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

Deadline for manuscript submissions: closed (30 November 2018) | Viewed by 61939

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Prof. Dr. José L. Bernal-Agustín

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Electrical Engineering Department, University of Zaragoza. Calle María de Luna, 3. 50018 Zaragoza, Spain
Interests: evolutionary computation applications to engineering; renewable energy; distribution power system; energy management; electric markets
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Prof. Dr. Rodolfo Dufo-López

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Department of Electrical Engineering, University of Zaragoza, Calle María de Luna, 3, 50018 Zaragoza, Spain
Interests: renewable energy; electricity storage; advanced batteries models; net metering; energy management; optimization algorithms
Special Issues, Collections and Topics in MDPI journals

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

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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 (14 papers)

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Research

22 pages, 3229 KiB

Open AccessArticle

Evaluating the Effect of Financing Costs on PV Grid Parity by Applying a Probabilistic Methodology

by Carlos J. Sarasa-Maestro, Rodolfo Dufo-López and José L. Bernal-Agustín

Appl. Sci. 2019, 9(3), 425; https://doi.org/10.3390/app9030425 - 27 Jan 2019

Cited by 6 | Viewed by 2562

Abstract

This paper presents a study that analyses the effect of financing costs on grid parity in photovoltaic (PV) installations by applying a probabilistic methodology. Three different case studies, located in Spain, have been considered, with 500 kW, 50 kW and 5 kW grid-connected PV generators. The technical and economic calculations were performed, considering the interest rate, yield across the Spanish geography, and PV module cost as parameters. The Monte Carlo method was applied to consider the full probabilistic range of values given to the different variables. The goal of this study was to determine, for the studied cases, the levelised cost of energy (LCOE) and the internal rate of return by considering realistic values of the variables. A success rate parameter was calculated, which determined the likelihood of the number of times that the LCOE was below the retail cost of electricity. All the cases were evaluated by applying 10,000 iterations, considering the standard deviations and means defined. Full article

(This article belongs to the Special Issue Distribution Power Systems)

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23 pages, 4036 KiB

Open AccessArticle

Multiobjective Scheduling of an Active Distribution Network Based on Coordinated Optimization of Source Network Load

by Chengsi Yong, Xiangyu Kong, Ying Chen, Zhijun E, Kai Cui and Xin Wang

Appl. Sci. 2018, 8(10), 1888; https://doi.org/10.3390/app8101888 - 11 Oct 2018

Cited by 28 | Viewed by 3675

Abstract

With the development of active distribution networks, the means of controlling such networks are becoming more abundant, and simultaneously, due to the intermittency of renewable energy and the randomness of the demand-side load, the operating uncertainty is becoming serious. To solve the problem of source–network–load coordination scheduling, a multiobjective scheduling model for an active distribution network (ADN) is proposed in this paper. The operating cost, renewable energy utilization rate, and user satisfaction are considered as the optimization objectives, and the distributed generation (DG) output power, switch number, and incentive price for the responsive load are set as the decision variables. Then the probabilistic power flow based on Monte Carlo sampling and the chance-constrained programming are used to deal with the uncertainty of the ADN. Moreover, the reference point–based many-objective evolutionary algorithm (NSGA3) is used to solve this nonlinear, multiperiod, and multiobjective optimization problem. The effectiveness of the proposed method is verified in the modified IEEE 33-bus distribution system. The results show that the proposed scheduling method can effectively improve the system status. Full article

(This article belongs to the Special Issue Distribution Power Systems)

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18 pages, 5905 KiB

Open AccessArticle

A Hybrid State Estimator Based on SCADA and PMU Measurements for Medium Voltage Distribution System

by Xiangyu Kong, Ying Chen, Tao Xu, Chengshan Wang, Chengsi Yong, Peng Li and Li Yu

