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Optimal Power Flow: Optimization and Control of Electric Power Systems

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 31788

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Prof. Dr. Almoataz Youssef Abdelaziz

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Electrical Power & Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
Interests: artificial intelligence; evolutionary and heuristic optimization algorithms; power systems operation, planning, and control
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Prof. Dr. Attia El-Fergany

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Department of Electric Power Engineering, Zagazig University, Zagazig 44519, Egypt
Interests: power system operations; planning and control; integrations of renewables to power systems; smart grids; artificial intelligence applications; power quality issues
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Prof. Dr. Ragab A. El-Sehiemy

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Electrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
Interests: power system modeling, computation, and control; renewable energy; microgrids
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Special Issue Information

Dear Colleagues,

The optimal power flow (OPF) model represents the problem of determining the best operating levels for electric power plants in order to meet demands given throughout a transmission network. Recently, many optimization methods have been developed to solve the OPF problem, particularly nonlinear complex optimization problems. Intelligent optimization methods are based on different concepts, such as evolutionary-inspired algorithms, human-inspired algorithms, natural-inspired algorithms, and artificial neural networks

This Special Issue (SI) aims at presenting novel research on optimization and control of electrical power systems. Confidently, this SI represents a hub for contributors/researchers for sharing their interesting, up-to-date research results. The key subjects of interest comprise, but are not limited to the following:

All categories of economic load dispatch and optimal power flow in electrical power systems;
Multi-objective optimal power flow in electrical power systems;
Ill-condition optimal power flow;
Solution of large-scale security constrained optimal power flow;
Decomposition methods for distributed optimal power flow;
Optimal power flow and demand response;
Applications of artificial intelligence optimization in electrical power systems;
Stochastic optimal power flow with renewable energy integration;
Real-time operation of electrical systems;
Deregulated power systems;
Optimal power flow with integration of FACTS devices;
Optimal allocations of electrical components in power systems;
Optimal sizing of energy storage battery in electrical power systems;
Renewable energy sources and support of energy storage systems;
Power flow analysis and optimization in ring distribution networks;
Smart grid and virtual power plants;
Grid integration of renewable sources;
Optimal power flow problem in hybrid AC/DC grids;
Vehicle to grid operation;
Planning of charging stations and their impact on the electrical grid.

Prof. Almoataz Youssef Abdelaziz
Prof. Dr. Attia El-Fergany
Prof. Dr. Ragab A. El-Sehiemy
Guest Editors

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Keywords

economic load dispatch
multi-objective optimal power flow
smart grid and virtual power plants
deregulated power systems

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Published Papers (12 papers)

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Research

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17 pages, 2859 KiB

Open AccessArticle

Optimizing Real and Reactive Power Dispatch Using a Multi-Objective Approach Combining the ϵ-Constraint Method and Fuzzy Satisfaction

by Ricardo Villacrés and Diego Carrión

Energies 2023, 16(24), 8034; https://doi.org/10.3390/en16248034 - 13 Dec 2023

Cited by 2 | Viewed by 1168

Abstract

Optimal power dispatch is essential to improve the power system’s safety, stability, and optimal operation. The present research proposes a multi-objective optimization methodology to solve the real and reactive power dispatch problem by minimizing the active power losses and generation costs based on mixed-integer nonlinear programming (MINLP) using the epsilon constraint method and fuzzy satisficing approach. The proposed methodology was tested on the IEEE 30-bus system, in which each objective function was modeled and simulated independently to verify the results with what is obtained via Digsilent Power Factory and then combined, which no longer allows for the simulation of Digsilent Power Factory. One of the main contributions was demonstrating that the proposed methodology is superior to the one available in Digsilent Power Factory, since this program only allows for the analysis of single-objective problems. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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18 pages, 2388 KiB

