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Automation, Control and Energy Efficiency in Complex 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 (30 December 2019) | Viewed by 54332

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Dr. Hamid Khayyam

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Department of Mechanical and Automotive Engineering, School of Engineering, RMIT University, Melbourne, VIC 3083, Australia
Interests: artificial intelligence; machine learning and adaptive intelligent systems; limited and big data modelling; Industry 4.0 and Education 4.0
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Special Issue Information

Dear Colleagues,

Each year, around the world, a massive amount of energy is wasted through inefficient technologies, leading to an increase in greenhouse gas emissions.

Energy efficiency is an effective approach to improve energy consumption, as well reducing energy costs for consumers.

It is well established that engineering systems are often complex, uncertain, and nonlinear. These complex systems are in great need of computation and their processing has led to the use of automation control. As such, the energy efficiency of complex systems is of great importance and is the topic of discussion for this Special Issue.

The Special Issue aims to be a leading peer-reviewed platform and surveys the state-of-the-art and modern automation control techniques, and optimization algorithms, which are deployed to achieve complex energy efficiency. The Special Issue covers research on energy analysis, energy modelling and prediction, integrated energy systems, energy planning, and energy management to improve energy efficiency. In addition, papers are welcome on other related topics, such as renewable energy, electricity supply and demand, bioenergy, robot, vehicle, energy storage, energy conservation, energy in buildings, industrial and residential within the context of the broader automation control and energy efficiency.

Dr. Hamid Khayyam
Guest Editor

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Keywords

Modern energy efficiency techniques
Vehicle/Robot energy efficiency
Intelligent control of energy systems
Big\limited data modelling of complex energy system
Process optimization
Energy storage, conservation, buildings, industrial and residential

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Published Papers (11 papers)

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Research

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14 pages, 1058 KiB

Open AccessArticle

Distributed Event-Based Control of Hierarchical Leader-Follower Networks with Time-Varying Layer-To-Layer Delays

by Guang-Hui Xu, Meng Xu, Ming-Feng Ge, Teng-Fei Ding, Feng Qi and Meng Li

Energies 2020, 13(7), 1808; https://doi.org/10.3390/en13071808 - 9 Apr 2020

Cited by 7 | Viewed by 2102

Abstract

Compared with the traditional multi-agent models, the hierarchical leader–follower network (HLFN) can describe some real-world multi-agent systems more precisely due to its layered properties. The distributed event-based consensus control problem of HLFNs with layer-to-layer delays, namely, communication delays among agents of different layers, is presented in this essay. In order to solve the aforementioned problem, several innovative hierarchical event-based control (HEC) algorithms are proposed. The sufficient conditions on the control parameters and event-triggered mechanism were derived to undertake the reliability of the closed-loop dynamics. Moreover, it is shown that the zeno-behaviors of the presented HEC algorithms can be excluded. Finally, there are some numerical examples that verify the availability of the results. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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21 pages, 2335 KiB

Open AccessArticle

An Optimal Air-Conditioner On-Off Control Scheme under Extremely Hot Weather Conditions

by Mohammed Al-Azba, Zhaohui Cen, Yves Remond and Said Ahzi

Energies 2020, 13(5), 1021; https://doi.org/10.3390/en13051021 - 25 Feb 2020

Cited by 24 | Viewed by 4020

Abstract

Being reliant on Air Conditioning (AC) throughout the majority of the year, desert countries with extremely hot weather conditions such as Qatar are facing challenges in lowering weariness cost due to AC On-Off switching while maintaining an adequate level of comfort under a wide-range of ambient temperature variations. To address these challenges, this paper investigates an optimal On-Off control strategy to improve the AC utilization process. To overcome complexities of online optimization, a Elman Neural Networks (NN)-based estimator is proposed to estimate real values of the outdoor temperature, and make off-line optimization available. By looking up the optimum values solved from an off-line optimization scheme, the proposed control solutions can adaptively regulate the indoor temperature regardless of outdoor temperature variations. In addition, a cost function of multiple objectives, which consider both Coefficient of Performance (COP), and AC compressor weariness due to On-Off switching, is designed for the optimization target of minimum cost. Unlike conventional On-Off control methodologies, the proposed On-Off control technique can respond adaptively to match large-range (up to 20

^{\circ}

C) ambient temperature variations while overcoming the drawbacks of long-time online optimization due to heavy computational load. Finally, the Elman NN based outdoor temperature estimator is validated with an acceptable accuracy and various validations for AC control optimization under Qatar’s real outdoor temperature conditions, which include three hot seasons, are conducted and analyzed. The results demonstrate the effectiveness and robustness of the proposed optimal On-Off control solution. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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25 pages, 7468 KiB

