Smart Energy Systems and Technologies

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: closed (30 July 2021) | Viewed by 15332

Special Issue Editors

Department of Management and Innovation Systems, University of Salerno, 84084 Salerno, Italy
Interests: smart grids; energy management; power systems; demand response
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, there is a large amount of effort required in order to achieve the deployment a smart city. Smart grids are the main parts of smart cities, and they aim to operate energy systems sustainably, efficiently, and securely. In the last few decades, issues such as energy security risks and environmental concerns have arisen, that lead to the deployment of a new type of energy resources, i.e. renewable energy resources. Traditional energy systems need thorough modifications to increase their ability to host such new energy sources; in order to avoid its stable operation and security. To this end, smart grids suggest new concepts, information and communication infrastructures, planning, operation, control, protection and analysis methods for upgrading conventional power systems to be smarter when it comes to achieving full smart energy systems.

Prof. Dr. Pierluigi Siano
Dr. Hassan Haes Alhelou
Guest Editors

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Keywords

  • Smart grids and microgrids
  • Smart energy system
  • Modern power systems
  • Energy system transition
  • Power system planning and operation
  • Power system control, stability, and protection
  • Generation, transmission, and distribution sectors
  • Demand-side management
  • Information and communication infrastructures
  • Distributed generation, demand response, and smart metering
  • Wide-area power systems and PMUs
  • Energy storage systems and flexibility

Published Papers (7 papers)

