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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 (20 March 2022) | Viewed by 26652

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Special Issue Editors

Prof. Dr. Hannu Laaksonen

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Guest Editor

School of Technology and Innovations, University of Vaasa, PB 700, 65101 Vaasa, Finland
Interests: smart grids; flexible energy systems; microgrids; protection and control of electricity; market concepts for smart grids; peer-to-peer energy trading
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Dr. Omid Palizban

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Co-Guest Editor

School of Technology and Innovations, University of Vaasa, 65200 Vaasa, Finland
Interests: smart grids; microgrids; distributed energy storage systems; hierarchical and cooperative control; energy management

Special Issue Information

Dear Colleagues,

Power systems are changing due to global drivers, and in many countries, traditional centralized power plants have been or will be shut down. Simultaneously distributed, renewable generation will be integrated in large scale and at all voltage levels. Large-scale integration of variable renewable generation increases the variations and peak situations in which electricity network capacity or voltage limits may become an issue. Therefore, in the future, the active and intelligent utilization of all the different flexible energy resource potentials at all voltage levels, for local and system-wide flexibility services and increased resiliency, will be required in order to maintain total system costs at a reasonable level. In addition, energy storage (e.g., batteries, power-to-X) and integration of different energy networks/vectors (electricity, heat, gas, transport, hydrogen) and their simultaneous optimization from the point of view of both local and whole society will be needed. Future smart and flexible energy systems will also require totally new protection and control solutions, as well as operation and planning principles based on optimal and coordinated utilization of flexible energy resources at different voltage levels. Enabling of flexible cost- and energy-efficient solutions, like hybrid AC–DC systems, advanced forecasts, and cyber-secure ICT technologies, will have a major role in new resilient smart grid technologies and architectures. However, the intelligent and optimized operation and planning of future sustainable power and energy systems is also strongly dependent on their business models, market structures, regulation, and tax and tariff structures, as well as customer knowledge. In order to achieve future-proof, compatible, and optimized solutions for the smart and flexible energy systems, the simultaneous development of multiple different aspects and the whole system view is needed.

Prof. Hannu Laaksonen
Dr. Omid Palizban
Guest Editor

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Keywords

resilient smart grid architectures with flexible energy resources
protection and control solutions for future power systems
grid-interactive microgrids
control of energy storage
optimized operation of smart energy systems
hybrid AC–DC systems in smart grids
cyber-secure ICT technologies for smart energy systems
integration of different energy networks (electricity, heat, gas, transport)
management of flexible energy resources in local energy communities
flexibility forecasts in future smart grids
energy market redesign (local and system-wide energy and flexibility markets)
regulation and legislation enabling use of different flexibility services.

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Published Papers (9 papers)

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Research

14 pages, 6809 KiB

Open AccessArticle

Cost and Cybersecurity Challenges in the Commissioning of Microgrids in Critical Infrastructure: COGE Case Study

by Rodrigo Antonio Sbardeloto Kraemer, Douglas Pereira Dias, Alisson Carlos da Silva, Marcos Aurelio Izumida Martins and Mathias Arno Ludwig

Energies 2022, 15(8), 2860; https://doi.org/10.3390/en15082860 - 14 Apr 2022

Cited by 4 | Viewed by 2530

Abstract

The application of microgrids in critical infrastructures has grown considerably due to the power supply reliability and resilience, and the island operation possibility of providing independence from the main grid. However, the necessity of intense information exchange between the devices that compose the microgrid to their proper operation, and the communication infrastructure required to realize that, makes the system vulnerable to cybersecurity threats. In this context, the case study presented in this paper raises two important subjects of discussion in the Brazilian electrical sector context, which are microgrids and cybersecurity in critical infrastructures of the electrical sector. Therefore, this paper presents the practical challenges related to these two subjects by reporting the development, implementation, and commissioning of a new microgrid controller, and the solutions found to accelerate the development by reducing costs, mitigating risks, and optimizing the commissioning time. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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21 pages, 2582 KiB

Open AccessArticle

Error Compensation Enhanced Day-Ahead Electricity Price Forecasting

by Dimitrios Kontogiannis, Dimitrios Bargiotas, Aspassia Daskalopulu, Athanasios Ioannis Arvanitidis and Lefteri H. Tsoukalas

