This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Power management and power flow control with back-to-back converters in a utility connected microgrid

Optimal operation of energy hubs integrated with renewable energy sources and storage devices considering CO2 emissions

Hybrid-cloud-based data processing for power system monitoring in smart grids

Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer

The purpose of this paper is to determine the relationship between total productive maintenance (TPM), kaizen event (KE) and innovation performance (IP) for Malaysian automotive industry using structural equation modeling (SEM).,The samples were selected from the list of Proton and Perodua automotive industry. The number of collected respondents was 238 respondents. An SEM technique was used in the study. In order to test the reliability and validity of the instrument, reliability analysis, exploratory and confirmatory factor analysis were conducted.,Based on the results, KE does not affect the relationship between TPM and IP. However, the impact of TPM on IP increases with mediating of KE for Malaysian automotive industry. Thus, this study has shown that empirical test results prove that the implementation of TPM and KE has improved the IP for Malaysian automotive industry.,This study only focused on the Malaysian automotive industry. The other limitation in this research is the number of factors and limited measurement in this study. Only a few TPM, KE and IP measurements were considered. By using the SEM technique, four TPM constructs, three for KE constructs and three for IP measures were developed and verified. Therefore, this study can assist the researchers and practitioners to the practice of TPM, KE and IP for Malaysian automotive industry.,This research provides fundamental knowledge and direction for researchers in further research as well as practitioners to constantly improve IP through the implementation of TPM and KE for Malaysian automotive industry.

Total productive maintenance, kaizen event, and performance

Hydro-thermal-wind generation scheduling (HTWGS) with economic and environmental factors is a multi-objective complex nonlinear power system optimization problem with many equality and inequality constraints. The objective of the problem is to generate an hour-by-hour optimum schedule of hydro-thermal-wind power plants to attain the least emission of pollutants from thermal plants and a reduced generation cost of thermal and wind plants for a 24-h period, satisfying the system constraints. The paper presents a detailed framework of the HTWGS problem and proposes a modified particle swarm optimization (MPSO) algorithm for evolving a solution. The competency of selected heuristic algorithms, representing different heuristic groups, viz. the binary coded genetic algorithm (BCGA), particle swarm optimization (PSO), improved harmony search (IHS), and JAYA algorithm, for searching for an optimal solution to HTWGS considering economic and environmental factors was investigated in a trial system consisting of a multi-stream cascaded system with four reservoirs, three thermal plants, and two wind plants. Appropriate mathematical models were used for representing the water discharge, generation cost, and pollutant emission of respective power plants incorporated in the system. Statistical analysis was performed to check the consistency and reliability of the proposed algorithm. The simulation results indicated that the proposed MPSO algorithm provided a better solution to the problem of HTWGS, with a reduced generation cost and the least emission, when compared with the other heuristic algorithms considered.

https://www.mdpi.com/1996-1073/11/2/353/pdf

Hydro-Thermal-Wind Generation Scheduling Considering Economic and Environmental Factors Using Heuristic Algorithms

Congestion management in restructured power systems for smart cities in India

The brief deals with a new algorithm for designing Proportional-Integral (PI) and Proportional-Integral Derivative (PID) Controllers for system with parametric uncertainty. The parameters of the controller are obtained by the frequency response matching of the actual and the desired closed-loop characteristics at two different frequency points. The desired closed-loop reference model can be chosen from the design requirements and the process dynamics. The method gives two set of linear algebraic equations, solution of which gives the controller parameters. The proposed method is also used for controller design of parametric uncertain system with dead time. The technique is demonstrated with two numerical examples and a good set-point response is achieved. Simulation results are obtained using MATLAB software.

PI, PID controller design for interval systems using frequency response model matching technique

The paper presents the design and implementation of a PID control based trajectory tracking of a nonholonomic wheeled mobile robot (WMR) with the objective of matching desired time domain specification and specified interaction. The desired time domain specification of output Y(s) is represented as a step response of a second order system with designer specific desired damping ratio (ζ) and natural frequency (ωn). The problem of finding the unknown parameters of PID controllers is formulated in a genetic algorithm (GA) based optimization frame in which the objective is to minimize the difference between the response of the designed closed-loop system and that of the desired closed-loop system. This procedure has been illustrated for achieving the desired time domain specification for WMR, taking different settling time of output response. The interaction analyses are carried out using the concept of Relative Gain Array (RGA). The RGA for both the desired and designed closed-loop systems are found to be matching. It has shown that interaction parameter λ controls both the steady-state and transient response of the desired closed-loop system. The interaction parameter also acts as a parameter which controls the coupling and is chosen by the designer as a specification to be met by the designed closed-loop system with PID controller.

Design and Implementation of GA Tuned PID Controller for Desired Interaction and Trajectory Tracking of Wheeled Mobile Robot

Contribution of coal-based power plant in the energy sector covers 41% globally. Therefore the role of economic and emission generation scheduling (EEGS) of thermal power plant is important in the aspect of environmental issues and health damages created by this plants. This paper discusses the optimal operation of thermal-wind power generation system in reducing fuel cost and environmental pollution. In this paper, the bi-objective EEGS problem is transformed to a lone function by maximum price penalty factor. Improved Harmony Search (IHS) technique is implemented to obtain the optimal solution. The efficiency of the proposed method for searching optimum solution is examined with test case comprising of three thermal and two wind generation plants. The performance is compared with the Particle Swarm Optimization (PSO) method.

T. K. Sunil Kumar

Papers

Hydro-Thermal-Wind Generation Scheduling Considering Economic and Environmental Factors Using Heuristic Algorithms

Congestion management in restructured power systems for smart cities in India

PI, PID controller design for interval systems using frequency response model matching technique

Design and Implementation of GA Tuned PID Controller for Desired Interaction and Trajectory Tracking of Wheeled Mobile Robot

Economic and emission generation scheduling of thermal power plant incorporating wind energy