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Optimal Control and Nonlinear Dynamics in Electrical Power Systems

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

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 26735

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Prof. Dr. Victor M. Becerra

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School of Engineering, University of Portsmouth, Anglesea Building, Anglesea Road, Portsmouth, PO1 3DJ, UK
Interests: computational optimal control; nonlinear control; fault diagnosis; fault-tolerant control; autonomous control systems; state estimation; smart grids; solar energy; control of power systems; control of energy storage
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Dear Colleagues,

The electrical power system is going through a revolution. Advances in telecommunications, computer hardware and software, measurement and metering systems, power electronics, along with the increasing integration of intermittent renewable energy sources and the drive for energy efficiency, have resulted in an evolution of the traditional power systems towards a smarter grid, which is characterised in part by a bi-directional flow of power and information. This evolution has created new opportunities for optimising the control and performance of the power grid, as well as new challenges associated with the complexity its dynamic behaviour.

Power systems are characterized by nonlinear dynamics, as many of its components exhibit nonlinear behaviour, and the resulting interconnected system thus presents a rich set nonlinear phenomena, including for instance, nonlinear oscillations, instabilities, bifurcations, and chaos. The behaviour of electrical power systems is becoming increasingly complex because of a greater level of interconnection, higher power system loading, and the deployment of high-speed power electronic devices, among other factors. Fortunately, many powerful and rigorous techniques have been proposed to control and analyse the behaviour of complex nonlinear systems.

Optimal control is the process of finding trajectories of key variables for a dynamic system over a period of time, so that the performance of the system is optimal in some given sense. The index which is used to quantify the performance of the system might include, for example, a measure of the control effort, a measure of energy consumption, or any other quantity of importance to the operation of the system. Optimal control can be applied off-line when planning the operation of the system, but it can also be used on-line by means of model predictive control strategies.

Energies is pleased to invite prospective authors to submit original research submissions covering innovations associated with the use of optimal control and nonlinear dynamics in electrical power systems. Topics of interest include, but are not limited to:

Nonlinear dynamics, bifurcations, and chaos in electrical power systems;
Lyapunov stability analysis of power systems, including the design of stable nonlinear controllers;
Nonlinear optimal control approaches for microgrids, energy storage, and the integration of renewable energy systems into the power grid;
Nonlinear control approaches in power systems, including for instance, backstepping, sliding mode control, adaptive control, nonlinear predictive control, fault tolerant control, and feedback linearization;
Nonlinear state estimation for power grids and smart grids;
Game theoretic approaches for the smart grid.

Prof. Victor Becerra
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

optimal control
nonlinear dynamics
stability analysis
nonlinear control methods
nonlinear state estimation
power systems
smart grids
microgrids
energy storage
intermittent renewable energy

Published Papers (9 papers)

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Research

31 pages, 4358 KiB

Open AccessArticle

Analysis of Transient Interactions between a PWR Nuclear Power Plant and a Faulted Electricity Grid

by Vineet Vajpayee, Elif Top and Victor M. Becerra

Energies 2021, 14(6), 1573; https://doi.org/10.3390/en14061573 - 12 Mar 2021

Cited by 8 | Viewed by 1990

Abstract

This paper presents the transient stability analysis of a pressurised water-type nuclear power plant following faults and disturbances affecting the electricity grid to which it is connected. The modelled nuclear plant consists of various integrated subsystems, such as core neutronics and thermal-hydraulics, piping and plenum, pressuriser, steam generator, turbine, governor, and dynamics shaft, in addition to the turbine-speed controller. The nonlinear nuclear power plant model is linearised at the operating point to acquire a linear model for controller design. The turbine-speed control loop effectively enacts a closed-loop implementation of the nuclear power plant connected to the electric grid. The various transient stability enhancement components such as the power system stabiliser, static var compensator, and static synchronous compensator are employed to test performance during severe contingencies. The interaction between the nuclear power plant, electric grid, and protection system is studied under various scenarios such as single-phase fault, three-phase fault, and permanent load loss. The performance of the nonlinear plant is further observed during load-following operation. The dynamic behaviour of the overall system is analysed using simulations in the MATLAB/Simulink/Simscape environment. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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21 pages, 6242 KiB

