Editorial

3 pages, 134 KiB

Open AccessEditorial

Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids

by Maria Carmela Di Piazza

Energies 2024, 17(8), 1811; https://0-doi-org.brum.beds.ac.uk/10.3390/en17081811 - 10 Apr 2024

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Electrical microgrids (MG) have emerged as one of the most promising solutions for the energy transition of electrical power systems [...] Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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17 pages, 4783 KiB

Open AccessArticle

Integration of PV Sources in Prosumer Installations Eliminating Their Negative Impact on the Supplying Grid and Optimizing the Microgrid Operation

by Rozmysław Mieński, Irena Wasiak and Paweł Kelm

Energies 2023, 16(8), 3479; https://0-doi-org.brum.beds.ac.uk/10.3390/en16083479 - 16 Apr 2023

Cited by 4 | Viewed by 978

Abstract

This paper concerns the mitigation of voltage disturbances deteriorating power quality and disrupting the operation of LV distribution grids due to the high penetration of PV energy sources in prosumer installations. A novel control strategy for 3-phase 4-wire PV inverters is proposed, which [...] Read more.

This paper concerns the mitigation of voltage disturbances deteriorating power quality and disrupting the operation of LV distribution grids due to the high penetration of PV energy sources in prosumer installations. A novel control strategy for 3-phase 4-wire PV inverters is proposed, which ensures the transmission of PV active power and simultaneous compensation of load unbalance and reactive power, making the prosumer installation balanced and purely active. It results in the balance of phase voltages and the mitigation of their variability. Unlike other methods used for voltage regulation in LV grids, the proposed solution contributes to the reduction in losses, is simple, and does not require additional costs. In the paper, a control algorithm for the PV inverter is described. Its effectiveness was tested by simulation using a model of the real LV distribution grid developed in the PSCAD/EMTDC program. The results of the simulations are presented and evaluated. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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19 pages, 3711 KiB

Open AccessArticle

Bacterial Foraging Algorithm for a Neural Network Learning Improvement in an Automatic Generation Controller

by Sadeq D. Al-Majidi, Hisham Dawood Salman Altai, Mohammed H. Lazim, Mohammed Kh. Al-Nussairi, Maysam F. Abbod and Hamed S. Al-Raweshidy

Energies 2023, 16(6), 2802; https://0-doi-org.brum.beds.ac.uk/10.3390/en16062802 - 17 Mar 2023

Cited by 3 | Viewed by 1160

Abstract

The frequency diversion in hybrid power systems is a major challenge due to the unpredictable power generation of renewable energies. An automatic generation controller (AGC) system is utilised in a hybrid power system to correct the frequency when the power generation of renewable [...] Read more.

The frequency diversion in hybrid power systems is a major challenge due to the unpredictable power generation of renewable energies. An automatic generation controller (AGC) system is utilised in a hybrid power system to correct the frequency when the power generation of renewable energies and consumers’ load demand are changing rapidly. While a neural network (NN) model based on a back-propagation (BP) training algorithm is commonly used to design AGCs, it requires a complicated training methodology and a longer processing time. In this paper, a bacterial foraging algorithm (BF) was employed to enhance the learning of the NN model for AGCs based on adequately identifying the initial weights of the model. Hence, the training error of the NN model was addressed quickly when it was compared with the traditional NN model, resulting in an accurate signal prediction. To assess the proposed AGC, a power system with a photovoltaic (PV) generation test model was designed using MATLAB/Simulink. The outcomes of this research demonstrate that the AGC of the BF-NN-based model was effective in correcting the frequency of the hybrid power system and minimising its overshoot under various conditions. The BP-NN was compared to a PID, showing that the former achieved the lowest standard transit time of 5.20 s under the mismatching power conditions of load disturbance and PV power generation fluctuation. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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27 pages, 3798 KiB

Open AccessArticle

Electric Vehicle Charging Hub Power Forecasting: A Statistical and Machine Learning Based Approach

by Francesco Lo Franco, Mattia Ricco, Vincenzo Cirimele, Valerio Apicella, Benedetto Carambia and Gabriele Grandi

Energies 2023, 16(4), 2076; https://0-doi-org.brum.beds.ac.uk/10.3390/en16042076 - 20 Feb 2023

Cited by 2 | Viewed by 2126

Abstract

Electric vehicles (EVs) penetration growth is essential to reduce transportation-related local pollutants. Most countries are witnessing a rapid development of the necessary charging infrastructure and a consequent increase in EV energy demand. In this context, power demand forecasting is an essential tool for [...] Read more.

