducted using real on-site data to calculate the overall efficiencies of the different assets during their operation. An economic assessment was carried out to evaluate the potential benefits of coordinating battery storage with a vehicle-to-building system regarding the flexibility and cost-efficient operation of the microgrid. The results show that these two systems effectively increase the levels of self-consumption and available flexibility, but the usefulness of private electric vehicles in public buildings is constrained by the schedules and parking times of the users. Furthermore, economic benefits are highly dependent on the variability of tariffs and the costs of energy storage systems and their degradation, as well as the efficiency of the equipment used in the conversion chain. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Graphical abstract

21 pages, 1857 KiB

Open AccessFeature PaperArticle

Optimizing Fuel Efficiency on an Islanded Microgrid under Varying Loads

by Joo Won Lee, Emily Craparo, Giovanna Oriti and Arthur Krener

Energies 2022, 15(21), 7943; https://doi.org/10.3390/en15217943 - 26 Oct 2022

Cited by 1 | Viewed by 1765

Abstract

Past studies of microgrids have been based on measurements of fuel consumption by generators under static loads. There is little information on the fuel efficiency of generators under time-varying loads. To help analyze the impact of time-varying loads on optimal generator operation and fuel consumption, we formulate a mixed-integer linear optimization model to plan generator and energy storage system (ESS) operation to satisfy known demands. Our model includes fuel consumption penalty terms on time-varying loads. We exercise the model on various scenarios and compare the resulting optimal fuel consumption and generator operation profiles. Our results show that the change in fuel efficiency between scenarios with the integration of ESS is minimal regardless of the imposed penalty placed on the generator. However, without the assistance of the ESS, the fuel consumption increases dramatically with the penalty imposed on the generator. The integration of an ESS improves fuel consumption because the ESS allows the generator to minimize power output fluctuation. While the presence of a penalty term has a clear impact on generator operation and fuel consumption, the exact type and weight of the penalty appears insignificant; this may provide useful insight for future studies in developing a real-time controller. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

26 pages, 4868 KiB

Open AccessArticle

Exact Feedback Linearization of a Multi-Variable Controller for a Bi-Directional DC-DC Converter as Interface of an Energy Storage System

by Gabriel R. Broday, Luiz A. C. Lopes and Gilney Damm

Energies 2022, 15(21), 7923; https://doi.org/10.3390/en15217923 - 25 Oct 2022

Cited by 3 | Viewed by 1180

Abstract

DC microgrids have shown to be a good approach for better accommodating stochastic renewable energy sources (RES) and for the charging of electric vehicles (EVs) at the distribution level. For this, fast-acting energy storage units (ESSs) are essential. This requires that both the bi-directional power converter topology and the control scheme present the right set of features. The ESS discussed in this paper consists of a new DC-DC converter based on a tapped inductor (TI) for a higher voltage gain at moderate duty cycles. The direction of the current in its intermediate inductor does not need to be reversed for power flow reversal, leading to a faster action. Moreover, it can employ a multi-state and multi-variable modulation scheme that eliminates the right half-plane (RHP) zero, common in boost-type converters. In order to achieve good dynamic performance across a wide range of operating points, a control scheme based on feedback linearization is developed. This paper presents the modeling of the five-switch DC-DC converter operating in the tri-state buck–boost mode. A systematic approach for deriving control laws for the TI current and output voltage based on exact state feedback linearization is discussed. The performance of the proposed control scheme is verified by simulation for a supercapacitor (SC)-based ESS. It is compared to that of a conventional control scheme for a dual-state buck–boost mode with cascaded PI controllers designed based on small-signal models. The results show that both control schemes work similarly well at the operating point that the conventional control scheme was designed for. However, only the proposed scheme allows the SC-based ESS to control the current injected into the DC microgrid with the voltage of the SC varying between the expected range of rated to half-rated. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

15 pages, 4835 KiB

Open AccessArticle

SOC Balancing and Coordinated Control Based on Adaptive Droop Coefficient Algorithm for Energy Storage Units in DC Microgrid

by Guizhen Tian, Yuding Zheng, Guangchen Liu and Jianwei Zhang

Energies 2022, 15(8), 2943; https://doi.org/10.3390/en15082943 - 17 Apr 2022

Cited by 12 | Viewed by 2248

Abstract

In order to achieve a state-of-charge (SOC) balance among multiple energy storage units (MESUs) in an islanded DC microgrid, a SOC balancing and coordinated control strategy based on the adaptive droop coefficient algorithm for MESUs is proposed. When the SOC deviation is significant, the droop coefficient for an energy storage unit (ESU) with a higher (or lower) SOC is set to a minimum value when discharging (or charging). The ESU with the higher (or lower) SOC is controlled to discharge (or charge) with the rated power, while the other ESU compensates for the remaining power when the demanded discharging (or charging) power is greater than the rated power of the individual ESU. Otherwise, when the demanded discharging (or charging) power is lower than the rated power of either ESU, the ESU with the higher (or lower) SOC releases (or absorbs) almost all the required power while the other ESU barely absorbs or releases power, thus quickly realizing SOC balancing. When the SOC deviation is slight, the fuzzy logic algorithm dynamically adjusts the droop coefficient and changes the power distribution relationship to balance the SOC accurately. Furthermore, a bus voltage recovery control scheme is employed to regulate the bus voltage, thus improving the voltage quality. The energy coordinated management strategy is adopted to ensure the power balance and stabilize the bus voltage in the DC microgrid. A simulation model is built in MATLAB/Simulink, and the simulation results demonstrate the effectiveness of the proposed control strategy in achieving fast and accurate SOC balance and regulating the bus voltage. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures

Figure 1

Review

Jump to: Research

24 pages, 2172 KiB

Open AccessReview

Review on Recent Strategies for Integrating Energy Storage Systems in Microgrids

by Ritu Kandari, Neeraj Neeraj and Alexander Micallef

Energies 2023, 16(1), 317; https://doi.org/10.3390/en16010317 - 27 Dec 2022

Cited by 15 | Viewed by 2730

Abstract

Energy security and the resilience of electricity networks have recently gained critical momentum as subjects of research. The challenges of meeting the increasing electrical energy demands and the decarbonisation efforts necessary to mitigate the effects of climate change have highlighted the importance of microgrids for the effective integration of renewable energy sources. Microgrids have been the focus of research for several years; however, there are still many unresolved challenges that need to be addressed. Energy storage systems are essential elements that provide reliability and stability in microgrids with high penetrations of renewable energy sources. This study provides a systematic review of the recent developments in the control and management of energy storage systems for microgrid applications. In the early sections, a summary of the microgrid topologies and architectures found in the recent literature is given. The main contributions and targeted applications by the energy storage systems in the microgrid applications is defined for each scenario. As various types of energy storage systems are currently being integrated for the reliable operation of the microgrids, the paper analyses the properties and limitations of the solutions proposed in the recent literature. The review that was carried out shows that a hybrid energy storage system performs better in terms of microgrid stability and reliability when compared to applications that use a simple battery energy storage system. Therefore, a case study for a DC microgrid with a hybrid energy storage system was modelled in MATLAB/Simulink. The presented results show the advantages of hybrid energy storage systems in DC microgrids. Full article

(This article belongs to the Special Issue Microgrids and the Integration of Energy Storage Systems)

► Show Figures