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Algorithms
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Algorithms in Planning and Operation of Power Systems
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Algorithms in Planning and Operation of Power Systems

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".

Deadline for manuscript submissions: closed (6 March 2022) | Viewed by 17158

Special Issue Editor

Dr. Sergio Rivera

E-Mail Website
Guest Editor
Electrical Engineering, National University of Colombia, Bogotá Cra 45, Colombia.
Interests: reliability of power systems; smart grids; microgrids; multiagent systems; renewable energy

Special Issue Information

Dear Colleagues,

Optimal planning and secure grid operation are a new challenge for modern power systems. Conventional generation assets are becoming a thing of the past. Similarly, conventional grids for power transmission and power distribution are also transforming their paradigms. Now, due to the rising power of the digital age and an era of sustainable development, renewable sources have taken the place of fossil fuels, and smart digital grids are also being used.

Renewable power plants, such as wind power generation (WEG), solar power generation (PVG), and small hydro power plants (SHP), together with the new conception of smart grids, are now chosen more often because, firstly, they are sustainable and environmentally friendly and can thus curb the issue of global warming, and secondly, they are more workable and reliable in commercial use. With this penetration of grids with high levels of stochastic resources, the development of innovative computing tools is necessary in order to obtain a risk-based power generation estimation by evaluating the stochasticity of primary sources (wind, solar, and river flow).

Different algorithm approaches must be applied to meet these modern power system  needs to obtain new solutions for the planning and operation of power systems. Through this approach, new research in this area is looking to expand the application of advanced computing algorithms for the solution of power system problems.

Dr. Sergio Rivera
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • algorithms for operation scheduling of power systems
  • risk-constrained operation scheduling applied to power systems
  • planning power systems with high penetration of intermittent renewable resources and storage technologies
  • power system risk assessment and management algorithms
  • algorithms intended for uncertainty cost functions and stochastic scenario reduction in clean energy modeling
  • scheduling tools for assuring a safe and economic network operation

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Published Papers (6 papers)

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Editorial

Jump to: Research, Review

2 pages, 165 KiB  
Editorial
Special Issue on Algorithms in Planning and Operation of Power Systems
by Sergio R. Rivera
Algorithms 2022, 15(11), 408; https://doi.org/10.3390/a15110408 - 1 Nov 2022
Viewed by 1540
Abstract
Optimal planning and secure grid operation are new challenges facing modern power systems [...] Full article
(This article belongs to the Special Issue Algorithms in Planning and Operation of Power Systems)

