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Sustainability of Smart Energy Grids: Pathway for Achieving a Green Smart Energy Grid

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 27157

Special Issue Editors


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Guest Editor
Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: fuel cells; advanced optimization techniques; solar thermal systems; concentrating photovoltaic/thermal photovoltaic systems; energy saving in buildings; solar heating and cooling; organic Rankine cycles; geothermal energy; dynamic simulations of energy systems; renewable polygeneration systems
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Guest Editor

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Guest Editor
Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: sustainable mobility; electric vehicles fed by renewables; polygeneration plants; district heating/cooling networks (4th and 5th gen); cogeneration/trigeneration; reduction in primary energy consumption
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the framework of the decarbonization of the building sector, several strategies were investigates. Smart energy grids fed by renewables or coupled with innovative technologies may be a promising solution for addressing this issue. Thus, this Special Issue aims at collecting accounts of recent work and research dealing with the sustainability of green smart energy grids. The papers must focus on the possible integration of different novel technologies and renewable energy sources in a smart energy grid while also assessing the environmental benefits and sustainability of these solutions. Moreover, papers may also focus on control strategies able to improve the integration of renewable and innovative technologies with smart energy grids. Studies including dynamic analyses and system optimizations are welcomed. Papers are invited in areas relevant to smart energy grids, including but not limited to the following topics:

  • 4th generation district heating and cooling networks fed by renewables or coupled with innovative technologies
  • 5th generation district heating and cooling networks fed by renewables or coupled with innovative technologies
  • Dynamic analysis of control strategies able to significantly reduce the environmental impact of district adopting 4th and 5th generation DHCs
  • Electric vehicles
  • Control strategies or solutions for peak shaving and peak shifting with the aim of avoid grid unbalancing and overvoltage
  • Optimal coupling of several renewable energy sources for addressing the issue of peak power production and peak of power demand

Prof. Dr. Francesco Calise
Dr. Maria Vicidomini
Dr. Francesco Liberato Cappiello
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

  • smart energy district
  • district heating and cooling
  • energy efficiency
  • sustainability
  • renewable energy
  • electric vehicle
  • storage system
  • optimization analysis

Published Papers (11 papers)