Open AccessArticle

Adaptive Higher-Order Sliding Mode Control of Series-Compensated DFIG-Based Wind Farm for Sub-Synchronous Control Interaction Mitigation

by Yaozhen Han, Shuzhen Li and Cuiqi Du

Energies 2020, 13(20), 5421; https://doi.org/10.3390/en13205421 - 16 Oct 2020

Cited by 5 | Viewed by 1696

Abstract

Sub-synchronous control interaction (SSCI) is an oscillation phenomenon caused by the interaction of converter control and series-compensated transmission line. This paper proposes a novel adaptive higher-order sliding mode (AHOSM) control strategy for damping the SSCI of a series-compensated DFIG-based wind power system. On the basis of system modeling and oscillation mechanism analysis, SSCI suppression is converted to the current tracking control problem. Firstly, an auxiliary feedback control is employed for the nonlinear series-compensated system, then integral sliding mode functions are defined to design a second-order sliding mode control law for the equivalent system. Adaptive laws for the control gains are then conceived based on the Lyapunov function considering unknown upper bounds of uncertainty derivatives. System stability is also analyzed in detail along with adaptive laws’ design. The effectiveness of the proposed control scheme is verified under different series-compensated level, different wind speed, symmetric and asymmetric short circuit fault, and internal and external disturbances. The PI control and conventional first-order sliding mode control scheme are also executed to compare the damping effect. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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23 pages, 2018 KiB

Open AccessArticle

Estimation of Radioactivity Release Activity Using Non-Linear Kalman Filter-Based Estimation Techniques

by Victor M. Becerra, Vineet Vajpayee, Nils Bausch, T.V. Santhosh, Gopika Vinod and Jiamei Deng

Energies 2020, 13(15), 3985; https://doi.org/10.3390/en13153985 - 02 Aug 2020

Cited by 3 | Viewed by 2340

Abstract

The estimation of radioactivity release following an accident in a nuclear power plant is crucial due to its short and long-term impacts on the surrounding population and the environment. In the case of any accidental release, the activity needs to be estimated quickly and reliably to effectively plan a rapid emergency response and design an appropriate evacuation strategy. The accurate prediction of incurred dose rate during normal or accident scenario is another important aspect. In this article, three different non-linear estimation techniques, extended Kalman filter, unscented Kalman filter, and cubature Kalman filter are proposed in order to estimate release activity and to improve the prediction of dose rates. Radionuclide release rate, average wind speed, and height of release are estimated using the dose rate monitors data collected in proximity of the release point. Further, the estimates are employed to improve the prediction of dose rates. The atmospheric dispersion phenomenon of radioactivity release is modelled using the Gaussian plume model. The Gaussian plume model is then employed for the calculation of dose rates. A variety of atmospheric and accident related scenarios for single source and multiple sources are studied in order to assess the efficacy of the proposed filters. Statistical measures have been used in order to validate the performance of the proposed approaches. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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46 pages, 6867 KiB

Open AccessArticle

Optimal Power Flow Management System for a Power Network with Stochastic Renewable Energy Resources Using Golden Ratio Optimization Method