Research

Jump to: Editorial, Review

10 pages, 632 KiB  
Article
An Algorithm for Estimation of SF6 Leakage on Power Substation Assets
by Ferley Castro Aranda, Rodolfo García Sierra, Andrés Felipe Cerón Piamba, Benjamin Mailhé and Luis Miguel León Gil
Algorithms 2022, 15(2), 38; https://doi.org/10.3390/a15020038 - 26 Jan 2022
Cited by 1 | Viewed by 2778
Abstract
This paper presents an algorithm that evaluates the current state of an asset fleet containing sulphur hexafluoride (SF6) and estimates its leakage in future electrical power substation projects. The algorithm uses simple models and easy tools to facilitate decision making for [...] Read more.
This paper presents an algorithm that evaluates the current state of an asset fleet containing sulphur hexafluoride (SF6) and estimates its leakage in future electrical power substation projects. The algorithm uses simple models and easy tools to facilitate decision making for transmission and distribution system operator companies. The algorithm is evaluated using data provided by ENEL-CODENSA. The corresponding results are shown, and the estimation values obtained are compared with leakage records in existing assets which helps to understand the advantages and limitations of the algorithm. Full article
(This article belongs to the Special Issue Algorithms in Planning and Operation of Power Systems)
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19 pages, 459 KiB  
Article
Optimal Integration of Dispersed Generation in Medium-Voltage Distribution Networks for Voltage Stability Enhancement
by Brayan Enrique Aguirre-Angulo, Lady Carolina Giraldo-Bello, Oscar Danilo Montoya and Francisco David Moya
Algorithms 2022, 15(2), 37; https://doi.org/10.3390/a15020037 - 25 Jan 2022
Cited by 3 | Viewed by 2748
Abstract
This study addresses the problem of the maximization of the voltage stability index (λ-coefficient) in medium-voltage distribution networks considering the optimal placement and sizing of dispersed generators. The problem is formulated through a mixed-integer nonlinear programming model (MINLP), which is solved [...] Read more.
This study addresses the problem of the maximization of the voltage stability index (λ-coefficient) in medium-voltage distribution networks considering the optimal placement and sizing of dispersed generators. The problem is formulated through a mixed-integer nonlinear programming model (MINLP), which is solved using General Algebraic Modeling System (GAMS) software. A numerical example with a 7-bus radial distribution network is employed to introduce the usage of GAMS software to solve the proposed MINLP model. A new validation methodology to verify the numerical results provided for the λ-coefficient is proposed by using recursive power flow evaluations in MATLAB and DigSILENT software. The recursive evaluations allow the determination of the λ-coefficient through the implementation of the successive approximation power flow method and the Newton–Raphson approach, respectively. It is effected by fixing the sizes and locations of the dispersed sources using the optimal solution obtained with GAMS software. Numerical simulations in the IEEE 33- and 69-bus systems with different generation penetration levels and the possibility of installing one to three dispersed generators demonstrate that the GAMS and the recursive approaches determine the same loadability index. Moreover, the numerical results indicate that, depending on the number of dispersed generators allocated, it is possible to improve the λ-coefficient between 20.96% and 37.43% for the IEEE 33-bus system, and between 18.41% and 41.98% for the IEEE 69-bus system. Full article
(This article belongs to the Special Issue Algorithms in Planning and Operation of Power Systems)
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14 pages, 3642 KiB  
Article
A Heuristic Methods-Based Power Distribution System Optimization Toolbox
by İsmail Alperen Özlü, Olzhas Baimakhanov, Almaz Saukhimov and Oğuzhan Ceylan
Algorithms 2022, 15(1), 14; https://doi.org/10.3390/a15010014 - 28 Dec 2021
Cited by 9 | Viewed by 2582
Abstract
This paper proposes a toolbox for simulating the effective integration of renewable energy sources into distribution systems. The toolbox uses four heuristic methods: the particle swarm optimization (PSO) method, and three recently developed methods, namely Gray Wolf Optimization (GWO), Ant Lion Optimization (ALO), [...] Read more.
This paper proposes a toolbox for simulating the effective integration of renewable energy sources into distribution systems. The toolbox uses four heuristic methods: the particle swarm optimization (PSO) method, and three recently developed methods, namely Gray Wolf Optimization (GWO), Ant Lion Optimization (ALO), and Whale Optimization Algorithm (WOA), for the efficient operation of power distribution systems. The toolbox consists of two main functionalities. The first one allows the user to select the test system to be solved (33-, 69-, or 141-bus test systems), the locations of the distributed generators (DGs), and the voltage regulators. In addition, the user selects the daily active power output profiles of the DGs, and the tool solves the voltage deviation problem for the specified time of day. The second functionality involves the simulation of energy storage systems and provides the optimal daily power output of the resources. With this program, a graphical user interface (GUI) allows users to select the test system, the optimization method to be used, the number of DGs and locations, the locations and number of battery energy storage systems (BESSs), and the tap changer locations. With the simple user interface, the user can manage the distribution system simulation and see the results by making appropriate changes to the test systems. Full article
(This article belongs to the Special Issue Algorithms in Planning and Operation of Power Systems)
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22 pages, 471 KiB  
Article
Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads
by Elkin D. Reyes and Sergio Rivera
Algorithms 2021, 14(10), 276; https://doi.org/10.3390/a14100276 - 25 Sep 2021
Cited by 1 | Viewed by 2125
Abstract
In an effort to quantify and manage uncertainties inside power systems with penetration of renewable energy, uncertainty costs have been defined and different uncertainty cost functions have been calculated for different types of generators and electric vehicles. This article seeks to use the [...] Read more.
In an effort to quantify and manage uncertainties inside power systems with penetration of renewable energy, uncertainty costs have been defined and different uncertainty cost functions have been calculated for different types of generators and electric vehicles. This article seeks to use the uncertainty cost formulation to propose algorithms and solve the problem of optimal power flow extended to controllable renewable systems and controllable loads. In a previous study, the first and second derivatives of the uncertainty cost functions were calculated and now an analytical and heuristic algorithm of optimal power flow are used. To corroborate the analytical solution, the optimal power flow was solved by means of metaheuristic algorithms. Finally, it was found that analytical algorithms have a much higher performance than metaheuristic methods, especially as the number of decision variables in an optimization problem grows. Full article
(This article belongs to the Special Issue Algorithms in Planning and Operation of Power Systems)
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Review

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22 pages, 838 KiB  
Review
A Review of Parallel Heterogeneous Computing Algorithms in Power Systems
by Diego Rodriguez, Diego Gomez, David Alvarez and Sergio Rivera
Algorithms 2021, 14(10), 275; https://doi.org/10.3390/a14100275 - 23 Sep 2021
Cited by 10 | Viewed by 3992
Abstract
The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the [...] Read more.
The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the analysis of power systems are reaching their operational limit since the complexity and size of modern power systems results in long simulation times and high computational demand. Time reductions in simulation and analysis lead to the better and further optimized performance of power systems. Heterogeneous computing—where different processing units interact—has shown that power system applications can take advantage of the unique strengths of each type of processing unit, such as central processing units, graphics processing units, and field-programmable gate arrays interacting in on-premise or cloud environments. Parallel Heterogeneous Computing appears as an alternative to reduce simulation times by optimizing multitask execution in parallel computing architectures with different processing units working together. This paper presents a review of Parallel Heterogeneous Computing techniques, how these techniques have been applied in a wide variety of power system applications, how they help reduce the computational time of modern power system simulation and analysis, and the current tendency regarding each application. We present a wide variety of approaches classified by technique and application. Full article
(This article belongs to the Special Issue Algorithms in Planning and Operation of Power Systems)
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