Open AccessArticle

Energy-Efficient Driving Strategies for Multi-Train by Optimization and Update Speed Profiles Considering Transmission Losses of Regenerative Energy

by Mo Chen, Zhuang Xiao, Pengfei Sun, Qingyuan Wang, Bo Jin and Xiaoyun Feng

Energies 2019, 12(18), 3573; https://doi.org/10.3390/en12183573 - 18 Sep 2019

Cited by 9 | Viewed by 2942

Abstract

This paper aims at minimizing the total energy consumption of multi-train in an urban rail transit (URT) system by optimizing and updating speed profiles considering regenerative braking power losses on the catenary. To make full use of regenerative energy and decrease traction energy consumption simultaneously, energy-efficient control strategies of multi-train and a corresponding solution method are proposed. The running process of multi-train is divided into several sections based on passenger stations. Speed profiles of each train in each section are collaboratively optimized by searching only one transition point from the optimized single-train speed profile, which can be worked out by searching the switching point of coasting mode, and the optimized multi-train speed profiles are updated based on departure orders of trains. Moreover, an electrical network model is established to analyze energy flows, and dynamic losses of recovered regenerative energy on the line can be calculated. Besides, an improved optimization strategy of multi-train, which contains seven motion phases, is presented for steep slope. Simulation results based on Guangzhou Metro Line 8 verify the effectiveness of the proposed methods. Total energy consumption of optimized multi-train can be decreased by 6.95% compared with multi-train adopted single-train optimal control strategy, and the energy-saving rate of 21.08% can be achieved compared with the measured data by drivers under same trip time. In addition, the influence of departure interval on total energy consumption is analyzed and the optimal departure interval can be obtained. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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32 pages, 5885 KiB

Open AccessArticle

Designing Intelligent MIMO Nonlinear Controller Based on Fuzzy Cognitive Map Method for Energy Reduction of the Buildings

by Farinaz Behrooz, Rubiyah Yusof, Norman Mariun, Uswah Khairuddin and Zool Hilmi Ismail

Energies 2019, 12(14), 2713; https://doi.org/10.3390/en12142713 - 16 Jul 2019

Cited by 12 | Viewed by 2823

Abstract

Designing a suitable controller for air-conditioning systems to reduce energy consumption and simultaneously meet the requirements of the system is very challenging. Important factors such as stability and performance of the designed controllers should be investigated to ensure the effectiveness of these controllers. In this article, the stability and performance of the fuzzy cognitive map (FCM) controller are investigated. The FCM method is used to control the direct expansion air conditioning system (DX A/C). The FCM controller has the ability to do online learning, and can achieve fast convergence thanks to its simple mathematical computation. The stability analysis of the controller was conducted using both fuzzy bidirectional associative memories (FBAMs) and the Lyapunov function. The performances of the controller were tested based on its ability for reference tracking and disturbance rejection. On the basis of the stability analysis using FBAMS and Lyapunov functions, the system is globally stable. The controller is able to track the set point faithfully, maintaining the temperature and humidity at the desired value. In order to simulate the disturbances, heat and moisture load changed to measure the ability of the controller to reject the disturbance. The results showed that the proposed controller can track the set point and has a good ability for disturbance rejection, making it an effective controller to be employed in the DX A/C system and suitable for a nonlinear robust control system. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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20 pages, 4369 KiB

Open AccessArticle

Controllability Evaluation of EV Charging Infrastructure Transformed from Gas Stations in Distribution Networks with Renewables

by Shuang Gao, Jianzhong Wu and Bin Xu

Energies 2019, 12(8), 1577; https://doi.org/10.3390/en12081577 - 25 Apr 2019

Cited by 2 | Viewed by 3497

Abstract

A considerable market share of electric vehicles (EVs) is expected in the near future, which leads to a transformation from gas stations to EV charging infrastructure for automobiles. EV charging stations will be integrated with the power grid to replace the fuel consumption at the gas stations for the same mobile needs. In order to evaluate the impact on distribution networks and the controllability of the charging load, the temporal and spatial distribution of the charging power is calculated by establishing mapping the relation between gas stations and charging facilities. Firstly, the arrival and parking period is quantified by applying queuing theory and defining membership function between EVs to parking lots. Secondly, the operational model of charging stations connected to the power distribution network is formulated, and the control variables and their boundaries are identified. Thirdly, an optimal control algorithm is proposed, which combines the configuration of charging stations and charging power regulation during the parking period of each individual EV. A two-stage hybrid optimization algorithm is developed to solve the reliability constrained optimal dispatch problem for EVs, with an EV aggregator installed at each charging station. Simulation results validate the proposed method in evaluating the controllability of EV charging infrastructure and the synergy effects between EV and renewable integration. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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14 pages, 3985 KiB

