Smart Energy Systems, 2nd Edition

Topic Information

Dear Colleagues,

There are some definitions for what a Smart Energy System is. Terms such as: cost-effective, sustainable, secure, renewable energy production, storage systems, demand-side response, electrical vehicles, energy efficiency, active users, and intelligent networking are often associated with the Smart Energy System concept. It is a broader term than Smart Grid, in the sense that it includes more sectors (electricity, heating, cooling, industry, buildings, transportation, and water) rather than focusing exclusively on the electricity sector. Smart Energy Systems are closely related to the ongoing energy transition toward a 100% renewable energy system.

We are pleased to invite the research community to submit review or regular research papers on, but not limited to, the following relevant topics related to Smart Energy Systems:

• Hydrogen systems;
• Storage technologies and systems;
• Demand side response;
• Electrical Vehicles;
• Planning, operation, control, and management;
• Modeling, simulation, and data management;
• Ancillary services;
• Power electronic converters and drives;
• Smart thermal grids;
• Smart gas grids;
• Smart electricity grids;
• Energy efficient systems;
• Virtual power plants;
• Renewable energy production and integration;
• Micro-Grids;
• Power-to-H2O (desalination and water purification);
• Hybrid AC/DC grids;
• Off-grid hybrid renewable systems;
• Artificial intelligence and optimization;
• Demand, Production, and weather forecast;
• Smart homes, cities, and communities;
• Efficient buildings and Net Zero Energy Buildings;
• Power quality;
• Protection systems and reliability;
• Sensors, communications, and intelligent networking;
• Smart metering;
• Virtual power lines;
• Security and privacy of data exchange;
• Life cycle assessment;
• Public policies;
• Local markets;
• Flexibility markets;
• TSO-DSO coordination;
• Education.

Prof.Dr. Hugo Morais
Prof.Dr. Rui Castro
Dr. Cindy Guzman
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.7	4.5	2011	16.9 Days	CHF 2400	Submit
Batteries batteries	4.0	5.4	2015	17.7 Days	CHF 2700	Submit
Buildings buildings	3.8	3.1	2011	14.6 Days	CHF 2600	Submit
Data data	2.6	4.6	2016	22 Days	CHF 1600	Submit
Electricity electricity	-	-	2020	20.3 Days	CHF 1000	Submit
Electronics electronics	2.9	4.7	2012	15.6 Days	CHF 2400	Submit
Energies energies	3.2	5.5	2008	16.1 Days	CHF 2600	Submit
Smart Cities smartcities	6.4	8.5	2018	20.2 Days	CHF 2000	Submit

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Published Papers (5 papers)

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All Applied Sciences Batteries Buildings Data Electricity Electronics Energies Smart Cities

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24 pages, 1376 KiB  

Open AccessArticle

Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks

by Jerzy Andruszkiewicz, Józef Lorenc and Agnieszka Weychan

Energies 2024, 17(1), 150; https://doi.org/10.3390/en17010150 - 27 Dec 2023

Viewed by 724

Abstract

The objective of the presented paper is to verify economically justified levels of reactive energy compensation in the distribution network in the new market conditions, including the extensive use of smart metering systems, new types of load, or distributed generation. The proposed methodology [...] Read more.

The objective of the presented paper is to verify economically justified levels of reactive energy compensation in the distribution network in the new market conditions, including the extensive use of smart metering systems, new types of load, or distributed generation. The proposed methodology is based on the minimization of annual costs of losses caused by the flow of reactive energy to the supplied loads through the equivalent resistance of the distribution system determined on the basis of statistical energy losses in this network. The costs of losses are compared to the costs of using compensating devices expressed by the levelized costs of reactive energy generation. The results are the relations describing the optimal annual average value of the tgφ factor to be maintained by customers to optimize the cost of loss of the distribution network caused by reactive energy flows. The dependence of the optimal tgφ value on the analyzed load and network parameters is also discussed. The resulting optimal tgφ levels should be considered in the tariffication process of services offered by distribution system operators to improve capacity and limit the costs of power network operation due to reactive energy transmission. Full article

(This article belongs to the Topic Smart Energy Systems, 2nd Edition)

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37 pages, 9772 KiB  

Open AccessArticle

Smoothing Intermittent Output Power in Grid-Connected Doubly Fed Induction Generator Wind Turbines with Li-Ion Batteries

by Henok Ayele Behabtu, Majid Vafaeipour, Abraham Alem Kebede, Maitane Berecibar, Joeri Van Mierlo, Kinde Anlay Fante, Maarten Messagie and Thierry Coosemans

Energies 2023, 16(22), 7637; https://doi.org/10.3390/en16227637 - 17 Nov 2023

Cited by 3 | Viewed by 1064

Abstract

Wind energy is an increasingly important renewable resource in today’s global energy landscape. However, it faces challenges due to the unpredictable nature of wind speeds, resulting in intermittent power generation. This intermittency can disrupt power grid stability when integrating doubly fed induction generators [...] Read more.