Open AccessFeature PaperArticle

New Distributed Optimization Method for TSO–DSO Coordinated Grid Operation Preserving Power System Operator Sovereignty

by Steffen Meinecke, David Sebastian Stock and Martin Braun

Energies 2023, 16(12), 4753; https://doi.org/10.3390/en16124753 - 16 Jun 2023

Cited by 2 | Viewed by 1450

Abstract

Electrical power system operators (SOs) are free to realize grid operations according to their own strategies. However, because resulting power flows also depend on the actions of neighboring SOs, appropriate coordination is needed to improve the resulting system states from an overall perspective and from an individual SO perspective. In this paper, a new method is presented that preserves the data integrity of the SOs and their independent operation of their grids. This method is compared with a non-coordinated local control and another sequential method that has been identified as the most promising distributed optimization method in previous research. The time series simulations use transformer tap positioning as well as generation unit voltage setpoints and reactive power injections as flexibilities. The methods are tested on a multi-voltage, multi-SO, realistic benchmark grid with different objective combinations of the SOs. In conclusion, the results of the new method are much closer to the theoretical optimum represented by central optimization than those of the other two methods. Furthermore, the introduced method integrates a sophisticated procedure to provide fairness between SOs that is missing in other methods. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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14 pages, 578 KiB

Open AccessArticle

Robust Placement and Control of Phase-Shifting Transformers Considering Redispatch Measures

by Allan Santos and Florian Steinke

Energies 2023, 16(11), 4438; https://doi.org/10.3390/en16114438 - 31 May 2023

Cited by 1 | Viewed by 1095

Abstract

Flexible AC transmission systems (FACTSs) can maximize capacity utilization under time-varying grid usage patterns by actively controlling the power flow of the transmission lines, e.g., with phase-shifting transformers (PST). In this paper, we propose an algorithm to determine the minimum number of PSTs and their location such that the grid can operate robustly for any realization of the (active) power set points from a known, continuous uncertainty set. As we show in our experiments, only considering a few extreme grid scenarios cannot provide this guarantee. The proposed algorithm considers the trade-offs between PST placement and operational decisions, such as PST control and redispatch. By minimizing the worst-case redispatch cost, it yields two affine linear control policies for these as a byproduct. Power flow is modeled as a constrained linear system, and the control design and actuator minimization tasks are formulated as a mixed-integer linear program (MILP). We also design a greedy algorithm, whose optimal value differs less than 20% from the MILP solution while being one to two orders of magnitude faster to compute. The proposed algorithm is evaluated for a small demonstrative 3-bus example and the IEEE 39 bus test system. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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20 pages, 8836 KiB

Open AccessArticle

Seamless Transition and Fault-Ride-Through by Using a Fuzzy EO PID Controller in AVR System

by Ahmed O. Badr, Soha Mansour, Mariam A. Sameh and Mahmoud A. Attia

Energies 2022, 15(22), 8475; https://doi.org/10.3390/en15228475 - 13 Nov 2022

Cited by 5 | Viewed by 1260

Abstract

One of the most crucial control aspects in electric power networks is ensuring constant voltage levels throughout different circumstances. To overcome this problem, an automatic voltage regulator (AVR) is installed in the electrical power networks to preserve the voltage at its allowable range. In this paper, a fuzzy-based PID controller was used to enhance the AVR dynamic performance under several operating conditions. Moreover, an Equilibrium Optimizer (EO) algorithm was used to initialize the controller gains. The validation of the proposed controller was proven through three different systems. The first was a simple AVR system under fixed and dynamic references. The proposed fuzzy EO PID controller proved its superiority in this case through the reduction of voltage overshoot by around 3–28% compared with the reported methods in the literature. Then, the fault-ride through capability of the proposed controller was proven through the second system, which was the Kundur two-area system suffering from a 3-phase fault condition, where the overshoot with the proposed controller was reduced by 4–7% compared with the default controller and modern weighted method reported in the literature. Lastly, an IEEE 9-bus system performance was tested with the proposed controller under normal, faulty, and dynamic loading conditions. Again, the proposed controller succeeded in reducing the maximum overshoot by around 5% compared with the default controller in the system. Moreover, the proposed controller achieved a seamless transition between the islanding and grid-connected mode of operation. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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33 pages, 10188 KiB