Appl. Sci. 2018, 8(9), 1527; https://doi.org/10.3390/app8091527 - 01 Sep 2018

Cited by 33 | Viewed by 4578

Abstract

With the increasing importance of renewable energy and flexible loads, the operation of the distribution system is becoming more stochastic and complex, and it is necessary to monitor the power system in real-time. Considering the gradual applications of intelligent electronic devices in the distribution systems, a hybrid state estimator based on supervisory control and data acquisition (SCADA) and phasor measurement unit (PMU) measurements is proposed in this paper, which consists of the improved robust estimation and linear state estimation. At the time of SCADA data acquisition, the improved robust estimation combining the SCADA measurements with PMU measurements is performed. To eliminate the effect of bad data, the internal student residual method is introduced, and the robust thresholds are adjusted adaptively. Then the linear state estimation is performed at the time of PMU data acquisition based on the results of the previous estimation time and the PMU measurements, which can quickly correct the robust estimation results and track the changes of the distribution system. Finally, the effectiveness and performance of the proposed method are verified in a modified IEEE 33-bus distribution system and a real distribution system in China. Full article

(This article belongs to the Special Issue Distribution Power Systems)

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17 pages, 3000 KiB

Open AccessArticle

Sizing Hybrid Energy Storage Systems for Distributed Power Systems under Multi-Time Scales

by Huanan Liu, Dezhi Li, Yuting Liu, Mingyu Dong, Xiangnan Liu and Hong Zhang

Appl. Sci. 2018, 8(9), 1453; https://doi.org/10.3390/app8091453 - 24 Aug 2018

Cited by 12 | Viewed by 5305

Abstract

With the rapid development of industry, more fossil energy is consumed to generate electricity, which increases carbon emissions and aggravates the burden of environmental protection. To reduce carbon emissions, traditional centralized power generation networks are transforming into distributed renewable generation systems. However, the deployment of distributed generation systems can affect power system economy and stability. In this paper, under different time scales, system economy, stability, carbon emissions, and renewable energy fluctuation are comprehensively considered to optimize battery and super-capacitor installation capacity for an off-grid power system. After that, based on the genetic algorithm, this paper shows the optimal system operation strategy under the condition of the theoretical best energy storage capacity. Finally, the theoretical best capacity is tested under different renewable energy volatility rates. The simulation results show that by properly sizing the storage system’s capacity, although the average daily costs of the system can increase by 10%, the system’s carbon emissions also reduce by 42%. Additionally, the system peak valley gap reduces by 23.3%, and the renewable energy output’s fluctuation range and system loss of load probability are successfully limited in an allowable range. Lastly, it has less influence on the theoretical best energy storage capacity if the renewable energy volatility rate can be limited to within 10%. Full article

(This article belongs to the Special Issue Distribution Power Systems)

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16 pages, 1342 KiB

Open AccessArticle

Methods for Aggregation and Remuneration of Distributed Energy Resources

by Pedro Faria, João Spínola and Zita Vale

Appl. Sci. 2018, 8(8), 1283; https://doi.org/10.3390/app8081283 - 01 Aug 2018

Cited by 13 | Viewed by 3275

Abstract

Distributed energy resource integration in power systems has advantages and challenges in both the economic and the technical operation of the system. An aggregator, as in the case of a Virtual Power Player, is essential in order to support the operation of these small size resources. Innovative approaches capable of supporting the decisions made in terms of resource scheduling, aggregation and remuneration are needed. The present paper addresses a methodology capable of managing resources through the activities of an aggregator, providing different choices of aggregation and remuneration strategies. The methodology is validated in a case study regarding a 21-bus network, composed of 20 consumers and 26 producers. Full article

(This article belongs to the Special Issue Distribution Power Systems)

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15 pages, 1733 KiB

Open AccessArticle

Fault Location in Double Circuit Medium Power Distribution Networks Using an Impedance-Based Method

by Rahman Dashti, Seyed Mehdi Salehizadeh, Hamid Reza Shaker and Maryamsadat Tahavori

