Special Issue "Distribution Power Systems"

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

Deadline for manuscript submissions: 31 August 2018

Special Issue Editors

Guest Editor
Prof. Dr. José L. Bernal-Agustín

Electrical Engineering. Department, University of Zaragoza. Calle María de Luna, 3. 50018 Zaragoza, Spain
Website | E-Mail
Phone: +34 976 76 19 21
Fax: +34 976 76 22 26
Interests: Evolutionary Computation Applications to Engineering; Renewable Energy; Distribution Power System; Electric Markets
Guest Editor
Dr. Rodolfo Dufo-López

Electrical Engineering. Department, University of Zaragoza. Calle María de Luna, 3. 50018 Zaragoza, Spain
Website | E-Mail
Interests: renewable energy; distribution power systems; electricity storage; net metering, optimization algorithms

Special Issue Information

Dear Colleagues,

Distribution Power Systems involve all the equipment and devices that carry electrical energy from the transmission system to consumers, including low voltage (LV) and medium voltage (MV). Therefore, their function is relevant, as it is necessary to offer high reliability at a reasonable cost. If a power system’s reliability is low, consumers will suffer repeated power cuts; an excessively high cost will result in high electricity cost for consumers. Another aspect to consider is distributed generation, which is usually connected to Distribution Power Systems. If the distributed generation has a renewable origin, it is necessary to take into account its possible variability, so the technical and operational aspects have to be studied properly. In addition, the economic regime of distributed generation based on renewable sources presents great differences between different countries, depending on the different policies applied in each one of them. “Net metering” is applied in many countries to encourage the installation of renewable distributed generation (mainly photovoltaic), and different schemes of net metering (or “net billing”) are used in different countries. Other topics of interest related to the previous ones are smart grids and demand side management. 

Taking into account all the above, this Special Issue is dedicated to topics related to Distribution Power Systems, including both technical and economic topics.

Prof. Dr. José L. Bernal-Agustín
Dr. Rodolfo Dufo-López
Guest Editors

Manuscript Submission Information

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Keywords

  • Reliability and cost of Distribution Power Systems.
  • Distributed generation
  • Energy policies
  • Net metering
  • Smart Grids
  • Demand side management

Published Papers (8 papers)