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Research

23 pages, 4059 KiB  
Article
Integrated Thermodynamic and Control Modeling of an Air-to-Water Heat Pump for Estimating Energy-Saving Potential and Flexibility in the Building Sector
by Dhirendran Munith Kumar, Pietro Catrini, Antonio Piacentino and Maurizio Cirrincione
Sustainability 2023, 15(11), 8664; https://doi.org/10.3390/su15118664 - 26 May 2023
Cited by 1 | Viewed by 1452
Abstract
Reversible heat pumps are increasingly adopted for meeting the demand for space heating and cooling in buildings. These technologies will play a key role not only in the decarbonization of space air conditioning but also in the development of 100% renewable energy systems. [...] Read more.
Reversible heat pumps are increasingly adopted for meeting the demand for space heating and cooling in buildings. These technologies will play a key role not only in the decarbonization of space air conditioning but also in the development of 100% renewable energy systems. However, to assess the achievable benefits through the adoption of these technologies in novel applications, reliable models are needed, capable of simulating both their steady-state operation and dynamic response at different conditions in terms of heating loads, outdoor temperatures, and so on. The operation of heat pumps is often investigated by highly simplified models, using performance data drawn from catalogs and paying scarce attention to the critical influence of controllers. In this respect, this paper proposed an integrated thermodynamic and control modeling for a reversible air-to-water heat pump. The study considered a heat pump alternatively equipped with variable-speed compressors and constant-speed compressors with sequential control. The developed modeling was then used to investigate the operation of an air-to-water heat pump serving an office building in Italy. Results show that the model provided insights into the transient operation of variable-speed heat pumps (e.g., the settling time). Regarding constant-speed heat pumps, the model provided hints of interest to the control engineer to prevent, in the examined case study, the risk of quick compressors cycling on low-load heating days or when low-temperature heating devices are supplied. Finally, using a control strategy based on a heating curve for the variable-speed heat pump, results show the potential for a sensible increase in the average coefficient of performance, from 17% up to 50%. Full article
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21 pages, 4277 KiB  
Article
An ANFIS-Fuzzy Tree-GA Model for a Hospital’s Electricity Purchasing Decision-Making Process Integrated with Virtual Cost Concept
by Dimitrios K. Panagiotou and Anastasios I. Dounis
Sustainability 2023, 15(10), 8419; https://doi.org/10.3390/su15108419 - 22 May 2023
Cited by 1 | Viewed by 1006
Abstract
In deregulated electricity markets, accurate load and price prediction play an essential role in the Demand Response (DR) context. Although electrical load and price demonstrate a strong correlation which is not linear, price prediction may be a task much more challenging than load [...] Read more.
In deregulated electricity markets, accurate load and price prediction play an essential role in the Demand Response (DR) context. Although electrical load and price demonstrate a strong correlation which is not linear, price prediction may be a task much more challenging than load prediction due to several factors. The volatility of electricity price compared to load makes price prediction a complex procedure. To perform purchasing decisions commercial consumers may rely on short term price and load prediction. A system which combines Adaptive Neuro-Fuzzy Systems (ANFIS) which predict Load Marginal Prices (LMPs) and electricity consumption is presented in this study. Furthermore, the Virtual Cost (VC) concept, which is the sum of the products between the predicted hourly consumption values and their respective predicted LMPs is introduced. Virtual Cost is assessed with a Fuzzy Decision Tree (FDT) compared to a threshold set by the customer. If needed, the amount of electrical energy that a healthcare facility must purchase at every hour of the day may be scheduled using Genetic Algorithm (GA) to meet the threshold criterion. This hybrid model proved economically beneficial for the facility, which is of great importance since the saved resources may be utilized to improve its infrastructures or for other purposes with social impact. The novelty of the proposed method is the utilization of ANFIS, Fuzzy Decision Trees and Genetic Algorithms combined as tools to improve the hospital’s energy and economic efficiency, achieving a reduction of the electricity costs up to 21.95 percent. The contribution of the study is to provide a reliable decision-making tool to everyone who participates in the electricity market in order to perform profitable energy scheduling automatically and accurately. Full article
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26 pages, 4382 KiB  
Article
A Roadmap for the Design, Operation and Monitoring of Renewable Energy Communities in Italy
by Emanuele Cutore, Alberto Fichera and Rosaria Volpe
Sustainability 2023, 15(10), 8118; https://doi.org/10.3390/su15108118 - 16 May 2023
Cited by 4 | Viewed by 1721
Abstract
Renewable energy communities (RECs) aim at achieving economic, environmental, and social benefits for members and for society. This paper presents a roadmap for the design, operation, and monitoring of renewable energy communities in Italy, fundamental to guide and orient any stakeholder involved in [...] Read more.
