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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 (31 December 2022) | Viewed by 35573

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Special Issue Editor

Dr. Miguel Jiménez Carrizosa

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Guest Editor

Energy & Fuel department, Universidad Politécnica de Madrid, 28003 Madrid, Spain
Interests: smart grid; control of power converters; hvdc systems; power flow; vehicule to grid integration

Special Issue Information

Dear Colleagues,

Due to the growing global energy demand and the increasing sensitivity to environmental concerns, the energy system, especially at the distribution level, is changing profoundly towards a new paradigm of electrical structures called smart grids.

Effectively, we are passing from the classic electrical structure, where production plants were far away from consumers, to new solutions with decentralized and local production, high renewable energy penetration, and distributed energy storage elements and power converters as essential components, where both AC and DC technology solutions are involved.

It is in this context where smart energy control will play a fundamental role in the development and implementation of these new microgrids. This Special Issue, entitled “Smart Energy Management for Smart Grids” is mainly proposed to cover original research and studies related to the above-mentioned topics, including but not limited to distributed energy systems, the control of microgrids with renewable energy and storage elements, electric vehicle integration and vehicle-to-grid (V2G) operation, weather and load forecasting, and providing ancillary services to the main grid (voltage and frequency regulation, active and reactive power support, grid forming, etc.)

Papers selected for this Special Issue will be subject to a rigorous peer-review procedure with the aim of the rapid and wide dissemination of research results, developments, and applications.

Dr. Miguel Jiménez Carrizosa
Guest Editor

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Keywords

distributed energy systems
control of smart grids
ancillary services to main grid
grid forming
load forecasting and scheduling
electric vehicle integration
weather forecasting for renewable
production
renewable energies

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Published Papers (11 papers)

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Research

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23 pages, 4874 KiB

Open AccessArticle

Integration of Local and Central Control Empowers Cooperation among Prosumers and Distributors towards Safe, Efficient, and Cost-Effective Operation of Microgrids

by Paolo Tenti and Tommaso Caldognetto

Energies 2023, 16(5), 2320; https://doi.org/10.3390/en16052320 - 28 Feb 2023

Cited by 11 | Viewed by 1658

Abstract

The advent of energy communities will revolutionize the energy market. However, exploiting their full potential requires innovations in the structure and management of low-voltage grids. End users shall be aggregated within microgrids, where their physical interaction is possible and coordinated operation of power sources and energy storage systems can be achieved. Moreover, meshed network topologies will enable multiple paths for the power flow. The combination of smart control and meshed networks can dramatically improve microgrid performance in terms of power quality, efficiency, and resilience to transients and faults. Ubiquitous control of the power flow becomes possible, as well as active fault clearing and isolation of subgrids without tripping circuit breakers. This paper proposes a control approach that pursues such goals without requiring modification of control and communication hardware implemented in commercial inverters. Instead, a revision of control firmware, integrated with local measurements, allows retrofitting existing plants to improve microgrid operation. Further improvements may derive from the installation of community power sources and energy storage systems, which can extend microgrid operation to pursue demand response and islanding. The potential of the proposed control methods is demonstrated by simulation considering a standard microgrid under different operating conditions. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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11 pages, 3821 KiB

Open AccessArticle

Power Quality Transient Detection and Characterization Using Deep Learning Techniques

by Nuno M. Rodrigues, Fernando M. Janeiro and Pedro M. Ramos

Energies 2023, 16(4), 1915; https://doi.org/10.3390/en16041915 - 15 Feb 2023

Cited by 6 | Viewed by 1839

Abstract

Power quality issues can affect the performance of devices powered by the grid and can, in severe cases, permanently damage connected devices. Events that affect power quality include sags, swells, waveform distortions and transients. Transients are one of the most common power quality disturbances and are caused by lightning strikes or switching activities among power-grid-connected systems and devices. Transients can reach very high magnitudes, and their duration spans from nanoseconds to milliseconds. This study proposed a deep-learning-based technique that was supported by convolutional neural networks and a bidirectional long short-term memory approach in order to detect and characterize power-quality transients. The method was validated (i.e., benchmarked) using an alternative algorithm that had been previously validated according to a digital high-pass filter and a morphological closing operation. The training and performance assessments were carried out using actual power-grid-measured data and events. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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24 pages, 2023 KiB

Open AccessArticle

Deployment of IoT-Based Smart Demand-Side Management System with an Enhanced Degree of User Comfort at an Educational Institution

by S. Charles Raja, A. C. Vishnu Dharssini, J. Jeslin Drusila Nesmalar and T. Karthick