by Khaled Nusair and Feras Alasali

Energies 2020, 13(14), 3671; https://doi.org/10.3390/en13143671 - 16 Jul 2020

Cited by 41 | Viewed by 3396

Abstract

An optimal operation system is a potential solution to increase the energy efficiency of a power network equipped with stochastic Renewable Energy Sources (RES). In this article, an Optimal Power Flow (OPF) problem has been formulated as a single and multi-objective problems for a conventional power generation and renewable sources connected to a power network. The objective functions reflect the minimization of fuel cost, gas emission, power loss, voltage deviation and improving the system stability. Considering the volatile renewable generation behaviour and uncertainty in the power prediction of wind and solar power output as a nonlinear optimization problem, this paper uses a Weibull and lognormal probability distribution functions to estimate the power output of renewable generation. Then, a new Golden Ratio Optimization Method (GROM) algorithm has been developed to solve the OPF problem for a power network incorporating with stochastic RES. The proposed GROM algorithm aims to improve the reliability, environmental and energy performance of the power network system (IEEE 30-bus system). Three different scenarios, using different RES locations, are presented and the results of the proposed GROM algorithm is compared to six heuristic search methods from the literature. The comparisons indicate that the GROM algorithm successfully reduce fuel costs, gas emission and improve the voltage stability and outperforms each of the presented six heuristic search methods. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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19 pages, 2437 KiB

Open AccessArticle

A Comparative Study of Optimal Energy Management Strategies for Energy Storage with Stochastic Loads

by Feras Alasali, Stephen Haben, Husam Foudeh and William Holderbaum

Energies 2020, 13(10), 2596; https://doi.org/10.3390/en13102596 - 20 May 2020

Cited by 7 | Viewed by 2052

Abstract

This paper aims to present the significance of predicting stochastic loads to improve the performance of a low voltage (LV) network with an energy storage system (ESS) by employing several optimal energy controllers. Considering the highly stochastic behaviour that rubber tyre gantry (RTG) cranes demand, this study develops and compares optimal energy controllers based on a model predictive controller (MPC) with a rolling point forecast model and a stochastic model predictive controller (SMPC) based on a stochastic prediction demand model as potentially suitable approaches to minimise the impact of the demand uncertainty. The proposed MPC and SMPC control models are compared to an optimal energy controller with perfect and fixed load forecast profiles and a standard set-point controller. The results show that the optimal controllers, which utilise a load forecast, improve peak reduction and cost savings of the storage device compared to the traditional control algorithm. Further improvements are presented for the receding horizon controllers, MPC and SMPC, which better handle the volatility of the crane demand. Furthermore, a computational cost analysis for optimal controllers is presented to evaluate the complexity for a practical implementation of the predictive optimal control systems. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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12 pages, 3218 KiB

Open AccessArticle

Finite Element and Experimental Analysis of an Axisymmetric Electromechanical Converter with a Magnetostrictive Rod

by Dorota Stachowiak and Andrzej Demenko

Energies 2020, 13(5), 1230; https://doi.org/10.3390/en13051230 - 06 Mar 2020

Cited by 11 | Viewed by 2482

Abstract

The paper presents the numerical and experimental investigations of the axisymmetric magnetostrictive actuator with a Terfenol-D rod. The applied model consists of equations that describe the magnetic and mechanical displacement fields. The equations of both fields are coupled through a nonlinear magneto-mechanical constitutive law. The model is considered as 2D axisymmetric. The finite element method is used to solve the field equations. Special attention is paid to the proper definition of magneto-mechanical relations. These relations are formed from measurements. A unique test stand is designed for the experimental investigation. The selected results of the simulation are compared with the measurement results. The comparison shows that the applied numerical model is sufficiently accurate. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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28 pages, 9916 KiB

Open AccessArticle

Direct Voltage Control of a Doubly Fed Induction Generator by Means of Optimal Strategy

by Arthur Medeiros, Thales Ramos, José Tavares de Oliveira and Manoel F. Medeiros Júnior