Open AccessArticle

A Slime Mould Algorithm Programming for Solving Single and Multi-Objective Optimal Power Flow Problems with Pareto Front Approach: A Case Study of the Iraqi Super Grid High Voltage

by Murtadha Al-Kaabi, Virgil Dumbrava and Mircea Eremia

Energies 2022, 15(20), 7473; https://doi.org/10.3390/en15207473 - 11 Oct 2022

Cited by 22 | Viewed by 2091

Abstract

Optimal power flow (OPF) represents one of the most important issues in the electrical power system for energy management, planning, and operation via finding optimal control variables with satisfying the equality and inequality constraints. Several optimization methods have been proposed to solve OPF problems, but there is still a need to achieve optimum performance. A Slime Mould Algorithm (SMA) is one of the new stochastic optimization methods inspired by the behaviour of the oscillation mode of slime mould in nature. The proposed algorithm is characterized as easy, simple, efficient, avoiding stagnation in the local optima and moving toward the optimal solution. Different frameworks have been applied to achieve single and conflicting multi-objective functions simultaneously (Bi, Tri, Quad, and Quinta objective functions) for solving OPF problems. These objective functions are total fuel cost of generation units, real power loss on transmission lines, total emission issued by fossil-fuelled thermal units, voltage deviation at load bus, and voltage stability index of the whole system. The proposed algorithm SMA has been developed by incorporating it with Pareto concept optimization to generate a new approach, named the Multi-Objective Slime Mould Algorithm (MOSMS), to solve multi-objective optimal power flow (MOOPF) problems. Fuzzy set theory and crowding distance are the proposed strategies to obtain the best compromise solution and rank and reduce a set of non-dominated solutions, respectively. To investigate the performance of the proposed algorithm, two standard IEEE test systems (IEEE 30 bus IEEE 57 bus systems) and a practical system (Iraqi Super Grid High Voltage 400 kV) were tested with 29 case studies based on MATLAB software. The optimal results obtained by the proposed approach (SMA) were compared with other algorithms mentioned in the literature. These results confirm the ability of SMA to provide better solutions to achieve the optimal control variables. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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24 pages, 3526 KiB

Open AccessArticle

A Critical Analysis of Modeling Aspects of D-STATCOMs for Optimal Reactive Power Compensation in Power Distribution Networks

by Subrat Kumar Dash, Sivkumar Mishra and Almoataz Y. Abdelaziz

Energies 2022, 15(19), 6908; https://doi.org/10.3390/en15196908 - 21 Sep 2022

Cited by 6 | Viewed by 1527

Abstract

Distribution static compensators (D-STATCOMs) can enhance the technical performance of the power distribution network by providing rapid and continuous reactive power support to the connected bus. Accurate modeling and efficient utilization of D-STATCOMs can maximize their utility. In this regard, this article offers a novel current-injection-based D-STATCOM model under the power control mode of operation for the reactive power compensation of the power distribution network. The versatility of the proposed D-STATCOM model is demonstrated by combining it with two of the most established distribution load flow techniques, viz., the forward–backward sweep load flow and the BIBC–BCBV-matrix-based direct load flow. Further, the allocation of the proposed D-STATCOM model is carried out under a multiobjective mathematical formulation consisting of various technical and economic indices such as the active power loss reduction index, voltage variation minimization index, voltage stability improvement index and annual expenditure index. A novel parameter-free metaheuristic algorithm, namely a student-psychology-based optimization algorithm, is proposed to determine the optimal assignment of the different number of D-STATCOM units under the multiobjective framework. The proposed allocation scheme is implemented on a standard 33-bus test system and on a practical 51-bus rural distribution feeder. The obtained results demonstrate that the proposed D-STATCOM model can be efficiently integrated into the distribution load flow algorithms. The student-psychology-based optimization algorithm is found to be robust and efficient in solving the optimal allocation of D-STATCOMs as it yields minimum power loss compared to other established approaches for 33-bus PDNs. Further, the economic analysis carried out in this work can guide network operators in deciding on the number of D-STATCOMs to be augmented depending on the investment costs and the resulting savings. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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18 pages, 7056 KiB

Open AccessArticle

Fuzzy Logic Controller Equilibrium Base to Enhance AGC System Performance with Renewable Energy Disturbances

by Soha Mansour, Ahmed O. Badr, Mahmoud A. Attia, Mariam A. Sameh, Hossam Kotb, Elmazeg Elgamli and Mokhtar Shouran