Appl. Sci. 2018, 8(7), 1034; https://doi.org/10.3390/app8071034 - 25 Jun 2018

Cited by 25 | Viewed by 3841

Abstract

The distribution network is extended throughout cities, towns, and villages. Because of the increase in loads and the decrease in power passageways and public corridor reduction, double circuit lines are increasingly being used instead of single circuit lines. Fault location in double circuit power networks is very important because it decreases the repair time and consequently the power outage time. In this paper, a new improved method for fault location in double circuit medium power distribution lines is proposed. The suggested impedance-based fault location method takes into account the mutual effect of double circuit lines on each other. To the best of our knowledge, the proposed method is the first of its kind which supports double circuit distribution networks. In the proposed method, a new quadratic equation for locating fault in power distribution networks is obtained using recorded voltage and current at the beginning of feeder. In this method, the π line model is used for improving the accuracy of the suggested method. The proposed method is supported by mathematical proofs and derivation. To evaluate the accuracy of the proposed method, the proposed method is tested on a thirteen-node network in different conditions, such as instrument error, various fault resistances, and different fault inception angles in various distances and fault types. The numerical results confirm the high accuracy and validity of the proposed method. Full article

(This article belongs to the Special Issue Distribution Power Systems)

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18 pages, 1737 KiB

Open AccessArticle

An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization

by Nur Faziera Napis, Aida Fazliana Abd. Kadir, Tamer Khatib, Elia Erwani Hassan and Mohamad Fani Sulaima

Appl. Sci. 2018, 8(5), 804; https://doi.org/10.3390/app8050804 - 16 May 2018

Cited by 13 | Viewed by 3348

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 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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5190 KiB

Open AccessArticle

CSO Based Solution for Load Kickback Effect in Deregulated Power Systems

by K. Selvakumar, K. Vijayakumar and C.S. Boopathi

Appl. Sci. 2017, 7(11), 1127; https://doi.org/10.3390/app7111127 - 01 Nov 2017

Cited by 6 | Viewed by 4081

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 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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2841 KiB

Open AccessArticle

Island Partition of Distribution System with Distributed Generators Considering Protection of Vulnerable Nodes

by Gang Xu, Shunyu Wu and Yuanpeng Tan

Appl. Sci. 2017, 7(10), 1057; https://doi.org/10.3390/app7101057 - 16 Oct 2017

Cited by 17 | Viewed by 3414

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 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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4228 KiB

Open AccessArticle

A Congestion Control Strategy for Power Scale-Free Communication Network

by Min Xiang and Qinqin Qu

Appl. Sci. 2017, 7(10), 1054; https://doi.org/10.3390/app7101054 - 13 Oct 2017

Cited by 6 | Viewed by 3838

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 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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2657 KiB

Open AccessArticle

Optimal System Frequency Response Model and UFLS Schemes for a Small Receiving-End Power System after Islanding

by Deyou Yang, Shiyu Liu and Guowei Cai

Appl. Sci. 2017, 7(5), 468; https://doi.org/10.3390/app7050468 - 02 May 2017

Cited by 5 | Viewed by 4429

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. 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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1805 KiB

Open AccessArticle

A Short-Term Photovoltaic Power Prediction Model Based on an FOS-ELM Algorithm

by Jidong Wang, Ran Ran and Yue Zhou

Appl. Sci. 2017, 7(4), 423; https://doi.org/10.3390/app7040423 - 21 Apr 2017

Cited by 32 | Viewed by 4167

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 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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3270 KiB

Open AccessArticle

Bi-Level Programming Approach for the Optimal Allocation of Energy Storage Systems in Distribution Networks

by Nian Shi and Yi Luo

Appl. Sci. 2017, 7(4), 398; https://doi.org/10.3390/app7040398 - 14 Apr 2017

Cited by 16 | Viewed by 5162

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 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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7836 KiB

Open AccessArticle

Use of the Genetic Algorithm-Based Fuzzy Logic Controller for Load-Frequency Control in a Two Area Interconnected Power System

by Ertugrul Cam, Goksu Gorel and Hayati Mamur

Appl. Sci. 2017, 7(3), 308; https://doi.org/10.3390/app7030308 - 22 Mar 2017

Cited by 41 | Viewed by 8905

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 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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