Renewable energy communities (RECs) aim at achieving economic, environmental, and social benefits for members and for society. This paper presents a roadmap for the design, operation, and monitoring of renewable energy communities in Italy, fundamental to guide and orient any stakeholder involved in the decision-making process of a REC. The roadmap is inspired by the Deming Cycle, also known as Plan-Do-Check-Act, which provides a framework for continuous improvement and standardization of the procedures. To demonstrate the practical application of the roadmap, a real case study is presented for Italian energy communities, making full adoption of data derived from official databases and using a real urban district as a case study. The findings of phase I in the “do” stage of the roadmap indicate that the REC could lead to a decrease in carbon emissions of roughly 38% and could support 51 to 67 families through REC’s revenues, depending on the installed PV capacity. Furthermore, both physical self-consumption and virtual self-consumption schemes assist in the sustainable transition of the built environment, where consumers have a significant impact on the electrical markets. Therefore, these results validate the roadmap’s effectiveness in promoting an informed design and implementation of RECs while guiding energy, social, and political decisions. Full article
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18 pages, 3539 KiB  
Article
WAMS-Based Fuzzy Logic PID Secondary Voltage Control of the Egyptian Grid
by Omar H. Abdalla and Hady H. Fayek
Sustainability 2023, 15(4), 3338; https://doi.org/10.3390/su15043338 - 11 Feb 2023
Cited by 1 | Viewed by 1959
Abstract
This paper presents the application of fuzzy logic PID secondary voltage control to the Egyptian power system model. The study included tertiary voltage control, Wide Area Measurement System (WAMS) configuration, a selection of pilot buses, and fuzzy logic PID secondary voltage control to [...] Read more.
This paper presents the application of fuzzy logic PID secondary voltage control to the Egyptian power system model. The study included tertiary voltage control, Wide Area Measurement System (WAMS) configuration, a selection of pilot buses, and fuzzy logic PID secondary voltage control to improve the system performance. The secondary voltage control was applied using a fuzzy PID coordinated controller, a reactive power integral controller, Automatic Voltage Regulators (AVRs), and regional generators. The tertiary voltage control was implemented based on the optimal power flow to maximize the reactive power reserve. A novel optimization technique is presented to select pilot buses based on different operating conditions and compared to other techniques. The optimal WAMS configuration included the best allocation of Phasor Measurement Units (PMUs), Phasor Data Concentrators (PDCs), and the required communication infrastructure considering geographical regions with minimum cost. The Egyptian power grid considering 500/220 kV level is simulated by using DIgSILENT software to perform static and dynamic analyses, while the WAMS optimization problems and fuzzy logic PID controller design are performed by employing MATLAB software. Full article
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26 pages, 2137 KiB  
Article
Electric Vehicle Charging System in the Smart Grid Using Different Machine Learning Methods
by Tehseen Mazhar, Rizwana Naz Asif, Muhammad Amir Malik, Muhammad Asgher Nadeem, Inayatul Haq, Muhammad Iqbal, Muhammad Kamran and Shahzad Ashraf
Sustainability 2023, 15(3), 2603; https://doi.org/10.3390/su15032603 - 1 Feb 2023
Cited by 29 | Viewed by 6367
Abstract
Smart cities require the development of information and communication technology to become a reality (ICT). A “smart city” is built on top of a “smart grid”. The implementation of numerous smart systems that are advantageous to the environment and improve the quality of [...] Read more.
Smart cities require the development of information and communication technology to become a reality (ICT). A “smart city” is built on top of a “smart grid”. The implementation of numerous smart systems that are advantageous to the environment and improve the quality of life for the residents is one of the main goals of the new smart cities. In order to improve the reliability and sustainability of the transportation system, changes are being made to the way electric vehicles (EVs) are used. As EV use has increased, several problems have arisen, including the requirement to build a charging infrastructure, and forecast peak loads. Management must consider how challenging the situation is. There have been many original solutions to these problems. These heavily rely on automata models, machine learning, and the Internet of Things. Over time, there have been more EV drivers. Electric vehicle charging at a large scale negatively impacts the power grid. Transformers may face additional voltage fluctuations, power loss, and heat if already operating at full capacity. Without EV management, these challenges cannot be solved. A machine-learning (ML)-based charge management system considers conventional charging, rapid charging, and vehicle-to-grid (V2G) technologies while guiding electric cars (EVs) to charging stations. This operation reduces the expenses associated with charging, high voltages, load fluctuation, and power loss. The effectiveness of various machine learning (ML) approaches is evaluated and compared. These techniques include Deep Neural Networks (DNN), K-Nearest Neighbors (KNN), Long Short-Term Memory (LSTM), Random Forest (RF), Support Vector Machine (SVM), and Decision Tree (DT) (DNN). According to the results, LSTM might be used to give EV control in certain circumstances. The LSTM model’s peak voltage, power losses, and voltage stability may all be improved by compressing the load curve. In addition, we keep our billing costs to a minimum, as well. Full article
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16 pages, 3441 KiB  
Article
Thermoeconomic Optimization of a Polygeneration System Based on a Solar-Assisted Desiccant Cooling
by Luis Gabriel Gesteira, Javier Uche, Francesco Liberato Cappiello and Luca Cimmino
Sustainability 2023, 15(2), 1516; https://doi.org/10.3390/su15021516 - 12 Jan 2023
Cited by 7 | Viewed by 1180
Abstract
This paper presents a thermoeconomic analysis of a polygeneration system based on solar-assisted desiccant cooling. The overall plant layout supplies electricity, space heating and cooling, domestic hot water, and freshwater for a residential building. The system combines photovoltaic/thermal collectors, photovoltaic panels, and a [...] Read more.