Energies 2022, 15(18), 6709; https://doi.org/10.3390/en15186709 - 14 Sep 2022

Cited by 9 | Viewed by 2128

Abstract

Owing to the various sources of complexity in the electrical power system, such as integrating intermittent renewable energy resources and widely spread nonlinear power system components, which result in sudden changes in the power system operating conditions, the conventional PID controller fails to track such dynamic challenges to mitigate the frequency deviation problem. Thus, in this paper, a fuzzy PI controller is proposed to enhance the automatic generation control system (AGC) against step disturbance, dynamic disturbance, and wind energy disturbance in a single area system. The proposed controller is initialized by using Equilibrium Optimization and proved its superiority through comparison with a classical PI optimized base. Results show that the fuzzy PI controller can reduce the peak-to-peak deviation in the frequency by 30–59% under wind disturbance, compared to a classical PI optimized base. Moreover, a fuzzy PID controller is also proposed and EO initialized in this paper to compare with the PIDA optimized by several techniques in the two-area system. Results show that the fuzzy PID controller can reduce the peak-to-peak deviation in the frequency of area 1 by 30–50% and the deviation of frequency in area 2 by 13–48% under wave disturbance, compared to the classical PIDA optimized base. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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19 pages, 1312 KiB

Open AccessArticle

The Influence of Cooperation on the Operation of an MPC Controller Pair in a Nuclear Power Plant Turbine Generator Set

by Paweł Sokólski, Tomasz A. Rutkowski, Bartosz Ceran, Daria Złotecka and Dariusz Horla

Energies 2022, 15(18), 6702; https://doi.org/10.3390/en15186702 - 13 Sep 2022

Cited by 3 | Viewed by 1258

Abstract

The paper discusses the problem of cooperation between multiple model predictive control (MPC) systems. This approach aims at improving the control quality in electrical energy generation and forms the next step in a series of publications by the authors focusing on the optimization and control of electric power systems. Cooperation and cooperative object concepts in relation to a multi MPC system are defined and a cooperative control solution for a nuclear power plant’s turbine generator set is proposed. The aim of enabling information exchange between the controllers is to improve the performance of power generation. Presented and discussed simulation tests include various variants of information exchange between the turbine and synchronous generator MPC controllers of the nuclear power plant. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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26 pages, 12875 KiB

Open AccessArticle

A New Robust Direct Torque Control Based on a Genetic Algorithm for a Doubly-Fed Induction Motor: Experimental Validation

by Said Mahfoud, Aziz Derouich, Najib El Ouanjli, Mahmoud A. Mossa, Mahajan Sagar Bhaskar, Ngo Kim Lan and Nguyen Vu Quynh

Energies 2022, 15(15), 5384; https://doi.org/10.3390/en15155384 - 26 Jul 2022

Cited by 16 | Viewed by 2409

Abstract

The parametric variation of nonlinear systems remains a significant drawback of automatic system controllers. The Proportional–Integral(PI) and Proportional–Integral–Derivative (PID) are the most commonly used controllers in industrial control systems. However, with the evolution of these systems, such controllers have become insufficient to compete with the complexity of the systems. This problem can be solved with the help of artificial intelligence, and especially with the use of optimization algorithms, which allow for variable gains in PID controllers that adapt to parametric variation. This article presents an analytical and experimental study of the Direct Torque Control (DTC) of a Doubly-Fed Induction Motor (DFIM). The speed adaptation of the DFIM is achieved using a PID controller, which is characterized by overshoots in the speed and ripples in the electromagnetic torque. The Genetic Algorithm (GA) within the DTC shows very good robustness in speed and torque by reducing torque ripples and suppressing overshoots. The simulation of the GA-DTC hybrid control in MATLAB/Simulink confirms the improvement offered by this strategy. The validation and implementation of this strategy on the dSPACE DS1104 board are in good agreement with the simulation results and theoretical analysis. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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22 pages, 6376 KiB

