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Optimal Dynamic Control of Active Distribution Power System

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 15201

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Special Issue Editors

Dr. Maryam Bahramipanah

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Guest Editor

Department of Electrical and Computer Engineering, Montana State University, Bozeman, Montana 59717, USA
Interests: energy storage systems; renewable energy resources; power system operation and control; smart grids

Dr. Zagros Shahooei

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Guest Editor

Department of Electrical and Computer Engineering, Montana State University, Bozeman, Montana 59717, USA
Interests: smart/micro-grid; renewable energy resources; power system protection and control; energy storage systems; power system reliability

Special Issue Information

Dear Colleagues,

In the last few decades, sustainable energy systems including renewable energy resources such as wind and solar energies attract worldwide attentions to tackle the energy shortage and environmental pollution issues. Although sustainable energies are widely encouraged due to their free of cost and clean aspects, their massive connections in distribution systems has triggered different operation and control challenges. The issue of optimal control of active distribution systems became more challenging due to the lack of direct control over these non-stochastic resources. The purpose of this Special Issue is to contribute to the development of sustainable active distribution systems with high penetration of renewable energy resources. Thus, this Special Issue focuses on different solutions to address the intermittent nature of these resources. Prospective authors are invited to submit original contributions or survey papers for publication in Sustainability. Topics of interest for this Special Issue include but are not limited to the following:

Active management including demand response, integration of energy storage technologies, etc.
Optimization problems in modern active distribution systems
Dynamic optimal power flow
Real-time monitoring using smart metering systems
Decentralized and centralized optimal control paradigm considering operational uncertainties
Novel approaches for integrating energy storage systems and renewable energy resources in a cost-effective and reliable manner
Innovative (hybrid) energy storage technologies
Multi-agent system design for optimally control of active distribution systems
Network clustering for distributed control
Optimal control design for reliability and resiliency
Modeling and detection of cyberattacks
Application of artificial intelligence in addressing active distribution system issues
Real-world applications/case studies

Dr. Maryam Bahramipanah
Dr. Zagros Shahooei
Guest Editors

Manuscript Submission Information

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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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

Sustainable energy
Renewable energy resources
Active distribution network
Distributed generation
Demand response
Energy storage systems
Distributed control
Real-time control
Smart grids

Published Papers (6 papers)

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Research

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36 pages, 10951 KiB

Open AccessArticle

A Cost-Effective Solution for Non-Convex Economic Load Dispatch Problems in Power Systems Using Slime Mould Algorithm

by Vikram Kumar Kamboj, Challa Leela Kumari, Sarbjeet Kaur Bath, Deepak Prashar, Mamoon Rashid, Sultan S. Alshamrani and Ahmed Saeed AlGhamdi

Sustainability 2022, 14(5), 2586; https://0-doi-org.brum.beds.ac.uk/10.3390/su14052586 - 23 Feb 2022

Cited by 21 | Viewed by 2306

Abstract

Slime Mould Algorithm (SMA) is a newly designed meat-heuristic search that mimics the nature of slime mould during the oscillation phase. This is demonstrated in a unique mathematical formulation that utilizes adjustable weights to influence the sequence of both negative and positive propagation waves to develop a method to link food supply with intensive exploration capacity and exploitation affinity. The study shows the usage of the SM algorithm to solve a non-convex and cost-effective Load Dispatch Problem (ELD) in an electric power system. The effectiveness of SMA is investigated for single area economic load dispatch on large-, medium-, and small-scale power systems, with 3-, 5-, 6-, 10-, 13-, 15-, 20-, 38-, and 40-unit test systems, and the results are substantiated by finding the difference between other well-known meta-heuristic algorithms. The SMA is more efficient than other standard, heuristic, and meta-heuristic search strategies in granting extremely ambitious outputs according to the comparison records. Full article

(This article belongs to the Special Issue Optimal Dynamic Control of Active Distribution Power System)

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27 pages, 13556 KiB

Open AccessArticle

A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers

by Mahdiyeh Eslami, Mehdi Neshat and Saifulnizam Abd. Khalid

Sustainability 2022, 14(1), 541; https://0-doi-org.brum.beds.ac.uk/10.3390/su14010541 - 04 Jan 2022

Cited by 38 | Viewed by 2174

Abstract

This paper presents an effective hybrid optimization technique based on a chaotic sine cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to the nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are preferable. In this regard, a nonlinear time domain-based objective function was used. Then, the proposed hybrid chaotic sine cosine pattern search (hCSC-PS) algorithm was employed for solving this optimization problem. The proposed method employed the global search ability of SCA and the local search ability of PS. The performance of the new hCSC-PS was investigated using a set of benchmark functions, and then the results were compared with those of the standard SCA and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed hCSC-PS for the coordinated design of controllers in the power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. In order to ensure the robustness and performance of the proposed controller, the objective function is evaluated for various extreme loading conditions and system configurations. The numerical investigations show that the new approach may provide better optimal damping and outperforms previous methods. Nonlinear time-domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations. Full article

(This article belongs to the Special Issue Optimal Dynamic Control of Active Distribution Power System)

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21 pages, 3181 KiB

Open AccessArticle

Multi-Objective Optimal Power Flow Problems Based on Slime Mould Algorithm

by Sirote Khunkitti, Apirat Siritaratiwat and Suttichai Premrudeepreechacharn

Sustainability 2021, 13(13), 7448; https://0-doi-org.brum.beds.ac.uk/10.3390/su13137448 - 02 Jul 2021