Energies 2022, 15(4), 1466; https://doi.org/10.3390/en15041466 - 17 Feb 2022

Cited by 13 | Viewed by 2496

Abstract

The evolution of electricity markets has led to increasingly complex energy trading dynamics and the integration of renewable energy sources as well as the influence of several external market factors contributed towards price volatility. Therefore, day-ahead electricity price forecasting models, typically using some kind of neural network, play a crucial role in the optimal behavior of market agents. The most prominent models and benchmarks rely on improving the accuracy of predictions and the time for convergence by some sort of a priori processing of the dataset that is used for the training of the neural network, such as hyperparameter tuning and feature selection techniques. What has been overlooked so far is the possible benefit of a posteriori processing, which would consider the effects of parameters that could refine the predictions once they have been made. Such a parameter is the estimation of the residual training error. In this study, we investigate the effect of residual training error estimation for the day-ahead price forecasting task and propose an error compensation deep neural network model (ERC–DNN) that focuses on the minimization of prediction error, while reinforcing error stability through the integration of an autoregression module. The experiments on the Nord Pool power market indicated that this approach yields improved error metrics when compared to the baseline deep learning structure in different training scenarios, and the refined predictions for each hourly sequence shared a more stable error profile. The proposed method contributes towards the development of more flexible hybrid neural network models and the potential integration of the error estimation module in future benchmarks, given a small and interpretable set of hyperparameters. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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23 pages, 2016 KiB

Open AccessArticle

Ushering in a New Dawn: Demand-Side Local Flexibility Platform Governance and Design in the Finnish Energy Markets

by Nayeem Rahman, Rodrigo Rabetino, Arto Rajala and Jukka Partanen

Energies 2021, 14(15), 4405; https://doi.org/10.3390/en14154405 - 21 Jul 2021

Cited by 4 | Viewed by 2526

Abstract

Energy ecosystems are under a significant transition. Local flexibility marketplaces (LFM) and platforms are argued to have significant potential in contributing to such a transition. The purpose of this study was to answer the following research question: how do market conditions and stakeholders shape emerging LFM platform governance choices? We approached this objective with an exploratory single-case study by conducting ten semi-structured interviews with key stakeholders in the Finnish energy ecosystem. The results of the content and pattern analyses revealed the key challenges to LFM implementation such as the current regulatory treatment of flexibility, high costs of gadget installations, and ensuring sufficient liquidity in the market. In addition, we also demonstrated that despite such barriers, the Finnish ecosystem is largely pragmatic about LFMs’ in its midst. All in all, we contributed to the non-technological streams of LFM literature by developing an exhaustive framework with four distinctive dimensions (i.e., ecosystem readiness, value-creation logic, platform architecture and governance, platform competitiveness) for LFM development, which helps academics, practitioners, and policy-makers to understand how novel platforms emerge and develop. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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18 pages, 7259 KiB

Open AccessArticle

An Islanding Detection Technique for Inverter-Based Distributed Generation in Microgrids

by Mazaher Karimi, Mohammad Farshad, Qiteng Hong, Hannu Laaksonen and Kimmo Kauhaniemi

Energies 2021, 14(1), 130; https://doi.org/10.3390/en14010130 - 29 Dec 2020

Cited by 33 | Viewed by 3087

Abstract

This article proposes a new passive islanding detection technique for inverter-based distributed generation (DG) in microgrids based on local synchrophasor measurements. The proposed method utilizes the voltage and current phasors measured at the DG connection point (point of connection, PoC). In this paper, the rate of change of voltages and the ratio of the voltage and current magnitudes (VoI index) at the PoC are monitored using micro-phasor measurement units. The developed local measurements based decentralized islanding detection technique is based on the VoI index in order to detect any kind of utility grid frequency fluctuations or oscillations and distinguishing them from islanding condition. The simulation studies confirm that the proposed scheme is accurate, robust, fast, and simple to implement for inverter-based DGs. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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32 pages, 3876 KiB