Open AccessArticle

Hierarchical Control of Nonlinear Active Four-Wheel-Steering Vehicles

by Jie Tian, Jie Ding, Yongpeng Tai and Ning Chen

Energies 2018, 11(11), 2930; https://doi.org/10.3390/en11112930 - 26 Oct 2018

Cited by 14 | Viewed by 2899

Abstract

A new type of hierarchical control is proposed for a four-wheel-steering (4WS) vehicle, in which both the sideslip angle and yaw rate feedback are used, and the saturation of the control variables (i.e., the front and rear steering angles) is considered. The nonlinear three degrees of freedom (3DOF) 4WS vehicle model is employed to describe the uncertainties originating from the operating situations. Further, a normal front-wheel-steering (2WS) vehicle with a drop filter of the sideslip angle is selected as the reference model. The inputs for the rear and front steering angles of the linear 2DOF 4WS, required to achieve the performances described by the reference model, are obtained and controlled by the upper controller. Further, the lower controller is designed to eliminate the state error between the linear 2DOF and nonlinear 3DOF 4WS vehicle models. The simulation results of several vehicle models with/without the controller are presented, and the robustness of the hierarchical control system is analyzed. The simulation results indicate that using the proposed hierarchical controller yields the same performance between the nonlinear 4WS vehicle and the reference model, in addition to exhibiting good robustness. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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18 pages, 2196 KiB

Open AccessArticle

Differential Steering Control of Four-Wheel Independent-Drive Electric Vehicles

by Jie Tian, Jun Tong and Shi Luo

Energies 2018, 11(11), 2892; https://doi.org/10.3390/en11112892 - 24 Oct 2018

Cited by 43 | Viewed by 7340

Abstract

This paper investigates the skid steering of four-wheel independent-drive (4WID) electric vehicles (EV) and a differential steering of a 4WID EV with a steer-by-wire (SBW) system in case of steering failure. The dynamic models of skid steering vehicle (SSV) and differential steering vehicle (DSV) are established and the traditional front-wheel steering vehicle with neutral steering characteristics is selected as the reference model. On this basis, sideslip angle observer and two different sliding mode variable structure controllers for SSV and DSV are designed respectively. Co-simulation results of CarSim and Simulink show that the designed controller for DSV not only controls the yaw rate and sideslip angle of DSV to track those of the reference model exactly, but also ensures the robustness of the controlled system compared with the designed controller for SSV. And the differential driving torque needed to realize the differential steering is much smaller than that for skid steering, which indicates the possibility of the differential steering in case of steering failure. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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18 pages, 6643 KiB

Open AccessArticle

Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

by Aniela Kaminska and Andrzej Ożadowicz

Energies 2018, 11(8), 2166; https://doi.org/10.3390/en11082166 - 19 Aug 2018

Cited by 46 | Viewed by 8216

Abstract

Energy used for lighting is one of the major components of total energy consumption in buildings. Nowadays, buildings have a great potential to reduce their energy consumption, but to achieve this purpose additional efforts are indispensable. In this study, the need for energy savings evaluation before the implementation of lighting control algorithms for a specified building is highlighted. Therefore, experimental tests have been carried out in a university building with laboratories and other rooms, equipped with KNX building automation system. A dimmable control strategy has been investigated, dependent on daylight illuminance. Moreover, a relationship between external and internal daylight illuminance levels has been evaluated as well. Based on the experimental results, the authors proposed a method for the rough estimation of electrical energy savings. Since, according to the EN 15232 standard, Building Automation and Control Systems (BACS) play an important role in buildings’ energy efficiency improvements, the BACS efficiency factors from this standard have been used to verify the experimental results presented in the paper. The potential to reduce energy consumption from lighting in non-residential buildings by 28% for offices and 24% for educational buildings has been confirmed, but its dependence on specific building parameters has been discussed as well. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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26 pages, 11949 KiB

