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Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids

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 (20 September 2021) | Viewed by 23297

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Guest Editor
Consiglio Nazionale delle Ricerche (CNR) – Istituto di Ingegneria del Mare (INM), Via Ugo La Malfa, 153, 90146 Palermo, Italy
Interests: shipboard electrical systems; electric power generation by renewable sources; power electronics and electrical drives; EMI/EMC; energy management systems (EMSs); smart micro/nanogrids
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Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions to a Special Issue of Energies on the subject area of energy management systems for optimal operation of electrical microgrids and nanogrids.

Energy management systems (EMSs) have been introduced in electrical power systems to perform optimized operations of the electrical grid infrastructure and to provide support to the grid operator in terms of optimized decisions. In electrical micro/nanogrids, the development of EMSs is crucial to correctly handling uncertainties and intermittency of renewables. Through their key functions (monitoring, control, optimization of flows, and use of electrical power), EMSs allow customers to play an active role in the energy market.

The EMSs proposed so far were not conceived to foster their widespread and fast adoption. Several issues remain to be tackled: EMSs should seamlessly integrate with the ecosystem of micro/nano grid devices and appliances, and they should interfere as little as possible with the comfort and habits of electricity market customers. The energy management algorithms should simultaneously provide advantages for both the end-user and the grid operator.

This Special Issue will address the development of EMSs specifically intended for the otimal operation of electrical micro/nanogrids. Topics of interest for publication include, but are not limited to:

  • Optimization of electrical power flows in micro/nanogrids;
  • EMSs for optimal integration and operation of renewables in micro/nanogrids;
  • EMSs for optimal integration and operation of energy storage systems;
  • EMSs for smart buildings;
  • EMSs for vehicle applications;
  • Forecasting techniques for EMSs;
  • Demand-side management;
  • Micro/nanogrid stability issues; and
  • Energy management algorithms implementation issues.
Dr. Maria Carmela Di Piazza
Guest Editor

Manuscript Submission Information

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Keywords

  • Electrical power systems
  • Micro/nanogrids
  • Power electronics
  • Renewable energy sources
  • Electrical storage systems
  • Optimization algorithm
  • Machine learning
  • Forecasting
  • Embedded systems
  • Internet of Things (IoT)

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Related Special Issue

Published Papers (8 papers)

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Editorial

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3 pages, 156 KiB  
Editorial
Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids
by Maria Carmela Di Piazza
Energies 2021, 14(24), 8469; https://doi.org/10.3390/en14248469 - 15 Dec 2021
Viewed by 2126
Abstract
Energy management systems (EMSs) have been introduced in electrical power systems to optimize operations of the electrical grid infrastructure and to provide support to the grid operator in terms of optimized decisions [...] Full article