Wind energy is an increasingly important renewable resource in today’s global energy landscape. However, it faces challenges due to the unpredictable nature of wind speeds, resulting in intermittent power generation. This intermittency can disrupt power grid stability when integrating doubly fed induction generators (DFIGs). To address this challenge, we propose integrating a Li-ion battery energy storage system (BESS) with the direct current (DC) link of grid-connected DFIGs to mitigate power fluctuations caused by variable wind speed conditions. Our approach entails meticulous battery modeling, sizing, and control methods, all tailored to match the required output power of DFIG wind turbines. To demonstrate how well our Li-ion battery solution works, we have developed a MATLAB/Simulink R2022a version model. This model enables us to compare situations with and without the Li-ion battery in various operating conditions, including steady-state and dynamic transient scenarios. We also designed a buck–boost bidirectional DC-DC converter controlled by a proportional integral controller for battery charging and discharging. The battery actively monitors the DC-link voltage of the DFIG wind turbine and dynamically adjusts its stored energy in response to the voltage level. Thus, DFIG wind turbines consistently generate 1.5 MW of active power, operating with a highly efficient power factor of 1.0, indicating there is no reactive power produced. Our simulation results confirm that Li-ion batteries effectively mitigate power fluctuations in grid-connected DFIG wind turbines. As a result, Li-ion batteries enhance grid power stability and quality by absorbing or releasing power to compensate for variations in wind energy production. Full article

(This article belongs to the Topic Smart Energy Systems, 2nd Edition)

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14 pages, 1217 KiB  

Open AccessArticle

Distributed Platform for Offline and Online EV Charging Simulation

by Joaquim Perez, Filipe Quintal and Lucas Pereira

Electronics 2023, 12(21), 4401; https://doi.org/10.3390/electronics12214401 - 25 Oct 2023

Viewed by 712

Abstract

Efforts to enhance electric vehicle (EV) charging processes have spurred the emergence of smart charging algorithms. However, these studies are intricate and costly, necessitating preliminary simulations to assess EV integration into power grids. Existing solutions to this issue tend to be limited to [...] Read more.

Efforts to enhance electric vehicle (EV) charging processes have spurred the emergence of smart charging algorithms. However, these studies are intricate and costly, necessitating preliminary simulations to assess EV integration into power grids. Existing solutions to this issue tend to be limited to academia and proprietary systems. To address this, we propose a user-friendly and intuitive simulation tool employing a decoupled and flexible architecture. This architecture, achieved through open design and containerized microservices, streamlines maintenance, extension, and scalability. We substantiated the validity of our solution by simulating the charging infrastructure from an H2020 Research Project. Furthermore, we integrated our solution with an external system that executes smart charging algorithms. The proposed system yielded the desired results, enabling the project team to evaluate both the integration and algorithms, even amidst the COVID-19 lockdown. Full article

(This article belongs to the Topic Smart Energy Systems, 2nd Edition)

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21 pages, 5422 KiB  

Open AccessArticle

System Dynamics Model of Decentralized Household Electricity Storage Implementation: Case Study of Latvia

by Armands Gravelsins, Erlanda Atvare, Edgars Kudurs, Anna Kubule and Dagnija Blumberga

Smart Cities 2023, 6(5), 2553-2573; https://doi.org/10.3390/smartcities6050115 - 25 Sep 2023

Cited by 2 | Viewed by 949

Abstract

Increasing renewable energy share in total energy production is a direction that leads toward the European Union’s aims of carbon neutrality by 2050, as well as increasing energy self-sufficiency and independence. Some of the main challenges to increasing renewable energy share while providing [...] Read more.

Increasing renewable energy share in total energy production is a direction that leads toward the European Union’s aims of carbon neutrality by 2050, as well as increasing energy self-sufficiency and independence. Some of the main challenges to increasing renewable energy share while providing an efficient and secure energy supply are related to the optimization and profitability of de-centralized energy production systems. Integration of energy storage systems in addition to decentralized renewable energy production, for example, by solar panels, leads to more effective electricity supply and smart energy solutions. The modeling of such a complex dynamic system can be performed using the system dynamics method. The main aim of this research is to build and validate the basic structure of the system dynamics model for PV and battery diffusion in the household sector. A system dynamics model predicting the implementation of battery storage in private households was created for the case study of Latvia. Modeling results reveal that under the right conditions for electricity price and investment costs and with the right policy interventions, battery storage technologies combined with PV panels have a high potential for utilization in the household sector. Model results show that in a baseline scenario with no additional policies, up to 21,422 households or 10.8% of Latvian households could have combined PV and battery systems installed in 2050. Moderate subsidy policy can help to increase this number up to 25,118. Full article

(This article belongs to the Topic Smart Energy Systems, 2nd Edition)

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13 pages, 1775 KiB  

Open AccessData Descriptor

Exploring Spatial Patterns in Sensor Data for Humidity, Temperature, and RSSI Measurements

by Juan Botero-Valencia, Adrian Martinez-Perez, Ruber Hernández-García and Luis Castano-Londono

Data 2023, 8(5), 82; https://doi.org/10.3390/data8050082 - 29 Apr 2023

Viewed by 1590

Abstract

The Internet of Things (IoT) is one of the fastest-growing research areas in recent years and is strongly linked to the development of smart cities, smart homes, and factories. IoT can be defined as connecting devices, sensors, and physical objects that can collect [...] Read more.

The Internet of Things (IoT) is one of the fastest-growing research areas in recent years and is strongly linked to the development of smart cities, smart homes, and factories. IoT can be defined as connecting devices, sensors, and physical objects that can collect and transmit data across a network, enabling increased automation and better decision-making. In several IoT applications, humidity and temperature are some of the most used variables for adjusting system configurations and understanding their performance because they are related to various physical processes, human comfort, manufacturing processes, and 3D printing, among other things. In addition, one of the biggest problems associated with IoT is the excessive production of data, so it is necessary to develop methodologies to optimize the process of collecting information. This work presents a new dataset comprising almost 55 million values of temperature, relative humidity, and RSSI (Received Signal Strength Indicator) collected in two indoor spaces for longer than 3915 h at 10 s intervals. For each experiment, we captured the information from 13 previously calibrated sensors suspended from the ceiling at the same height and with a known relative position. The proposed dataset aims to contribute a benchmark for evaluating indoor temperature and humidity-controlled systems. The collected data allow the validation and improvement of the acquisition process for IoT applications. Full article

(This article belongs to the Topic Smart Energy Systems, 2nd Edition)

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