Open AccessArticle

Impact Analysis of Large-Scale Wind Farms Integration in Weak Transmission Grid from Technical Perspectives

by Shah Rukh Abbas, Syed Ali Abbas Kazmi, Muhammad Naqvi, Adeel Javed, Salman Raza Naqvi, Kafait Ullah, Tauseef-ur-Rehman Khan and Dong Ryeol Shin

Energies 2020, 13(20), 5513; https://doi.org/10.3390/en13205513 - 21 Oct 2020

Cited by 15 | Viewed by 3407

Abstract

The integration of commercial onshore large-scale wind farms into a national grid comes with several technical issues that predominately ensure power quality in accordance with respective grid codes. The resulting impacts are complemented with the absorption of larger amounts of reactive power by wind generators. In addition, seasonal variations and inter-farm wake effects further deteriorate the overall system performance and restrict the optimal use of available wind resources. This paper presented an assessment framework to address the power quality issues that have arisen after integrating large-scale wind farms into weak transmission grids, especially considering inter-farm wake effect, seasonal variations, reactive power depletion, and compensation with a variety of voltage-ampere reactive (Var) devices. Herein, we also proposed a recovery of significant active power deficits caused by the wake effect via increasing hub height of wind turbines. For large-scale wind energy penetration, a real case study was considered for three wind farms with a cumulative capacity of 154.4 MW integrated at a Nooriabad Grid in Pakistan to analyze their overall impacts. An actual test system was modeled in MATLAB Simulink for a composite analysis. Simulations were performed for various scenarios to consider wind intermittency, seasonal variations across four seasons, and wake effect. The capacitor banks and various flexible alternating current transmission systems (FACTS) devices were employed for a comparative analysis with and without considering the inter-farm wake effect. The power system parameters along with active and reactive power deficits were considered for comprehensive analysis. Unified power flow controller (UPFC) was found to be the best compensation device through comparative analysis, as it maintained voltage at nearly 1.002 pu, suppressed frequency transient in a range of 49.88–50.17 Hz, and avoided any resonance while maintaining power factors in an allowable range. Moreover, it also enhanced the power handling capability of the power system. The 20 m increase in hub height assisted the recovery of the active power deficit to 48%, which thus minimized the influence of the wake effect. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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21 pages, 4563 KiB

Open AccessFeature PaperArticle

Quantifying Topological Flexibility of Active Distribution Networks Based on Community Detection

by Huizi Gu and Xiaodong Chu

Energies 2020, 13(18), 4786; https://doi.org/10.3390/en13184786 - 14 Sep 2020

Viewed by 2040

Abstract

Active distribution networks (ADNs) provide a flexible platform to integrate various distributed generation sources, among which the intermittent renewable sources impose high operating uncertainty. Topological flexibility of ADNs should be exploited to counter the stochastic operating conditions by modifying the topologies of ADNs. Quantifying the topological flexibility is a vital step to utilize it, which is lacking in previous studies. A quantification method is proposed to measure the topological flexibility of ADNs in this paper. First, the community structures of ADNs are detected to achieve spatial partitions of the networks. Second, an improved spectral clustering algorithm is employed to significantly reduce the dimensionality of the partition space, in which the ADNs are further partitioned using the affinity propagation algorithm. Finally, a topological flexibility metric is defined based on the guiding role of sectionalizing and tie switches within and between communities. The proposed topological flexibility quantification method is a superb approach to the utilization of flexibility resources in distribution networks. Case study results of test ADNs demonstrate the effectiveness and efficiency of the proposed quantification method. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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17 pages, 4089 KiB

Open AccessArticle

Defect Texts Mining of Secondary Device in Smart Substation with GloVe and Attention-Based Bidirectional LSTM

by Kai Chen, Rabea Jamil Mahfoud, Yonghui Sun, Dongliang Nan, Kaike Wang, Hassan Haes Alhelou and Pierluigi Siano