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Research

Open AccessArticle An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization
Appl. Sci. 2018, 8(5), 804; https://doi.org/10.3390/app8050804
Received: 22 April 2018 / Revised: 9 May 2018 / Accepted: 14 May 2018 / Published: 16 May 2018
Cited by 1 | PDF Full-text (1737 KB) | HTML Full-text | XML Full-text
Abstract
The presence of optimized distributed generation (DG) with suitable distribution network reconfiguration (DNR) in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a
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The presence of optimized distributed generation (DG) with suitable distribution network reconfiguration (DNR) in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO) is proposed in this research. The objective function is formulated to minimize the total power losses (TPL) and to improve the voltage stability index (VSI). The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO) and iteration particle swarm optimization (IPSO). Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle CSO Based Solution for Load Kickback Effect in Deregulated Power Systems
Appl. Sci. 2017, 7(11), 1127; https://doi.org/10.3390/app7111127
Received: 18 September 2017 / Accepted: 25 October 2017 / Published: 1 November 2017
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Abstract
With increase in power demand, load demand values have also risen to a greater extent. Sometimes, these demands are met with the great difficulties. All these difficulties drive us to seek other alternative ways. One such a way demand response (DR) is considered
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With increase in power demand, load demand values have also risen to a greater extent. Sometimes, these demands are met with the great difficulties. All these difficulties drive us to seek other alternative ways. One such a way demand response (DR) is considered in this paper, it is a new concept that is introduced in the system in order to reduce peak hour stresses. When implementing the demand response, the main setbacks that arise is the load kickback effect, which the sudden rise in demand during non-peak hours that is caused by the overuse of power by consumers, after their constant reduction of power during peak hours. This paper discusses the various kickback load types, and an effective approach to avoid and tackle kickback effect, by an effective method Cat Swarm Optimization (CSO), which is based on studying the movement of cats. The optimization has been implemented on an IEEE 30 bus and 75 bus Indian utility system, and the results are discussed. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle Island Partition of Distribution System with Distributed Generators Considering Protection of Vulnerable Nodes
Appl. Sci. 2017, 7(10), 1057; https://doi.org/10.3390/app7101057
Received: 5 September 2017 / Accepted: 12 October 2017 / Published: 16 October 2017
Cited by 1 | PDF Full-text (2841 KB) | HTML Full-text | XML Full-text
Abstract
To improve the reliability of power supply in the case of the fault of distribution system with multiple distributed generators (DGs) and reduce the influence of node voltage fluctuation on the stability of distribution system operation in power restoration, this paper proposes an
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To improve the reliability of power supply in the case of the fault of distribution system with multiple distributed generators (DGs) and reduce the influence of node voltage fluctuation on the stability of distribution system operation in power restoration, this paper proposes an island partition strategy of the distribution system considering the protection of vulnerable nodes. First of all, the electrical coupling coefficient of neighboring nodes is put forward according to distribution system topology and equivalent electrical impedance, and the power-dependence relationship between neighboring nodes is calculated based on the direction and level of the power flow between nodes. Then, the bidirectional transmission of the coupling features of neighboring nodes is realized through the modified PageRank algorithm, thus identifying the vulnerable nodes that have a large influence on the stability of distribution system operation. Next, combining the index of node vulnerability, an island partition model is constructed with the restoration of important loads as the primary goal. In addition, the mutually exclusive firefly algorithm (MEFA) is also proposed to realize the interaction of learning and competition among fireflies, thus enhancing the globally optimal solution search ability of the algorithm proposed. The proposed island partition method is verified with a Pacific Gas and Electric Company (PG and E) 60-node test system. Comparison with other methods demonstrates that the new method is feasible for the distribution system with multiple types of distributed generations and valid to enhance the stability and safety of the grid with a relatively power restoration ratio. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle A Congestion Control Strategy for Power Scale-Free Communication Network
Appl. Sci. 2017, 7(10), 1054; https://doi.org/10.3390/app7101054
Received: 17 September 2017 / Accepted: 11 October 2017 / Published: 13 October 2017
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Abstract
The scale-free topology of power communication network leads to more data flow in less hub nodes, which can cause local congestion. Considering the differences of the nodes’ delivery capacity and cache capacity, an integrated routing based on the communication service classification is proposed
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The scale-free topology of power communication network leads to more data flow in less hub nodes, which can cause local congestion. Considering the differences of the nodes’ delivery capacity and cache capacity, an integrated routing based on the communication service classification is proposed to reduce network congestion. In the power communication network, packets can be classified as key operational services (I-level) and affairs management services (II-level). The shortest routing, which selects the path of the least hops, is adopted to transmit I-level packets. The load-balanced global dynamic routing, which uses the node’s queue length and delivery capacity to establish the cost function and chooses the path with minimal cost, is adopted to transmit II-level packets. The simulation results show that the integrated routing has a larger critical packet generation rate and can effectively reduce congestion. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle Optimal System Frequency Response Model and UFLS Schemes for a Small Receiving-End Power System after Islanding