Energies 2023, 16(3), 1403; https://doi.org/10.3390/en16031403 - 31 Jan 2023

Cited by 5 | Viewed by 2004

Abstract

Nowadays, the Internet of Things (IoT) has a wide impact on many potential applications. The impact of IoT on performing demand-side management (DSM) in an Indian educational institution has not been researched in depth before. In this research work, an IoT-enabled SDSMS (Smart DSM System) has been deployed with the main objective of minimizing electricity tariff and also to tweak the quality of user comfort. It can be feasible by prioritizing available renewable PV solar energy during peak hours in an Indian educational institution. DSM has been performed using day-ahead load shifting and rescheduling the different classes of institutional loads by applying hybrid BPSOGSA (Binary Particle Swarm Optimization and Gravitational Search Algorithm). The BPSOGSA performance on DSM has been evaluated based on electricity tariff, peak demand range, and PAR and compared with the outcomes of both binary conventional algorithms BPSO and BGSA, respectively. The proposed method enhances the degree of user comfort (DUC) by tripping the operation of non-critical institutional loads. Simulation results obtained using MATLAB corroborate that BPSOGSA outperforms both BPSO and BGSA under both DSM scenarios. Before DSM, Peak demand, PAR, and Electricity tariffs were found to be 1855.47 kW, 4.1286, and $2030.67 while after DSM, they reduced to 1502.24 kW, 3.263, and $1314.40 respectively. This indicates a 35.273% reduction in electricity tariff, a 19.037% scale down in peak demand, and a 20.97% reduction in PAR. Finally, the real-time IoT-based SDSMS hardware is implemented at the Renewable energy laboratory for real monitoring of energy consumption via the Blynk application. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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24 pages, 3028 KiB

Open AccessArticle

An Elastic Energy Management Algorithm in a Hierarchical Control System with Distributed Control Devices

by Piotr Powroźnik, Paweł Szcześniak, Krzysztof Turchan, Miłosz Krysik, Igor Koropiecki and Krzysztof Piotrowski

Energies 2022, 15(13), 4750; https://doi.org/10.3390/en15134750 - 28 Jun 2022

Cited by 9 | Viewed by 1644

Abstract

In modern Electric Power Systems, emphasis is placed on the increasing share of electricity from renewable energy sources (PV, wind, hydro, etc.), at the expense of energy generated with the use of fossil fuels. This will lead to changes in energy supply. When there is excessive generation from RESs, there will be too much energy in the system, otherwise, there will be a shortage of energy. Therefore, smart devices should be introduced into the system, the operation of which can be initiated by the conditions of the power grid. This will allow the load profiles of the power grid to be changed and the electricity supply to be used more rationally. The article proposes an elastic energy management algorithm (EEM) in a hierarchical control system with distributed control devices for controlling domestic smart appliances (SA). In the simulation part, scenarios of the algorithm’s operation were carried out for 1000 households with the use of the distribution of activities of individual SAs. In experimental studies, simplified results for three SA types and 100 devices for each type were presented. The obtained results confirm that, thanks to the use of SAs and the appropriate algorithm for their control, it is possible to change the load profile of the power grid. The efficacious operation of SAs will be possible thanks to the change of habits of electricity users, which is briefly described in the article. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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20 pages, 494 KiB

Open AccessArticle

Synthetic Theft Attacks and Long Short Term Memory-Based Preprocessing for Electricity Theft Detection Using Gated Recurrent Unit

by Pamir, Nadeem Javaid, Saher Javaid, Muhammad Asif, Muhammad Umar Javed, Adamu Sani Yahaya and Sheraz Aslam

Energies 2022, 15(8), 2778; https://doi.org/10.3390/en15082778 - 10 Apr 2022

Cited by 22 | Viewed by 3421

Abstract

Electricity theft is one of the challenging problems in smart grids. The power utilities around the globe face huge economic loss due to ET. The traditional electricity theft detection (ETD) models confront several challenges, such as highly imbalance distribution of electricity consumption data, curse of dimensionality and inevitable effects of non-malicious factors. To cope with the aforementioned concerns, this paper presents a novel ETD strategy for smart grids based on theft attacks, long short-term memory (LSTM) and gated recurrent unit (GRU) called TLGRU. It includes three subunits: (1) synthetic theft attacks based data balancing, (2) LSTM based feature extraction, and (3) GRU based theft classification. GRU is used for drift identification. It stores and extracts the long-term dependency in the power consumption data. It is beneficial for drift identification. In this way, a minimum false positive rate (FPR) is obtained. Moreover, dropout regularization and Adam optimizer are added in GRU for tackling overfitting and trapping model in the local minima, respectively. The proposed TLGRU model uses the realistic EC profiles of the Chinese power utility state grid corporation of China for analysis and to solve the ETD problem. From the simulation results, it is exhibited that 1% FPR, 97.96% precision, 91.56% accuracy, and 91.68% area under curve for ETD are obtained by the proposed model. The proposed model outperforms the existing models in terms of ETD. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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23 pages, 6154 KiB