Research

Jump to: Editorial

11 pages, 423 KiB  
Article
Electric Vehicle Fleets as Balancing Instrument in Micro-Grids
by Giambattista Gruosso and Fredy Orlando Ruiz
Energies 2021, 14(22), 7616; https://doi.org/10.3390/en14227616 - 15 Nov 2021
Cited by 7 | Viewed by 1940
Abstract
Micro-grids have become the building block of modern energy systems, where distributed resources are the characterizing feature. The charging operation of electric vehicles can be exploited as a flexible load to achieve operational goals of the micro-grid. In the particular case of car-sharing [...] Read more.
Micro-grids have become the building block of modern energy systems, where distributed resources are the characterizing feature. The charging operation of electric vehicles can be exploited as a flexible load to achieve operational goals of the micro-grid. In the particular case of car-sharing fleets, the degrees of freedom in the charging procedures are reduced when compared to private users. In this work, we illustrate how a car sharing fleet can be incorporated as a flexible load in the micro-grid management system. A linear optimization problem is formulated, where the cost function makes a trade-off between the gain in flexibility in the micro-grid and the loss incurred by the car-sharing service for delaying the recharging procedure of the EV. The proposed approach is evaluated on a data set of charging events generated by a real car-sharing fleet showing that the EMS allows reducing the daily peak demand requested to the public grid and diminishes the operational costs. Full article
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19 pages, 4081 KiB  
Article
Model Predictive Control for Efficient Management of Energy Resources in Smart Buildings
by Francesco Simmini, Tommaso Caldognetto, Mattia Bruschetta, Enrico Mion and Ruggero Carli
Energies 2021, 14(18), 5592; https://doi.org/10.3390/en14185592 - 7 Sep 2021
Cited by 11 | Viewed by 3127
Abstract
Efficient management of energy resources is crucial in smart buildings. In this work, model predictive control (MPC) is used to minimize the economic costs of prosumers equipped with production units, energy storage systems, and electric vehicles. To this purpose, the predictive control manages [...] Read more.
Efficient management of energy resources is crucial in smart buildings. In this work, model predictive control (MPC) is used to minimize the economic costs of prosumers equipped with production units, energy storage systems, and electric vehicles. To this purpose, the predictive control manages the available energy resources by exploiting future information about energy prices, absorption and production power profiles, and electric vehicle (EV) usage, such as times of departure and arrival and predicted energy consumption. The predictive control is compared with a rule-based technique, herein referred to as a heuristic approach, that acts in an instant-by-instant fashion without considering any future information. The reported results show that the studied predictive approach allows one to achieve charging profiles that adapt to variable operating conditions, aiming at optimal performances in terms of economic cost minimization in time-varying price scenarios, reduction of rms current stresses, and recharging capability of EV batteries. Specifically, unlike the heuristic method, the MPC approach is proven to be capable of efficiently managing the available energy resources to ensure a full recharge of the EV battery during nighttime while always respecting all system constraints. In addition, the proposed control is shown to be capable of keeping the peak power absorption from the grid constrained within set limits, which is a valuable feature in scenarios with widespread adoption of EVs in order to limit the stress on the electrical system. Full article
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23 pages, 2932 KiB  
Article
A Comparison of Time-Domain Implementation Methods for Fractional-Order Battery Impedance Models
by Brian Ospina Agudelo, Walter Zamboni and Eric Monmasson
Energies 2021, 14(15), 4415; https://doi.org/10.3390/en14154415 - 22 Jul 2021
Cited by 21 | Viewed by 2386
Abstract
This paper is a comparative study of the multiple RC, Oustaloup and Grünwald–Letnikov approaches for time domain implementations of fractional-order battery models. The comparisons are made in terms of accuracy, computational burden and suitability for the identification of impedance parameters from time-domain measurements. [...] Read more.
This paper is a comparative study of the multiple RC, Oustaloup and Grünwald–Letnikov approaches for time domain implementations of fractional-order battery models. The comparisons are made in terms of accuracy, computational burden and suitability for the identification of impedance parameters from time-domain measurements. The study was performed in a simulation framework and focused on a set of ZARC elements, representing the middle frequency range of Li-ion batteries’ impedance. It was found that the multiple RC approach offers the best accuracy–complexity compromise, making it the most interesting approach for real-time battery simulation applications. As for applications requiring the identification of impedance parameters, the Oustaloup approach offers the best compromise between the goodness of the obtained frequency response and the accuracy–complexity requirements. Full article
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16 pages, 2887 KiB  
Article
Effect of Daily Forecasting Frequency on Rolling-Horizon-Based EMS Reducing Electrical Demand Uncertainty in Microgrids
by Giuseppe La Tona, Maria Carmela Di Piazza and Massimiliano Luna
Energies 2021, 14(6), 1598; https://doi.org/10.3390/en14061598 - 13 Mar 2021
Cited by 7 | Viewed by 1946
Abstract
Accurate forecasting is a crucial task for energy management systems (EMSs) used in microgrids. Despite forecasting models destined to EMSs having been largely investigated, the analysis of criteria for the practical execution of this task, in the framework of an energy management algorithm, [...] Read more.
Accurate forecasting is a crucial task for energy management systems (EMSs) used in microgrids. Despite forecasting models destined to EMSs having been largely investigated, the analysis of criteria for the practical execution of this task, in the framework of an energy management algorithm, has not been properly investigated yet. On such a basis, this paper aims at exploring the effect of daily forecasting frequency on the performance of rolling-horizon EMSs devised to reduce demand uncertainty in microgrids by adhering to a reference planned profile. Specifically, the performance of a sample EMS, where the forecasting task is committed to a nonlinear autoregressive network with exogenous inputs (NARX) artificial neural network (ANN), has been studied under different daily forecasting frequencies, revealing a representative trend relating the forecasting execution frequency in the EMS and the reduction of uncertainty in the electrical demand. On the basis of such a trend, it is possible to establish how often is convenient to repeat the forecasting task for obtaining increasing performance of the EMS. The obtained results have been generalized by extending the analysis to different test scenarios, whose results have been found coherent with the identified trend. Full article
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19 pages, 6728 KiB  
Article
Real-Time Validation of Power Flow Control Method for Enhanced Operation of Microgrids
by Hossein Abedini, Tommaso Caldognetto, Paolo Mattavelli and Paolo Tenti