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Research

31 pages, 15073 KiB  
Article
Fourier Singular Values-Based False Data Injection Attack Detection in AC Smart-Grids
by Moslem Dehghani, Taher Niknam, Mohammad Ghiasi, Pierluigi Siano, Hassan Haes Alhelou and Amer Al-Hinai
Appl. Sci. 2021, 11(12), 5706; https://doi.org/10.3390/app11125706 - 20 Jun 2021
Cited by 14 | Viewed by 2147
Abstract
Cyber-physical threats as false data injection attacks (FDIAs) in islanded smart microgrids (ISMGs) are typical accretion attacks, which need urgent consideration. In this regard, this paper proposes a novel cyber-attack detection model to detect FDIAs based on singular value decomposition (SVD) and fast [...] Read more.
Cyber-physical threats as false data injection attacks (FDIAs) in islanded smart microgrids (ISMGs) are typical accretion attacks, which need urgent consideration. In this regard, this paper proposes a novel cyber-attack detection model to detect FDIAs based on singular value decomposition (SVD) and fast Fourier transform (FFT). Since new research are mostly focusing on FDIAs detection in DC systems, paying attention to AC systems attack detection is also necessary; hence, AC state estimation (SE) have been used in SI analysis and in considering renewable energy sources effect. Whenever malicious data are added into the system state vectors, vectors’ temporal and spatial datum relations might drift from usual operating conditions. In this approach, switching surface based on sliding mode controllers is dialyzed to regulate detailed FFT’s coefficients to calculate singular values. Indexes are determined according to the composition of FFT and SVD in voltage/current switching surface to distinguish the potential cyber-attack. This protection layout is presented for cyber-attack detection and is studied in various types of FDIA forms like amplitude and vector derivation of signals, which exchanged between agents such as smart sensor, control units, smart loads, etc. The prominent advantage of the proposed detection layout is to reduce the time (less than 10 milliseconds from the attack outset) in several kinds of case studies. The proposed method can detect more than 96% accuracy from 2967 sample tests. The performances of the method are carried out on AC-ISMG in MATLAB/Simulink environment. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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15 pages, 346 KiB  
Article
Genetic-Convex Model for Dynamic Reactive Power Compensation in Distribution Networks Using D-STATCOMs
by Oscar Danilo Montoya, Harold R. Chamorro, Lazaro Alvarado-Barrios, Walter Gil-González and César Orozco-Henao
Appl. Sci. 2021, 11(8), 3353; https://doi.org/10.3390/app11083353 - 08 Apr 2021
Cited by 16 | Viewed by 1838
Abstract
This paper proposes a new hybrid master–slave optimization approach to address the problem of the optimal placement and sizing of distribution static compensators (D-STATCOMs) in electrical distribution grids. The optimal location of the D-STATCOMs is identified by implementing the classical and well-known Chu [...] Read more.
This paper proposes a new hybrid master–slave optimization approach to address the problem of the optimal placement and sizing of distribution static compensators (D-STATCOMs) in electrical distribution grids. The optimal location of the D-STATCOMs is identified by implementing the classical and well-known Chu and Beasley genetic algorithm, which employs an integer codification to select the nodes where these will be installed. To determine the optimal sizes of the D-STATCOMs, a second-order cone programming reformulation of the optimal power flow problem is employed with the aim of minimizing the total costs of the daily energy losses. The objective function considered in this study is the minimization of the annual operative costs associated with energy losses and installation investments in D-STATCOMs. This objective function is subject to classical power balance constraints and device capabilities, which generates a mixed-integer nonlinear programming model that is solved with the proposed genetic-convex strategy. Numerical validations in the 33-node test feeder with radial configuration show the proposed genetic-convex model’s effectiveness to minimize the annual operative costs of the grid when compared with the optimization solvers available in GAMS software. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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10 pages, 301 KiB  
Article
The Equivalence between Successive Approximations and Matricial Load Flow Formulations
by María Camila Herrera-Briñez, Oscar Danilo Montoya, Lazaro Alvarado-Barrios and Harold R. Chamorro
Appl. Sci. 2021, 11(7), 2905; https://doi.org/10.3390/app11072905 - 24 Mar 2021
Cited by 12 | Viewed by 1585
Abstract
This paper shows the equivalence of the matricial form of the classical backward/forward load flow formulation for distribution networks with the recently developed successive approximations (SA) load flow approach. Both formulations allow solving the load flow problem in meshed and radial distribution grids [...] Read more.
This paper shows the equivalence of the matricial form of the classical backward/forward load flow formulation for distribution networks with the recently developed successive approximations (SA) load flow approach. Both formulations allow solving the load flow problem in meshed and radial distribution grids even if these are operated with alternating current (AC) or direct current (DC) technologies. Both load flow methods are completely described in this research to make a fair comparison between them and demonstrate their equivalence. Numerical comparisons in the 33- and 69-bus test feeder with radial topology show that both methods have the same number of iterations to find the solution with a convergence error defined as 1×1010. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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12 pages, 338 KiB  
Article
Chaotic Evolutionary Programming for an Engineering Optimization Problem
by Nirbhow Jap Singh, Shakti Singh, Vikram Chopra, Mohd Asim Aftab, S. M. Suhail Hussain and Taha Selim Ustun
Appl. Sci. 2021, 11(6), 2717; https://doi.org/10.3390/app11062717 - 18 Mar 2021
Cited by 5 | Viewed by 1534
Abstract
The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell’s pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic [...] Read more.