Appl. Sci. 2017, 7(5), 468; https://doi.org/10.3390/app7050468
Received: 14 March 2017 / Revised: 19 April 2017 / Accepted: 26 April 2017 / Published: 2 May 2017
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Abstract
Large frequency deviations after islanding are exceedingly critical in small receiving-end power systems. The under-frequency load shedding (UFLS) scheme is an efficient protection step for preventing system black outs. It is very important to get an exact model to design the UFLS schemes.
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Large frequency deviations after islanding are exceedingly critical in small receiving-end power systems. The under-frequency load shedding (UFLS) scheme is an efficient protection step for preventing system black outs. It is very important to get an exact model to design the UFLS schemes. In this paper, an optimization model to achieve the system frequency response (SFR) model either from the full-scale power system or from test records was proposed. The optimized SFR model took into account the response of governors-prime movers and the dynamic characteristics of loads developed in the modern power system. Then the UFLS schemes were designed via the optimized SFR model and particle swarm optimization (PSO) method. The time-domain simulation with the actual small receiving-end power system was presented to investigate the validity of the presented model and the developed technique. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle A Short-Term Photovoltaic Power Prediction Model Based on an FOS-ELM Algorithm
Appl. Sci. 2017, 7(4), 423; https://doi.org/10.3390/app7040423
Received: 8 March 2017 / Revised: 12 April 2017 / Accepted: 17 April 2017 / Published: 21 April 2017
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Abstract
With the increasing proportion of photovoltaic (PV) power in power systems, the problem of its fluctuation and intermittency has become more prominent. To reduce the negative influence of the use of PV power, we propose a short-term PV power prediction model based on
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With the increasing proportion of photovoltaic (PV) power in power systems, the problem of its fluctuation and intermittency has become more prominent. To reduce the negative influence of the use of PV power, we propose a short-term PV power prediction model based on the online sequential extreme learning machine with forgetting mechanism (FOS-ELM), which can constantly replace outdated data with new data. We use historical weather data and historical PV power data to predict the PV power in the next period of time. The simulation result shows that this model has the advantages of a short training time and high accuracy. This model can help the power dispatch department schedule generation plans as well as support spatial and temporal compensation and coordinated power control, which is important for the security and stability as well as the optimal operation of power systems. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle Bi-Level Programming Approach for the Optimal Allocation of Energy Storage Systems in Distribution Networks
Appl. Sci. 2017, 7(4), 398; https://doi.org/10.3390/app7040398
Received: 12 March 2017 / Revised: 5 April 2017 / Accepted: 12 April 2017 / Published: 14 April 2017
Cited by 2 | PDF Full-text (3270 KB) | HTML Full-text | XML Full-text
Abstract
Low-CO2-emission wind generation can alleviate the world energy crisis, but intermittent wind generation influences the reliability of power systems. Energy storage might smooth the wind power fluctuations and effectively improve system reliability. The contribution of energy storage to system reliability cannot
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Low-CO2-emission wind generation can alleviate the world energy crisis, but intermittent wind generation influences the reliability of power systems. Energy storage might smooth the wind power fluctuations and effectively improve system reliability. The contribution of energy storage to system reliability cannot be comprehensively assessed by the installed capacity of energy storage. The primary goal of this paper is to investigate the impact of the installed location and capacity of energy storage on power system reliability. Based on a bi-level programming approach, this paper presents a bi-level energy storage programming configuration model for energy storage capacity and location configuration. For upper-level optimization, a depth search method is utilized to obtain the optimal installed location of energy storage. For the lower-level optimization, the optimal capacity of energy storage is solved to meet the system reliability requirements. The influence of the contribution of energy storage location to system reliability is analyzed. The proposed model and method are demonstrated using the RBTS-Bus6 System and Nanao (NA) island distribution system in China. The results show the effectiveness and practicability of the proposed model and method. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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Open AccessArticle Use of the Genetic Algorithm-Based Fuzzy Logic Controller for Load-Frequency Control in a Two Area Interconnected Power System
Appl. Sci. 2017, 7(3), 308; https://doi.org/10.3390/app7030308
Received: 27 February 2017 / Revised: 14 March 2017 / Accepted: 16 March 2017 / Published: 22 March 2017
Cited by 1 | PDF Full-text (7836 KB) | HTML Full-text | XML Full-text
Abstract
The use of renewable energy resources has created some problems for power systems. One of the most important of these is load frequency control (LFC). In this study, in order to solve the LFC problem, modern control methods were applied to a two
[...] Read more.
The use of renewable energy resources has created some problems for power systems. One of the most important of these is load frequency control (LFC). In this study, in order to solve the LFC problem, modern control methods were applied to a two area multi source interconnected power system. A photovoltaic solar power plant (PV-SPP) was also connected, in order to identify the harmful effects on the frequency of the system. A new Genetic-based Fuzzy Logic (GA-FL) controller was designed to control the frequency of the system. For comparison, conventional proportional-integral-derivative (PID), fuzzy logic (FL), and Genetic Algorithm (GA)-PID controllers were also designed. The new control method exhibited a better performance than the conventional and other modern control methods, because of the low overshoot and short settling time. All simulations were realized with the Matlab-Simulink program. Full article
(This article belongs to the Special Issue Distribution Power Systems)
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