Energies 2020, 13(17), 4522; https://doi.org/10.3390/en13174522 - 1 Sep 2020

Cited by 23 | Viewed by 3021

Abstract

In the process of the operation and maintenance of secondary devices in smart substation, a wealth of defect texts containing the state information of the equipment is generated. Aiming to overcome the low efficiency and low accuracy problems of artificial power text classification and mining, combined with the characteristics of power equipment defect texts, a defect texts mining method for a secondary device in a smart substation is proposed, which integrates global vectors for word representation (GloVe) method and attention-based bidirectional long short-term memory (BiLSTM-Attention) method in one model. First, the characteristics of the defect texts are analyzed and preprocessed to improve the quality of the defect texts. Then, defect texts are segmented into words, and the words are mapped to the high-dimensional feature space based on the global vectors for word representation (GloVe) model to form distributed word vectors. Finally, a text classification model based on BiLSTM-Attention was proposed to classify the defect texts of a secondary device. Precision, Recall and F1-score are selected as evaluation indicators, and compared with traditional machine learning and deep learning models. The analysis of a case study shows that the BiLSTM-Attention model has better performance and can achieve the intelligent, accurate and efficient classification of secondary device defect texts. It can assist the operation and maintenance personnel to make scientific maintenance decisions on a secondary device and improve the level of intelligent management of equipment. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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27 pages, 6331 KiB

Open AccessArticle

Distributed Resilient Voltage and Reactive Power Control for Islanded Microgrids under False Data Injection Attacks

by Liang Ma and Gang Xu

Energies 2020, 13(15), 3828; https://doi.org/10.3390/en13153828 - 25 Jul 2020

Cited by 9 | Viewed by 2529

Abstract

This paper addresses the problem of voltage and reactive power control of inverter-based distributed generations (DGs) in an islanded microgrid subject to False Data Injection (FDI) attacks. To implement average voltage restoration and reactive power sharing, a two-layer distributed secondary control framework employing a multiagent system (MAS)-based dynamic consensus protocol is proposed. While communication network facilitates distributed control scheme, it leads to vulnerability of microgrids to malicious cyber-attacks. The adverse effects of FDI attack on the secondary controller are analyzed, and the necessary and sufficient conditions to model stealthy attack and probing attack are discussed in detail. A trust-based resilient control strategy is developed to resist the impacts of FDI attack. Based on the forward-backward consistency criterion, the self-monitoring and neighbor-monitoring mechanisms are developed to detect the misbehaving DGs. A group decision-making mechanism is also introduced to settle conflicts arising from the dishonest trust index caused by colluding attacks. A novel mitigation countermeasure is designed to eliminate the adversarial effects of attack: the discarding information mechanism is used to prevent the propagation of false data in the cooperative network while the recovery actions are designed to correct the deviations of collective estimation error in both transient disturbance and continuous FDI attack scenarios. Through a theoretical analysis, it is proved that the proposed mitigation and recovery mechanism can maintain the correct average estimates of voltage and reactive power, which ensures the secondary control objectives of microgrids under FDI attack. Simulation results on an islanded microgrid show the effectiveness and resilience of the proposed control scheme. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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23 pages, 5278 KiB

Open AccessArticle

“Peer-to-Peer Plus” Electricity Transaction within Community of Active Energy Agents Regarding Distribution Network Constraints

by Min Fu, Zhiyu Xu, Ning Wang, Xiaoyu Lyu and Weisheng Xu

Energies 2020, 13(9), 2408; https://doi.org/10.3390/en13092408 - 11 May 2020

Cited by 14 | Viewed by 2767

Abstract

This paper proposes the concept “active energy agent (AEA)” to characterize the autonomous and interactive entities of power system. The future distribution network is a peer-to-peer (P2P) community based on numbers of AEAs. A two-stage “P2P Plus” mechanism is developed to address the electricity transaction within AEA community. In the first “P2P” stage, electricity is directly traded among AEAs via P2P price bidding. The model of P2P transaction is established, and the method of multi-dimensional willingness is adopted in price bidding. In the second “Plus” stage, the centralized coordination by distribution company (DisCo) is formulated as a constrained optimization problem, in which the objective is to maximize profit and the constraints are the basic rights of AEAs and line ratings of distribution network. A 30-bus test system including 29 AEAs and main grid is investigated. Numeric simulation results verify the effectiveness of the proposed models and methods regarding flow constraint. Comparative study reveals the economic motivations of AEAs to participate in P2P transaction, the efficiency of combined search, and the benefit of DisCo from pricing control. Full article

(This article belongs to the Special Issue Smart Grids and Flexible Energy Systems)

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