The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell’s pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionary programming, whereas exploitation is taken care off by a pattern search. The proposed CEPPS has two variants based on the Gauss map and the tent map. Seven generalized benchmark test functions and six cases of the multi-fuel economic load dispatch problem are considered for the performance analysis. It is observed from the analysis that the CEPPS solution procedure based on the tent map exhibits superiority to obtain an excellent solution and better convergence characteristics than traditional chaotic evolutionary programming. Further, the performance investigation for the considered economic load dispatch shows that the Gauss map CEPPS solution procedure performs better than the tent map based CEPPS to obtain the solution of the multi-fuel economic dispatch problem. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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11 pages, 283 KiB  
Article
A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids
by Alejandro Garces, Walter Gil-González, Oscar Danilo Montoya, Harold R. Chamorro and Lazaro Alvarado-Barrios
Appl. Sci. 2021, 11(5), 1972; https://doi.org/10.3390/app11051972 - 24 Feb 2021
Cited by 10 | Viewed by 2008
Abstract
Phase balancing is a classical optimization problem in power distribution grids that involve phase swapping of the loads and generators to reduce power loss. The problem is a non-linear integer and, hence, it is usually solved using heuristic algorithms. This paper proposes a [...] Read more.
Phase balancing is a classical optimization problem in power distribution grids that involve phase swapping of the loads and generators to reduce power loss. The problem is a non-linear integer and, hence, it is usually solved using heuristic algorithms. This paper proposes a mathematical reformulation that transforms the phase-balancing problem in low-voltage distribution networks into a mixed-integer convex quadratic optimization model. To consider both conventional secondary feeders and microgrids, renewable energies and their subsequent stochastic nature are included in the model. The power flow equations are linearized, and the combinatorial part is represented using a Birkhoff polytope B3 that allows the selection of phase swapping in each node. The numerical experiments on the CIGRE low-voltage test system demonstrate the use of the proposed formulation. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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20 pages, 2575 KiB  
Article
Performance of Hybrid Filter in a Microgrid Integrated Power System Network Using Wavelet Techniques
by Soumya Ranjan Das, Prakash K. Ray, Arun Kumar Sahoo, Somula Ramasubbareddy, Thanikanti Sudhakar Babu, Nallapaneni Manoj Kumar, Hassan Haes Alhelou and Pierluigi Siano
Appl. Sci. 2020, 10(19), 6792; https://doi.org/10.3390/app10196792 - 28 Sep 2020
Cited by 13 | Viewed by 2645
Abstract
Nowadays, the application of distributed energy sources (DES) has been extensively employed to serve the power system by supplying the power into the grid and improving the power quality (PQ). Therefore, DES is one solution that can efficiently overcome the energy crisis and [...] Read more.
Nowadays, the application of distributed energy sources (DES) has been extensively employed to serve the power system by supplying the power into the grid and improving the power quality (PQ). Therefore, DES is one solution that can efficiently overcome the energy crisis and climate change problems. The DES, such as solar photovoltaic (PV), wind turbine (WT), and battery energy storage systems (BESS), are incorporated to form the microgrid (MG), which are interfaced with the power system. However, interfacing MG to the power system is undoubtedly a big challenge. Therefore, more focus is required on the control strategy to control the MG with the power system. To address the PQ problems, a controlled MG integrated with a hybrid shunt active power filter (HSAPF) is provided in this work. For controlling the MG integrated HSAPF, different control strategies are applied. In this work, a learning-based incremental conductance (LINC) technique is used as a maximum power point tracking (MPPT) for tracking the maximum power in PV and WT. The voltage source inverter (VSI) of HSAPF is controlled using a wavelet-based technique with a synchronous reference frame (SRF). The main focus is to improve the PQ by compensating the harmonics and regulating the reactive power in both grid-interactive and islanded condition and also supply continuous and adequate power to the non-linear load. The power system model has been developed with MATLAB/Simulink tool, which shows the efficiency of the proposed method. The results obtained have been satisfactorily under various operating conditions and can be validated further using the real-time dSPACE. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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25 pages, 10127 KiB  
Article
A Robust Adaptive Overcurrent Relay Coordination Scheme for Wind-Farm-Integrated Power Systems Based on Forecasting the Wind Dynamics for Smart Energy Systems
by Mian Rizwan, Lucheng Hong, Muhammad Waseem, Shafiq Ahmad, Mohamed Sharaf and Muhammad Shafiq
Appl. Sci. 2020, 10(18), 6318; https://doi.org/10.3390/app10186318 - 10 Sep 2020
Cited by 27 | Viewed by 2397
Abstract
Conventional protection schemes in the distribution system are liable to suffer from high penetration of renewable energy source-based distributed generation (RES-DG). The characteristics of RES-DG, such as wind turbine generators (WTGs), are stochastic due to the intermittent behavior of wind dynamics (WD). It [...] Read more.
Conventional protection schemes in the distribution system are liable to suffer from high penetration of renewable energy source-based distributed generation (RES-DG). The characteristics of RES-DG, such as wind turbine generators (WTGs), are stochastic due to the intermittent behavior of wind dynamics (WD). It can fluctuate the fault current level, which in turn creates the overcurrent relay coordination (ORC) problem. In this paper, the effects of WD such as wind speed and direction on the short-circuit current contribution from a WTG is investigated, and a robust adaptive overcurrent relay coordination scheme is proposed by forecasting the WD. The seasonal autoregression integrated moving average (SARIMA) and artificial neuro-fuzzy inference system (ANFIS) are implemented for forecasting periodic and nonperiodic WD, respectively, and the fault current level is calculated in advance. Furthermore, the ORC problem is optimized using hybrid Harris hawks optimization and linear programming (HHO–LP) to minimize the operating times of relays. The proposed algorithm is tested on the modified IEEE-8 bus system with wind farms, and the overcurrent relay (OCR) miscoordination caused by WD is eliminated. To further prove the effectiveness of the algorithm, it is also tested in a typical wind-farm-integrated substation. Compared to conventional protection schemes, the results of the proposed scheme were found to be promising in fault isolation with a remarkable reduction in the total operation time of relays and zero miscoordination. Full article
(This article belongs to the Special Issue Smart Energy Systems and Technologies)
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