Electric vehicles (EVs) penetration growth is essential to reduce transportation-related local pollutants. Most countries are witnessing a rapid development of the necessary charging infrastructure and a consequent increase in EV energy demand. In this context, power demand forecasting is an essential tool for planning and integrating EV charging as much as possible with the electric grid, renewable sources, storage systems, and their management systems. However, this forecasting is still challenging due to several reasons: the still not statistically significant number of circulating EVs, the different users’ behavior based on the car parking scenario, the strong heterogeneity of both charging infrastructure and EV population, and the uncertainty about the initial state of charge (SOC) distribution at the beginning of the charge. This paper aims to provide a forecasting method that considers all the main factors that may affect each charging event. The users’ behavior in different urban scenarios is predicted through their statistical pattern. A similar approach is used to forecast the EV’s initial SOC. A machine learning approach is adopted to develop a battery-charging behavioral model that takes into account the different EV model charging profiles. The final algorithm combines the different approaches providing a forecasting of the power absorbed by each single charging session and the total power absorbed by charging hubs. The algorithm is applied to different parking scenarios and the results highlight the strong difference in power demand among the different analyzed cases. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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21 pages, 7086 KiB

Open AccessFeature PaperArticle

Optimal Management of Battery and Fuel Cell-Based Decentralized Generation in DC Shipboard Microgrids

by Massimiliano Luna, Giuseppe La Tona, Angelo Accetta, Marcello Pucci, Andrea Pietra and Maria Carmela Di Piazza

Energies 2023, 16(4), 1682; https://0-doi-org.brum.beds.ac.uk/10.3390/en16041682 - 08 Feb 2023

Cited by 5 | Viewed by 1285

Abstract

This paper proposes an energy management system (EMS) that aims at managing the modular direct current (DC) microgrids (MGs) of a hybrid DC/AC power system onboard cruise ships. Each shipboard microgrid is an electrically self-sufficient system supplied only by a fuel cell (FC) [...] Read more.

This paper proposes an energy management system (EMS) that aims at managing the modular direct current (DC) microgrids (MGs) of a hybrid DC/AC power system onboard cruise ships. Each shipboard microgrid is an electrically self-sufficient system supplied only by a fuel cell (FC) and a Lithium battery, and it powers the ship’s hotel services. However, continuously varying power demand profiles negatively affect the FC. Thus, the proposed EMS aims to minimize the FC operating point excursion on the source’s characteristic. This goal is pursued by exploiting the battery capability to manage load fluctuations and compensate for power demand forecasting errors. Furthermore, it is accomplished while satisfying all the operational constraints of the shipboard microgrids and ensuring daily battery charging/discharging cycles. The proposed EMS is based on two subsystems: (1) a rule-based microgrid supervisor, which makes the EMS capable of managing black start, normal operating conditions, and transient or faulty conditions; (2) an energy management (EM) algorithm, which allows achieving the desired goal without oversizing the battery, thus granting the cost-effectiveness of the solution and a reduced impact on technical volumes/weights on board. The EMS was tested with specific reference to a real-world case study, i.e., a 48,000 gross tonnage cruise ship under different operating scenarios, including black start and multi-day period operation of shipboard MGs. Test results showed that the operating points of the FC were always in the neighborhood of the point chosen by the MG designer, that the voltage variations were always well below 5%, guaranteeing stable operation, and that the black start operation was suitably handled by the EMS. According to the obtained results, the effectiveness of the proposed approach was assessed. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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25 pages, 4900 KiB

Open AccessArticle

Optimal Sizing and Environ-Economic Analysis of PV-BESS Systems for Jointly Acting Renewable Self-Consumers

by Nicola Blasuttigh, Simone Negri, Alessandro Massi Pavan and Enrico Tironi

Energies 2023, 16(3), 1244; https://0-doi-org.brum.beds.ac.uk/10.3390/en16031244 - 23 Jan 2023

Cited by 10 | Viewed by 1792

Abstract

Future residential applications could benefit from nanogrids that integrate photovoltaics (PV) and battery energy storage systems (BESS), especially after the establishment of recent European Community directives on renewable energy communities (RECs) and jointly acting renewable self-consumers (JARSCs). These entities consist of aggregations of [...] Read more.