Energies 2020, 13(22), 5959; https://doi.org/10.3390/en13225959 - 15 Nov 2020
Cited by 15 | Viewed by 2247
Abstract
This paper describes a control methodology for electronic power converters distributed in low-voltage microgrids and its implementation criteria in general microgrid structures. In addition, a real-time simulation setup is devised, implemented, and discussed to validate the control operation in a benchmark network. Considering [...] Read more.
This paper describes a control methodology for electronic power converters distributed in low-voltage microgrids and its implementation criteria in general microgrid structures. In addition, a real-time simulation setup is devised, implemented, and discussed to validate the control operation in a benchmark network. Considering these key aspects, it is shown that operational constraints regarding the power delivered by sources, flowing through network branches, and exchanged at the point of connection with the main grid can generally be fulfilled by the presented control approach. The control is performed considering a cost function aiming at optimizing various operation indexes, including distribution losses, current stresses on feeders, voltage deviations. The control system allows an enhanced operation of the microgrid, specifically, it allows dynamic and accurate power flow control enabling the provision of ancillary services to the upstream grid, like the demand–response, by exploiting the available infrastructure and the energy resources. Then, the validation of the approach is reported by using a real-time simulation setup with accurate models of the power electronic converters and related local controllers, of the grid infrastructure, of the power flow controller, and of the communication network used for data exchange. It is also shown that the implemented platform allows to fully reproduce, analyze, and finally validate all the relevant steady-state and dynamic behaviors related in the considered scenario. Full article
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24 pages, 7604 KiB  
Article
Investigation of Black-Starting and Islanding Capabilities of a Battery Energy Storage System Supplying a Microgrid Consisting of Wind Turbines, Impedance- and Motor-Loads
by Jürgen Marchgraber and Wolfgang Gawlik
Energies 2020, 13(19), 5170; https://doi.org/10.3390/en13195170 - 5 Oct 2020
Cited by 14 | Viewed by 3557
Abstract
Microgrids are small scale electrical power systems that comprise distributed energy resources (DER), loads, and storage devices. The integration of DER into the electrical power system basically allows the clustering of small parts of the main grid into Microgrids. Due to the increasing [...] Read more.
Microgrids are small scale electrical power systems that comprise distributed energy resources (DER), loads, and storage devices. The integration of DER into the electrical power system basically allows the clustering of small parts of the main grid into Microgrids. Due to the increasing amount of renewable energy, which is integrated into the main grid, high power fluctuations are expected to become common in the next years. This carries the risk of blackouts to be also more likely in the future. Microgrids hold the potential of increasing reliability of supply, since they are capable of providing a backup supply during a blackout of the main grid. This paper investigates the black-starting and islanding capabilities of a battery energy storage system (BESS) in order to provide a possible backup supply for a small part of the main grid. Based on field tests in a real Microgrid, the backup supply of a residential medium voltage grid is tested. Whereas local wind turbines within this grid section are integrated into this Microgrid during the field test, the supply of households is reproduced by artificial loads consisting of impedance- and motor loads, since a supply of real households carries a high risk of safety issues and open questions regarding legal responsibility. To operate other DER during the island operation of such a Microgrid, control mechanisms have to ensure the power capabilities and energy reserves of the BESS to be respected. Since the operation during a backup supply of such a Microgrid requires a simple implementation, this paper presents a simple master–slave control approach, which influences the power output of other DER based on frequency characteristics without the need for further communication. Besides the operation of other DER, the capability to handle load changes during island operation while ensuring acceptable power quality is crucial for such a Microgrid. With the help of artificial loads, significant load changes of the residential grid section are reproduced and their influence on power quality is investigated during the field tests. Besides these load changes, the implementation and behavior of the master–slave control approach presented in this paper is tested. To prepare these field tests, simulations in Matlab/Simulink are performed to select appropriate sizes for the artificial loads and to estimate the expected behavior during the field tests. The field tests prove that a backup supply of a grid section during a blackout of the main grid by a BESS is possible. By creating the possibility of operating other DER during this backup supply, based on the master–slave control approach presented in this paper, the maximum duration for this backup supply can be increased. Full article
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23 pages, 2713 KiB  
Article
Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation
by Mahmoud Elkazaz, Mark Sumner, Seksak Pholboon, Richard Davies and David Thomas
Energies 2020, 13(13), 3436; https://doi.org/10.3390/en13133436 - 3 Jul 2020
Cited by 23 | Viewed by 4044
Abstract
Home energy management systems (HEMS) are a key technology for managing future electricity distribution systems as they can shift household electricity usage away from peak consumption times and can reduce the amount of local generation penetrating into the wider distribution system. In doing [...] Read more.
Home energy management systems (HEMS) are a key technology for managing future electricity distribution systems as they can shift household electricity usage away from peak consumption times and can reduce the amount of local generation penetrating into the wider distribution system. In doing this they can also provide significant cost savings to domestic electricity users. This paper studies a HEMS which minimizes the daily energy costs, reduces energy lost to the utility, and improves photovoltaic (PV) self-consumption by controlling a home battery storage system (HBSS). The study assesses factors such as the overnight charging level, forecasting uncertainty, control sample time and tariff policy. Two management strategies have been used to control the HBSS; (1) a HEMS based on a real-time controller (RTC) and (2) a HEMS based on a model predictive controller (MPC). Several methods have been developed for home demand energy forecasting and PV generation forecasting and their impact on the HEMS is assessed. The influence of changing the battery’s capacity and the PV system size on the energy costs and the lost energy are also evaluated. A significant reduction in energy costs and energy lost to the utility can be achieved by combining a suitable overnight charging level, an appropriate sample time, and an accurate forecasting tool. The HEMS has been implemented on an experimental house emulation system to demonstrate it can operate in real-time. Full article
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