Open AccessArticle

Participation of Aggregated DERs to the Ancillary Services Market: A Monte Carlo Simulation-Based Heuristic Greedy-Indexing Model

by Davide Falabretti, Francesco Gulotta and Lorenzo Spinelli

Energies 2022, 15(3), 1037; https://doi.org/10.3390/en15031037 - 29 Jan 2022

Cited by 7 | Viewed by 2567

Abstract

In an effort to improve the stability and secure operation of the grid, regulatory bodies are opening Ancillary Services Markets participation to Distributed Energy Resources (DERs), energy storage systems, and demand response. Within this framework, this study proposes a model that simulates the coordinated operation of an aggregate of power plants, including non-dispatchable DERs and, as regulating units, Combined Heat and Power (CHP) generation and electrochemical energy storage systems. A Monte Carlo procedure is adopted to realistically create a population of aggregation scenarios. The real-time operation of the DER portfolio is managed through a Heuristic Greedy-Indexing logic, which allows the Aggregator to select the optimal control action to implement according to the technical and economic quantities characterizing the market and the grid. The techno-economic performance of the proposed algorithm is evaluated by simulating its interaction with the electricity markets. Finally, a sensitivity analysis is performed to analyze the profitability in different scenarios. The novel mathematical model proposed showed to be effective in managing a complex problem like the one at hand with an acceptable computational effort. The numerical results obtained confirmed that the aggregated participation in the market could provide interesting economic returns, especially if a CHP unit is involved as regulating unit, while the feasibility of the batteries adoption is still limited by the actual cost of the technology. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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18 pages, 3452 KiB

Open AccessArticle

Optimal Configuration and Sizing of Seaport Microgrids including Renewable Energy and Cold Ironing—The Port of Aalborg Case Study

by Nur Najihah Abu Bakar, Josep M. Guerrero, Juan C. Vasquez, Najmeh Bazmohammadi, Muzaidi Othman, Brian Dalby Rasmussen and Yusuf A. Al-Turki

Energies 2022, 15(2), 431; https://doi.org/10.3390/en15020431 - 7 Jan 2022

Cited by 26 | Viewed by 4488

Abstract

Microgrids are among the promising green transition technologies that will provide enormous benefits to the seaports to manage major concerns over energy crises, environmental challenges, and economic issues. However, creating a good design for the seaport microgrid is a challenging task, considering different objectives, constraints, and uncertainties involved. To ensure the optimal operation of the system, determining the right microgrid configuration and component size at minimum cost is a vital decision at the design stage. This paper aims to design a hybrid system for a seaport microgrid with optimally sized components. The selected case study is the Port of Aalborg, Denmark. The proposed grid-connected structure consists of renewable energy sources (photovoltaic system and wind turbines), an energy storage system, and cold ironing facilities. The seaport architecture is then optimized by utilizing HOMER to meet the maximum load demand by considering important parameters such as solar global horizontal irradiance, temperature, and wind resources. Finally, the best configuration is analyzed in terms of economic feasibility, energy reliability, and environmental impacts. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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25 pages, 4940 KiB

Open AccessArticle

Developing Novel Technologies and Services for Intelligent Low Voltage Electricity Grids: Cost–Benefit Analysis and Policy Implications

by Alemu Moges Belay, Sanket Puranik, Ramon Gallart-Fernández, Heidi Tuiskula, Joaquim Melendez, Ilias Lamprinos, Francisco Díaz-González and Miha Smolnikar

Energies 2022, 15(1), 94; https://doi.org/10.3390/en15010094 - 23 Dec 2021

Cited by 3 | Viewed by 3817

Abstract

The paper presents a set of prototype smart grid technologies and services and validates the economic viability of the proposed solution using cost–benefit analysis (CBA). The study considered the EU-funded project called RESOLVD and implemented the technologies and services in a real-life pilot. The paper focuses on the analysis of technological solutions which enhance the operational efficiency and the hosting capacity of low-voltage electricity distribution grids. The solutions provided better integration of a hybrid battery storage system, with the grid interfacing power electronics, smart gateways for the interconnection of assets at the grid edge, and sensors enhancing infrastructure observability and control. The result from the CBA indicates the economic viability of the project, high scalability, and replicability. The economic benefits were realized with the breakeven value of eight secondary substations (SS) and 16 feeders. The scenario test on the DSO’s willingness to pay for the software as a service (SaaS) revealed that the payback period can further be reduced by almost half with a higher internal rate of return (IRR) and net present value (NPV). Both the CBA and scenario tests showed RESOLVD solution can become more economically viable when deployed in largescale. Moreover, the CBA results provide evidence to the energy policy by allowing DSOs to consider both CAPEX and OPEX for better investment decisions. Further, the paper proposes an alternative business approach that shifts from grid reinforcement to service provision. The paper also discusses the research implications on energy policy and business. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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26 pages, 26225 KiB