This paper presents a thermoeconomic analysis of a polygeneration system based on solar-assisted desiccant cooling. The overall plant layout supplies electricity, space heating and cooling, domestic hot water, and freshwater for a residential building. The system combines photovoltaic/thermal collectors, photovoltaic panels, and a biomass boiler coupled with reverse osmosis and desiccant air conditioning. The plant was modeled in TRNSYS and simulated for 1 year. A parametric study defined the system’s setup. A thermoeconomic optimization determined the set of parameters that minimize the simple payback period. The optimal structure showed a total energy efficiency of 0.49 for the solar collectors and 0.16 for the solar panels. The coefficient of performance of the desiccant air conditioning was 0.37. Finally, a sensitivity analysis analyzed the influence of purchase electricity and natural gas costs and the electricity sell-back price on the system. The optimum simple payback was 20.68 years; however, the increase in the energy cost can reduce it by up to 85%. Full article
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23 pages, 6912 KiB  
Article
Energy-Economic Assessment of Islanded Microgrid with Wind Turbine, Photovoltaic Field, Wood Gasifier, Battery, and Hydrogen Energy Storage
by Maciej Żołądek, Alexandros Kafetzis, Rafał Figaj and Kyriakos Panopoulos
Sustainability 2022, 14(19), 12470; https://doi.org/10.3390/su141912470 - 30 Sep 2022
Cited by 6 | Viewed by 1872
Abstract
Island energy systems are becoming an important part of energy transformation due to the growing needs for the penetration of renewable energy. Among the possible systems, a combination of different energy generation technologies is a viable option for local users, as long as [...] Read more.
Island energy systems are becoming an important part of energy transformation due to the growing needs for the penetration of renewable energy. Among the possible systems, a combination of different energy generation technologies is a viable option for local users, as long as energy storage is implemented. The presented paper describes an energy-economic assessment of an island system with a photovoltaic field, small wind turbine, wood chip gasifier, battery, and hydrogen circuit with electrolyzer and fuel cell. The system is designed to satisfy the electrical energy demand of a tourist facility in two European localizations. The operation of the system is developed and dynamically simulated in the Transient System Simulation (TRNSYS) environment, taking into account realistic user demand. The results show that in Gdansk, Poland, it is possible to satisfy 99% of user demand with renewable energy sources with excess energy equal to 31%, while in Agkistro, Greece, a similar result is possible with 43% of excess energy. Despite the high initial costs, it is possible to obtain Simple Pay Back periods of 12.5 and 22.5 years for Gdansk and Agkistro, respectively. This result points out that under a high share of renewables in the energy demand of the user, the profitability of the system is highly affected by the local cost of energy vectors. The achieved results show that the system is robust in providing energy to the users and that future development may lead to an operation based fully on renewables. Full article
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15 pages, 3138 KiB  
Article
Minimizing the Utilized Area of PV Systems by Generating the Optimal Inter-Row Spacing Factor
by Ayman Al-Quraan, Mohammed Al-Mahmodi, Khaled Alzaareer, Claude El-Bayeh and Ursula Eicker
Sustainability 2022, 14(10), 6077; https://doi.org/10.3390/su14106077 - 17 May 2022
Cited by 12 | Viewed by 3269
Abstract
In mounted photovoltaic (PV) facilities, energy output losses due to inter-row shading are unavoidable. In order to limit the shadow cast by one module row on another, sufficient inter-row space must be planned. However, it is not uncommon to see PV plants with [...] Read more.
In mounted photovoltaic (PV) facilities, energy output losses due to inter-row shading are unavoidable. In order to limit the shadow cast by one module row on another, sufficient inter-row space must be planned. However, it is not uncommon to see PV plants with such close row spacing that energy losses occur owing to row-to-row shading effects. Low module prices and high ground costs lead to such configurations, so the maximum energy output per available surface area is prioritized over optimum energy production per peak power. For any applications where the plant power output needs to be calculated, an exact analysis of the influence of inter-row shading on power generation is required. In this paper, an effective methodology is proposed and discussed in detail, ultimately, to enable PV system designers to identify the optimal inter-row spacing between arrays by generating a multiplier factor. The spacing multiplier factor is mathematically formulated and is generated to be a general formula for any geographical location including flat and non-flat terrains. The developed model is implemented using two case studies with two different terrains, to provide a wider context. The first one is in the Kingdome of Saudi Arabia (KSA) provinces, giving a flat terrain case study; the inter-row spacing multiplier factor is estimated for the direct use of a systems designer. The second one is the water pump for agricultural watering using renewable energy sources, giving a non-flat terrain case study in Dhamar, Al-Hada, Yemen. In this case study, the optimal inter-row spacing factor is estimated for limited-area applications. Therefore, the effective area using the proposed formula is minimized so that the shading of PV arrays on each other is avoided, with a simple design using the spacing factor methodology. Full article
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23 pages, 4876 KiB  
Article
Thermoeconomic Analysis of Biomethane Production Plants: A Dynamic Approach
by Francesco Liberato Cappiello, Luca Cimmino, Marialuisa Napolitano and Maria Vicidomini
Sustainability 2022, 14(10), 5744; https://doi.org/10.3390/su14105744 - 10 May 2022
