Special Issue "Optimal Dynamic Control of Active Distribution Power System"

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

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Maryam Bahramipanah
E-Mail Website
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
E-Mail Website
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

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 papers will be 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. 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 1900 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 (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Multi-Objective Optimal Power Flow Problems Based on Slime Mould Algorithm
Sustainability 2021, 13(13), 7448; https://doi.org/10.3390/su13137448 - 02 Jul 2021
Viewed by 417
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 [...] Read more.
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)
Show Figures

Figure 1

Article
Resiliency-Oriented Optimization of Critical Parameters in Multi Inverter-Fed Distributed Generation Systems
Sustainability 2021, 13(12), 6699; https://doi.org/10.3390/su13126699 - 12 Jun 2021
Viewed by 568
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 [...] Read more.
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)
Show Figures

Figure 1

Article
A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques
Sustainability 2021, 13(9), 4979; https://doi.org/10.3390/su13094979 - 29 Apr 2021
Cited by 1 | Viewed by 599
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 [...] Read more.
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)
Show Figures

Figure 1

Back to TopTop