Open AccessArticle

Blockchain-Enabled Energy Demand Side Management Cap and Trade Model

by Alain Aoun, Hussein Ibrahim, Mazen Ghandour and Adrian Ilinca

Energies 2021, 14(24), 8600; https://doi.org/10.3390/en14248600 - 20 Dec 2021

Cited by 10 | Viewed by 3722

Abstract

Global economic growth, demographic explosion, digitization, increased mobility, and greater demand for heating and cooling due to climate change in different world areas are the main drivers for the surge in energy demand. The increase in energy demand is the basis of economic challenges for power companies alongside several socio-economic problems in communities, such as energy poverty, defined as the insufficient coverage of energy needs, especially in the residential sector. Two main strategies are considered to meet this increased demand. The first strategy focuses on new sustainable and eco-friendly modes of power generation, such as renewable energy resources and distributed energy resources. The second strategy is demand-side oriented rather than the supply side. Demand-side management, demand response (DR), and energy efficiency (EE) programs fall under this category. On the other hand, the decentralization and digitization of the energy sector convoyed by the emersion of new technologies such as blockchain, Internet of Things (IoT), and Artificial Intelligence (AI), opened the door to new solutions for the energy demand dilemma. Among these technologies, blockchain has proved itself as a decentralized trading platform between untrusted peers without the involvement of a trusted third party. This newly introduced Peer-to-Peer (P2P) trading model can be used to create a new demand load control model. In this article, the concept of an energy cap and trade demand-side management (DSM) model is introduced and simulated. The introduced DSM model is based on the concept of capping consumers’ monthly energy consumption and rewarding consumers who do not exceed this cap with energy tradeable credits that can be traded using blockchain-based Peer-to-Peer (P2P) energy trading. A model based on 200 households is used to simulate the proposed DSM model and prove that this model can be beneficial to both energy companies and consumers. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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Review

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22 pages, 3676 KiB

Open AccessReview

Microgrid Energy Management and Methods for Managing Forecast Uncertainties

by Shanmugarajah Vinothine, Lidula N. Widanagama Arachchige, Athula D. Rajapakse and Roshani Kaluthanthrige

Energies 2022, 15(22), 8525; https://doi.org/10.3390/en15228525 - 15 Nov 2022

Cited by 14 | Viewed by 2761

Abstract

The rising demand for electricity, economic benefits, and environmental pressures related to the use of fossil fuels are driving electricity generation mostly from renewable energy sources. One of the main challenges in renewable energy generation is uncertainty involved in forecasting because of the intermittent nature of renewable sources. The demand also varies according to the time of day, the season, the location, the climate, and the availability of resources. Microgrids offer a potential solution for the integration of small-scale renewable energy sources and loads along with energy storage systems and other non-renewable sources. However, intermittent generation and varying demand need to be matched to provide stable power to consumers. Therefore, it is crucial to design an energy management system to effectively manage the energy sources and supply loads for reliable and efficient operation. This paper reviews different techniques proposed in the literature to achieve the objectives of a microgrid energy management system. The benefits of existing energy management systems and their challenges are also discussed. The challenges associated with uncertainties and methods to overcome them are critically reviewed. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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31 pages, 46954 KiB

Open AccessReview

A Review of the Conceptualization and Operational Management of Seaport Microgrids on the Shore and Seaside

by Nur Najihah Abu Bakar, Josep M. Guerrero, Juan C. Vasquez, Najmeh Bazmohammadi, Yun Yu, Abdullah Abusorrah and Yusuf A. Al-Turki

Energies 2021, 14(23), 7941; https://doi.org/10.3390/en14237941 - 26 Nov 2021

Cited by 25 | Viewed by 5652

Abstract

Seaports are well known as the medium that has evolved into the central link between sea and land for complex marine activities. The growth in maritime logistics particularly necessitates a large volume of energy supply in order to maintain the operation of sea trade, resulting in an imbalance between generation and demand sides. Future projections for three major concerns show an increase in load demand, cost of operation, and environmental issues. In order to overcome these problems, integrating microgrids as an innovative technology in the seaport power system appears to be a vital strategy. It is believed that microgrids enhance seaport operation by providing sustainable, environmentally friendly, and cost-effective energy. Although microgrids are well established and widely used in a variety of operations on land, their incorporation into the seaport is still limited. The involvement of a variety of heavy loads such as all-electric ships, cranes, cold ironing, and buildings infrastructure renders it a complicated arrangement task in several aspects, which necessitates further research and leaves space for improvement. In this paper, an overview of the seaport microgrids in terms of their concepts and operation management is presented. It provides the perspectives for integrating the microgrid concept into a seaport from both shore side and seaside as a smart initiative for the green port’s vision. Future research directions are discussed towards the development of a more efficient marine power system. Full article

(This article belongs to the Special Issue Smart Energy Management for Smart Grid)

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