Cited by 10 | Viewed by 1964
Abstract
This work analyses the two most diffused technologies for biogas upgrading, namely water scrubbing and membrane separation. In order to carry out such analysis, these two technologies are coupled with photovoltaic panels and an electric energy storage system. The optimal water scrubbing renewable [...] Read more.
This work analyses the two most diffused technologies for biogas upgrading, namely water scrubbing and membrane separation. In order to carry out such analysis, these two technologies are coupled with photovoltaic panels and an electric energy storage system. The optimal water scrubbing renewable plant achieves a primary energy saving of 5.22 GWh/year and an operating cost saving of 488 k€/year, resulting in the best plant. It was compared to a reference system based on a cogenerator unit, directly supplied by biogas, producing thermal and electric energy, and delivered to the district heating network and to the electric grid. The profitability of both plants depends on the electric energy and biomethane exporting price. The proposed bigas upgrading plant achieves a payback period lower than 10 years with a biomethane selling price greater than 0.55 €/Sm3 and a primary energy saving index around 25–30% with a null share of thermal energy exported by the cogeneration plant. Full article
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21 pages, 6778 KiB  
Article
Design of Multi-Renewable Energy Storage and Management System Using RL-ICSO Based MPPT Scheme for Electric Vehicles
by Krishnan Sakthidasan Sankaran, Claude Ziad El-Bayeh and Ursula Eicker
Sustainability 2022, 14(8), 4826; https://doi.org/10.3390/su14084826 - 18 Apr 2022
Cited by 7 | Viewed by 1876
Abstract
Nowadays, traditional power systems are being developed as an emergence for the use of smart grids that cover the integration of multi-renewable energy sources with power electronics converters. Efforts were made to design power quality controllers for multi-renewable energy systems (photovoltaic (PV), Fuel [...] Read more.
Nowadays, traditional power systems are being developed as an emergence for the use of smart grids that cover the integration of multi-renewable energy sources with power electronics converters. Efforts were made to design power quality controllers for multi-renewable energy systems (photovoltaic (PV), Fuel Cell and Battery) to meet huge energy demands. Though there have been several techniques employed so far, the power quality issue is a major concern. In this paper, a multi-objective optimal energy management system for electric vehicles (EVs) is proposed using a reinforcement learning mechanism. Furthermore, the maximum power point tracking (MPPT)-based Reinforcement Learning-Iterative cuckoo search optimization algorithm (RL-ICSO) along with the Proportional Integral Derivative (PID) controller is incorporated. For this, a renewable energy source is considered as input for eliminating voltage and current harmonics. Similarly, a DC to AC inverter using a Model Predictive Control (MPC) controller-based pulse generation process was carried out to incorporate the power quality compensation of multi-renewable energy microgrid harmonics in three-phase systems. The generated energy is checked for any liabilities by adding a fault in the transmission line and thereby rectifying the fault by means of the Unified Power Quality Controller (UPQC) device. Thus, the fault-rectified power is stored in the grid, and the transmitting power can be used for EV charging purposes. Thus, the energy storage system is effective in charging and storing the needed power for EVs. The performance estimation is carried out by estimating the simulation outcome on Total Harmonic Distortion (THD) values, parameters, load current and voltage. In addition, the performance estimation is employed, and the outcomes attained are represented. The analysis depicts the effectiveness of the power and energy management ability of the proposed approach. Full article
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18 pages, 15087 KiB  
Article
A Novel Polygeneration System Based on a Solar-Assisted Desiccant Cooling System for Residential Buildings: An Energy and Environmental Analysis
by Luis Gabriel Gesteira and Javier Uche
Sustainability 2022, 14(6), 3449; https://doi.org/10.3390/su14063449 - 15 Mar 2022
Cited by 7 | Viewed by 2159
Abstract
This work aims to design and dynamically simulate a polygeneration system that integrates a solar-assisted desiccant cooling system for residential applications as an alternative to vapor compression systems. The overall plant layout supplies electricity, space heating and cooling, domestic hot water, and freshwater [...] Read more.
This work aims to design and dynamically simulate a polygeneration system that integrates a solar-assisted desiccant cooling system for residential applications as an alternative to vapor compression systems. The overall plant layout supplies electricity, space heating and cooling, domestic hot water, and freshwater for a single-family townhouse located in the city of Almería in Spain. The leading technologies used in the system are photovoltaic/thermal collectors, reverse osmosis, and desiccant air conditioning. The system model was developed and accurately simulated in the TRNSYS environment for a 1-year simulation with a 5-min time step. Design optimization was carried out to investigate the system’s best configuration. The optimal structure showed a satisfactory total annual energy efficiency in solar collectors of about 0.35 and about 0.47 for desiccant air conditioning. Coverage of electricity, space heating and cooling, domestic hot water, and freshwater was 104.1%, 87.01%, 97.98%, 96.05 %, and 100 %, respectively. Furthermore, significant ratios for primary energy saving, 98.62%, and CO2 saving, 97.17%, were achieved. The users’ thermal comfort level was satisfactory over the entire year. Finally, a comparison with an alternative coastal site was performed to extend the polygeneration system’s applicability. Full article
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