Open AccessArticle

An Adaptive-Equivalent Consumption Minimum Strategy for an Extended-Range Electric Bus Based on Target Driving Cycle Generation

by Hongwei Liu, Chantong Wang, Xin Zhao and Chong Guo

Energies 2018, 11(7), 1805; https://doi.org/10.3390/en11071805 - 10 Jul 2018

Cited by 26 | Viewed by 3269

Abstract

Energy management strategies based on instantaneous optimization have been widely used in hybrid/plug-in hybrid electric vehicles (HEV/PHEV) in order to improve fuel economy while guaranteeing vehicle performance. In this study, an adaptive-equivalent consumption minimum strategy (A-ECMS) based on target driving cycle (TDC) generation was proposed for an extended-range electric bus (E-REB) operating on fixed routes. Firstly, a Hamilton function and a co-state equation for E-REB were determined according to the Pontryagin Minimum Principle (PMP). Then a series of TDCs were generated using Markov chain, and the optimal solutions under different initial state of charges (SOCs) were obtained using the PMP algorithm, forming the optimal initial co-state map. Thirdly, an adaptive co-state function consisting of fixed and dynamic terms was designed. The co-state map was interpolated using the initial SOC data and the vehicle driving data obtained by an Intelligent Transport System, and thereby the initial co-state values were solved and used as the fixed term. A segmented SOC reference curve was put forward according to the optimal SOC changing curves under different initial SOCs solved by using PMP. The dynamic term was determined using a PI controlling method and by real-time adjusting the co-states to follow the reference curve. Finally with the generated TDCs, the control effect of A-ECMS was compared with PMP and Constant-ECMS, which was showed A-ECMS provided the final SOC closer to the pre-set value and fully used the power of the batteries. The oil consumption solutions were close to the PMP optimized results and thereby the oil depletion was reduced. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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10 pages, 2569 KiB

Open AccessArticle

A Pathway to Reduce Energy Consumption in the Thermal Stabilization Process of Carbon Fiber Production

by Srinivas Nunna, Maxime Maghe, Seyed Mousa Fakhrhoseini, Bhargav Polisetti and Minoo Naebe

Energies 2018, 11(5), 1145; https://doi.org/10.3390/en11051145 - 4 May 2018

Cited by 15 | Viewed by 4740

Abstract

Process parameters, especially in the thermal stabilization of polyacrylonitrile (PAN) fibers, play a critical role in controlling the cost and properties of the resultant carbon fibers. This study aimed to efficiently handle the energy expense areas during carbon fiber manufacturing without reducing the quality of carbon fibers. We introduced a new parameter (recirculation fan frequency) in the stabilization stage and studied its influence on the evolution of the structure and properties of fibers. Initially, the progress of the cyclization reaction in the fiber cross-sections with respect to fan frequencies (35, 45, and 60 Hz) during stabilization was analyzed using the Australian Synchrotron-high resolution infrared imaging technique. A parabolic trend in the evolution of cyclic structures was observed in the fiber cross-sections during the initial stages of stabilization; however, it was transformed to a uniform trend at the end of stabilization for all fan frequencies. Simultaneously, the microstructure and property variations at each stage of manufacturing were assessed. We identified nominal structural variations with respect to fan frequencies in the intermediate stages of thermal stabilization, which were reduced during the carbonization process. No statistically significant variations were observed between the tensile properties of fibers. These observations suggested that, when using a lower fan frequency (35 Hz), it was possible to manufacture carbon fibers with a similar performance to those produced using a higher fan frequency (60 Hz). As a result, this study provided an opportunity to reduce the energy consumption during carbon fiber manufacturing. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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Review

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27 pages, 2680 KiB

Open AccessReview

Robust Speed Control of PMSM Using Sliding Mode Control (SMC)—A Review

by Fardila Mohd Zaihidee, Saad Mekhilef and Marizan Mubin

Energies 2019, 12(9), 1669; https://doi.org/10.3390/en12091669 - 1 May 2019

Cited by 165 | Viewed by 11389

Abstract

Permanent magnet synchronous motors (PMSMs) are known as highly efficient motors and are slowly replacing induction motors in diverse industries. PMSM systems are nonlinear and consist of time-varying parameters with high-order complex dynamics. High performance applications of PMSMs require their speed controllers to provide a fast response, precise tracking, small overshoot and strong disturbance rejection ability. Sliding mode control (SMC) is well known as a robust control method for systems with parameter variations and external disturbances. This paper investigates the current status of implementation of sliding mode control speed control of PMSMs. Our aim is to highlight various designs of sliding surface and composite controller designs with SMC implementation, which purpose is to improve controller’s robustness and/or to reduce SMC chattering. SMC enhancement using fractional order sliding surface design is elaborated and verified by simulation results presented. Remarkable features as well as disadvantages of previous works are summarized. Ideas on possible future works are also discussed, which emphasize on current gaps in this area of research. Full article

(This article belongs to the Special Issue Automation, Control and Energy Efficiency in Complex Systems)

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