Energies 2020, 13(3), 770; https://doi.org/10.3390/en13030770 - 10 Feb 2020

Cited by 5 | Viewed by 2651

Abstract

The major objective of the investigation reported in this article is to demonstrate the feasibility of controlling a Doubly Fed Induction Generator actuating directly on the rotor voltage produced by the Rotor Side Converter, as its reference value may be determined analytically, after definition of the control objective. Two usual objectives are here considered: maximum power extraction from wind (MPPT) and stator reactive power equal to zero. This last objective defines the reference slip to be considered in the formulation of developed power that, jointly with the reactive power equation, forms the system to calculate the rotor reference voltages. The process is completed by specifying the desired dynamical response. Thus, the angular velocity of the rotor should quickly reach its reference value, which requires maximal power acceleration at the beginning, but respects the restriction that no overshoot should be allowed. This is achieved by means of a constrained optimization process solved in real time. Following recent trends, only measurements obtained from stator (voltages and currents) sensors are used. This way, angular velocity and rotor currents are estimated in real time. An algorithm for inductance estimation is also included, which prevents deviations of nominal values that could lead to false reference voltages. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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27 pages, 5516 KiB

Open AccessArticle

Demand Response Model Development for Smart Households Using Time of Use Tariffs and Optimal Control—The Isle of Wight Energy Autonomous Community Case Study

by Sourav Khanna, Victor Becerra, Adib Allahham, Damian Giaouris, Jamie M. Foster, Keiron Roberts, David Hutchinson and Jim Fawcett

Energies 2020, 13(3), 541; https://doi.org/10.3390/en13030541 - 22 Jan 2020

Cited by 10 | Viewed by 5218

Abstract

Residential variable energy price schemes can be made more effective with the use of a demand response (DR) strategy along with smart appliances. Using DR, the electricity bill of participating customers/households can be minimised, while pursuing other aims such as demand-shifting and maximising consumption of locally generated renewable-electricity. In this article, a two-stage optimization method is used to implement a price-based implicit DR scheme. The model considers a range of novel smart devices/technologies/schemes, connected to smart-meters and a local DR-Controller. A case study with various decarbonisation scenarios is used to analyse the effects of deploying the proposed DR-scheme in households located in the west area of the Isle of Wight (Southern United Kingdom). There are approximately 15,000 households, of which 3000 are not connected to the gas-network. Using a distribution network model along with a load flow software-tool, the secondary voltages and apparent-power through transformers at the relevant substations are computed. The results show that in summer, participating households could export up to 6.4 MW of power, which is 10% of installed large-scale photovoltaics (PV) capacity on the island. Average carbon dioxide equivalent (CO₂e) reductions of 7.1 ktons/annum and a reduction in combined energy/transport fuel-bills of 60%/annum could be achieved by participating households. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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16 pages, 4295 KiB

Open AccessFeature PaperArticle

Techno-Economic Analysis of a Residential PV-Storage Model in a Distribution Network

by Lue Xiong and Mutasim Nour

Energies 2019, 12(16), 3062; https://doi.org/10.3390/en12163062 - 08 Aug 2019

Cited by 17 | Viewed by 3585

Abstract

The high penetration level of photovoltaic (PV) generation in distribution networks not only brings benefits like carbon savings, but also induces undesirable outcomes, like more harmonic components and voltage fluctuations. Driven by decreasing costs of energy storage, the focus of this paper is to investigate the feasibility of applying energy storage in the grid-connected PV system to mitigate its intermittency. Firstly, to appreciate the functionality of storage, a generic PV-battery-supercapacitor model was simulated in MATLAB/Simulink, and a flat load profile was obtained to enhance predictability from the network management point of view. However, the usage of supercapacitors at the residential level is limited, due to its high startup costs. Secondly, a detailed residential PV-battery model was implemented in the System Advisor Model (SAM) based on local data in Dubai. The optimal sizing of a battery system was determined by assessing two criteria: The number of excursions, and average target power, which are contradictory in optimization process. Statistical indicators show that a properly sized battery system can alleviate network fluctuations. The proposed sizing method can be also applied to other PV-storage systems. Finally, economic studies of PV-battery system demonstrated its competitiveness against standalone PV systems under appropriate tariff incentives. Full article

(This article belongs to the Special Issue Optimal Control and Nonlinear Dynamics in Electrical Power Systems)

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