Cited by 60 | Viewed by 2803

Abstract

Solving the optimal power flow problems (OPF) is an important step in optimally dispatching the generation with the considered objective functions. A single-objective function is inadequate for modern power systems, required high-performance generation, so the problem becomes multi-objective optimal power flow (MOOPF). Although the MOOPF problem has been widely solved by many algorithms, new solutions are still required to obtain better performance of generation. Slime mould algorithm (SMA) is a recently proposed metaheuristic algorithm that has been applied to solve several optimization problems in different fields, except the MOOPF problem, while it outperforms various algorithms. Thus, this paper proposes solving MOOPF problems based on SMA considering cost, emission, and transmission line loss as part of the objective functions in a power system. The IEEE 30-, 57-, and 118-bus systems are used to investigate the performance of the SMA on solving MOOPF problems. The objective values generated by SMA are compared with those of other algorithms in the literature. The simulation results show that SMA provides better solutions than many other algorithms in the literature, and the Pareto fronts presenting multi-objective solutions can be efficiently obtained. Full article

(This article belongs to the Special Issue Optimal Dynamic Control of Active Distribution Power System)

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16 pages, 2842 KiB

Open AccessArticle

Resiliency-Oriented Optimization of Critical Parameters in Multi Inverter-Fed Distributed Generation Systems

by Mohammad Alali, Zagros Shahooei and Maryam Bahramipanah

Sustainability 2021, 13(12), 6699; https://0-doi-org.brum.beds.ac.uk/10.3390/su13126699 - 12 Jun 2021

Cited by 1 | Viewed by 1914

Abstract

In the modern power grid, with the growing penetration of renewable and distributed energy systems, the use of parallel inverters has significantly increased. It is essential to achieve stable parallel operation and reasonable power sharing between these parallel inverters. Droop controllers are commonly used to control the power sharing between parallel inverters in an inverter-based microgrid. In this paper, a small signal model of droop controllers with secondary loop control and an internal model-based voltage and current controller is proposed to improve the stability, resiliency, and power sharing of inverter-based distributed generation systems. The distributed generation system’s nonlinear dynamic equations are derived by incorporating the appropriate and accurate models of the network, load, phase locked loop and filters. The obtained model is then trimmed and linearized around its operating point to find the distributed generation system’s state space representation. Moreover, we optimize the critical control parameters of the model, which are found using eigenvalue analysis, and Grey Wolf optimization technique. Through time-domain simulations, we show that the proposed method improves the system’s resiliency, stability, and power sharing characteristics. Full article

(This article belongs to the Special Issue Optimal Dynamic Control of Active Distribution Power System)

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25 pages, 5107 KiB

Open AccessArticle

A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques

by Hatem Diab, Mahmoud Abdelsalam and Alaa Abdelbary

Sustainability 2021, 13(9), 4979; https://0-doi-org.brum.beds.ac.uk/10.3390/su13094979 - 29 Apr 2021

Cited by 17 | Viewed by 2081

Abstract

Optimal power flow (OPF) is considered one of the most critical challenges that can substantially impact the sustainable performance of power systems. Solving the OPF problem reduces three essential items: operation costs, transmission losses, and voltage drops. An intelligent controller is needed to adjust the power system’s control parameters to solve this problem optimally. However, many constraints must be considered that make the design process of the OPF algorithm exceedingly tricky due to the increased number of limitations and control variables. This paper proposes a multi-objective intelligent control technique based on three different meta-heuristic optimization algorithms: multi-verse optimization (MVO), grasshopper optimization (GOA), and Harris hawks optimization (HHO) to solve the OPF problem. The proposed control techniques were validated by applying them to the IEEE-30 bus system under different operating conditions through MATLAB simulations. The proposed techniques were then compared with the particle swarm optimization (PSO) algorithm, which is very popular in the literature studying how to solving the OPF problem. The obtained results show that the proposed methods are more effective in solving the OPF problem when compared to the commonly used PSO algorithm. The proposed HHO, in particular, shows that it can form a reliable candidate in solving power systems’ optimization problems. Full article

(This article belongs to the Special Issue Optimal Dynamic Control of Active Distribution Power System)

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Review

Jump to: Research

16 pages, 2482 KiB

Open AccessReview

A Review on State Estimation Techniques in Active Distribution Networks: Existing Practices and Their Challenges

by Sepideh Radhoush, Maryam Bahramipanah, Hashem Nehrir and Zagros Shahooei

Sustainability 2022, 14(5), 2520; https://0-doi-org.brum.beds.ac.uk/10.3390/su14052520 - 22 Feb 2022

Cited by 18 | Viewed by 2767

Abstract

This paper provides a comprehensive review of distribution system state estimation in terms of basic definition, different methods, and their application. In the last few years, the operation of distribution networks has been influenced by the installation of distributed generations. In order to control and manage an active distribution network’s performance, distribution system state estimation methods are introduced. A transmission system state estimation cannot be used directly in distribution networks since transmission and distribution networks are different due to topology configuration, the number of buses, line parameters, and the number of measurement instruments. So, the proper state estimation algorithms should be proposed according to the main distribution network features. Accuracy, computational efficiency, and practical implications should be considered in the designing of distribution state estimation techniques since technical issues and wrong decisions could emerge in the control center by inaccurate distribution state estimation results. In this study, conventional techniques are reviewed and compared with data-driven methods in order to highlight the pros and cons of different techniques. Furthermore, the integrated distribution state estimation methods are compared with the distributed approaches, and the different criteria, including the level of area overlapping execution time and computing architecture, are elaborated. Moreover, mathematical problem formulation and different measuring methods are discussed. Full article

(This article belongs to the Special Issue Optimal Dynamic Control of Active Distribution Power System)

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