Future residential applications could benefit from nanogrids that integrate photovoltaics (PV) and battery energy storage systems (BESS), especially after the establishment of recent European Community directives on renewable energy communities (RECs) and jointly acting renewable self-consumers (JARSCs). These entities consist of aggregations of users who share locally produced energy with the aim of gaining economic, environmental, and social benefits by enhancing their independence from the electricity grid. In this regard, the sizing of the PV and BESS systems is an important aspect that results in a trade-off from technical, economic, and environmental perspectives. To this end, this paper presents an investigation on the optimal PV-BESS system sizing of a condominium acting as a JARSC community, which includes a common PV plant and EMS, operated by rule-based criteria. PV-BESS sizing results are investigated from economic and environmental perspectives, considering a case study located in Milan, Italy. In these regards, in addition to the common techno-economic criteria, carbon dioxide emissions are considered with particular attention, as their reduction is the driving ethos behind recent EU directives. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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24 pages, 6156 KiB

Open AccessFeature PaperArticle

MPPT Solution for Commercial Small Wind Generation Systems with Grid Connection

by Carlos Andres Ramos-Paja, Elkin Edilberto Henao-Bravo and Andres Julian Saavedra-Montes

Energies 2023, 16(2), 719; https://0-doi-org.brum.beds.ac.uk/10.3390/en16020719 - 07 Jan 2023

Cited by 1 | Viewed by 1350

Abstract

Power generation using small wind turbines connected to AC grids has been gaining attention and contributions in recent years. As small wind turbines are connected to remote areas as support energy systems, there are not extensive contributions connecting those small turbines to AC [...] Read more.

Power generation using small wind turbines connected to AC grids has been gaining attention and contributions in recent years. As small wind turbines are connected to remote areas as support energy systems, there are not extensive contributions connecting those small turbines to AC grids. This paper presents the integration of a small wind generation system which is AC-grid-connected. The system is composed of a 160 W commercial small wind turbine with a permanent magnet synchronous generator and a 140 W Texas Instruments (Dallas, TX, USA) development kit devoted to connecting photovoltaic panels to AC grids. Several experimental tests were developed to characterize the devices, e.g., to obtain the power–current curves of the synchronous generator. Moreover, a mathematical model of the flyback converter is developed in detail in order to design a new converter controller. All the control capacity of the development kit is used to extract the maximum power of the synchronous generator, to reject the oscillation produced by the inverter and to connect the system to the AC grid. Experimental results show that is possible to integrate these devices to provide energy to power systems with some achievable adaptations. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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23 pages, 5849 KiB

Open AccessArticle

Control of a Three-Phase Current Source Rectifier for H₂ Storage Applications in AC Microgrids

by Quentin Combe, Alireza Abasian, Serge Pierfederici, Mathieu Weber and Stéphane Dufour

Energies 2022, 15(7), 2436; https://0-doi-org.brum.beds.ac.uk/10.3390/en15072436 - 25 Mar 2022

Cited by 4 | Viewed by 1951

Abstract

The share of electrical energy from renewable sources has increased considerably in recent years in an attempt to reduce greenhouse gas emissions. To mitigate the uncertainties of these sources and to balance energy production with consumption, an energy storage system (ESS) based on [...] Read more.

The share of electrical energy from renewable sources has increased considerably in recent years in an attempt to reduce greenhouse gas emissions. To mitigate the uncertainties of these sources and to balance energy production with consumption, an energy storage system (ESS) based on water electrolysis to produce hydrogen is studied. It can be applied to AC microgrids, where several renewable energy sources and several loads may be connected, which is the focus of the study. When excess electricity production is converted into hydrogen via water electrolysis, low DC voltages and high currents are applied, which needs specific power converters. The use of a three-phase, buck-type current source converter, in a single conversion stage, allows for an adjustable DC voltage to be obtained at the terminals of the electrolyzer from a three-phase AC microgrid. The voltage control is preferred to the current control in order to improve the durability of the system. The classical control of the buck-type rectifier is generally done using two loops that correspond only to the control of its output variables. The lack of control of the input variables may generate oscillations of the grid current. Our contribution in this article is to propose a new control for the buck-type rectifier that controls both the input and output variables of the converter to avoid these grid current oscillations, without the use of active damping methods. The suggested control method is based on an approach using the flatness properties of differential systems: it ensures the large-signal stability of the converter. The proposed control shows better results than the classical control, especially in oscillation mitigation and dynamic performances with respect to the rejection of disturbances caused by a load step. Full article

(This article belongs to the Special Issue Volume II: Energy Management Systems for Optimal Operation of Electrical Micro/Nanogrids)

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