Open AccessArticle

An Adaptive Load Frequency Control for Power Systems with Renewable Energy Sources

by Mohamed Mokhtar, Mostafa I. Marei, Mariam A. Sameh and Mahmoud A. Attia

Energies 2022, 15(2), 573; https://doi.org/10.3390/en15020573 - 13 Jan 2022

Cited by 25 | Viewed by 3583

Abstract

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to demonstrate the superiority of the proposed controller, the dynamic performance is compared with previous work based on an optimized controller in the third case study. Finally in the fourth case study, a sensitivity analysis is carried out through parameters variations in the nonlinear PV-thermal hybrid system. The novel application of the adaptive controller into the LFC leads to enhance the system performance under disturbance of different sources of renewable energy. Moreover, a robustness test is presented to validate the reliability of the proposed controller. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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29 pages, 1137 KiB

Open AccessArticle

Comprehensive Overview of Power System Flexibility during the Scenario of High Penetration of Renewable Energy in Utility Grid

by Ekata Kaushik, Vivek Prakash, Om Prakash Mahela, Baseem Khan, Adel El-Shahat and Almoataz Y. Abdelaziz

Energies 2022, 15(2), 516; https://doi.org/10.3390/en15020516 - 12 Jan 2022

Cited by 43 | Viewed by 5197

Abstract

Increased deployment of variable renewable energy (VRE) has posed significant challenges to ensure reliable power system operations. As VRE penetration increases beyond 80%, the power system will require long duration energy storage and flexibility. Detailed uncertainty analysis, identifying challenges, and opportunities to provide sufficient flexibility will help to achieve smooth operations of power system networks during the scenario of high share of VRE sources. Hence, this paper presents a comprehensive overview of the power system flexibility (PSF). The intention of this review is to provide a wide spectrum of power system flexibility, PSF drivers, PSF resources, PSF provisions, methods used for assessment of flexibility and flexibility planning to the researchers, academicians, power system planners, and engineers working on the integration of VRE into the utility grid to achieve high share of these sources. More than 100 research papers on the basic concepts of PSF, drivers of the PSF, resources of PSF, requirement of the PSF, metrics used for assessment of the flexibility, methods and approaches used for measurement of flexibility level in network of the power system, and methods used for the PSF planning and flexibility provisions have been thoroughly reviewed and classified for quick reference considering different dimensions. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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Review

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32 pages, 15659 KiB

Open AccessReview

A Comprehensive Examination of Vector-Controlled Induction Motor Drive Techniques

by Ahmed G. Mahmoud A. Aziz, Almoataz Y. Abdelaziz, Ziad M. Ali and Ahmed A. Zaki Diab

Energies 2023, 16(6), 2854; https://doi.org/10.3390/en16062854 - 19 Mar 2023

Cited by 14 | Viewed by 4887

Abstract

This paper introduces a comprehensive examination of vector-controlled- (VC-) based techniques intended for induction motor (IM) drives. In addition, the evaluation and critique of modern control techniques that improve the performance of IM drives are discussed by considering a systematic literature survey. Detailed research on variable-speed drive control, for instance, VC and scalar control (SCC), was conducted. The SCC-based systems’ speed and V/f control purposes are clarified in closed and open loops of IM drives. The operations, benefits, and drawbacks of the direct and indirect field-oriented control systems are illustrated. Furthermore, the direct torque control (DTC) method for IMs is reviewed. Numerous VC methods established along with microprocessor/digital control, model reference adaptive control (MRAC), sliding mode control (SMC), and intelligent control (in terms of fuzzy logic (FL) and artificial neural networks (ANNs)) are described and examined. Uncertainties in the IM parameter are a considerable problem in VC drives. Therefore, this problem is addressed, and some studies that attempted to provide solutions are listed. Magnetic saturation and core loss impact are mentioned, as they are important issues in IM drives. Toward demonstrating the strengths and limitations of various VC configurations, a few experiments were simulated via MATLAB^® and Simulink^® that show the influence of machine parameter variation. Efforts are made to supply powerful guidelines for practicing engineers and researchers in AC drives. Full article

(This article belongs to the Special Issue Optimal Power Flow: Optimization and Control of Electric Power Systems)

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