scholarly journals Short-term Hydro-Thermal-Wind-Solar Power Scheduling: A Case Study of Kanyakumari Region of India

2021 ◽  
Vol 10 (3) ◽  
pp. 635-651
Author(s):  
Sunimerjit Kaur ◽  
Yadwinder Singh Brar ◽  
Jaspreet Singh Dhillon
Keyword(s):  
Solar System ◽  
Power System ◽  
Real Time ◽  
Solar Power ◽  
Test System ◽  
Scheduling Problem ◽  
Fuel Cost ◽  
Thermal Wind ◽  
Power Scheduling

In this paper, an advanced modus operandi named the -constrained simplex method (ACSM) is deployed to resolve a real-time hydro-thermal-wind-solar power scheduling problem. ACSM is an updated articulation of the Nonlinear Simplex Method (SM) of Nelder and Mead. It has been designed after interbreeding an ordinary SM with some other methods like-evolutionary method, α-constrained method, etc. To develop this technique three alterations in the SM are adopted (i) -level differentiation, (ii) mutations of the worst point, and (iii) the incorporation of multi-simplexes. A real-time multi-objective hydro-thermal-wind-solar power scheduling problem is established and optimized for the Kanyakumari (Tamil Nadu, India) for the 18th of September of 2020. Four contrary constraints are contemplated for this case study (i)fuel cost and employing cost of wind and solar power system, (ii)  emission, (iii)  emission, and (iv) emission. The fidelity of the projected practice is trailed upon two test systems. The first test system is hinged upon twenty-four-hour power scheduling of a pure thermal power system. The values of total fuel cost,emission, emission, and emission are attained as 4707.19$/day, 59325.23 kg/day, 207672.70 kg/day, and 561369.20 kg/day, respectively. In the second test system, two thermal generators are reintegrated with renewable energy resources (RER) based power system (hydro, wind, and solar system) for the same power demands. The hydro, wind, and solar data are probed with the Glimn-Kirchmayer model, Weibull Distribution Density Factor, and Normal Distribution model, respectively. The outturns using ACSM are contrasted with the SM and evolutionary method(EM). For this real-time hydro-thermal-wind-solar power scheduling problem the values of fuel cost,  emission,  emission, and  emission are shortened to 1626.41 $/day, 24262.24 kg/day, 71753.80 kg/day, and 196748.20 kg/day, respectively for the specified interval using ACSM and with SM, these values are calculated as 1626.57 $/day, 24264.67 kg/day, 71760.98 kg/day, 196767.68 kg/day, respectively. The results for the same are obtained as 1626.74 $/day, 24267.10 kg/day, 71768.15 kg/day, 196787.55 kg/day, respectively, by using EM. The values of the operating cost of the solar system, wind system, total system transmission losses, and computational time of test system-2 with ACSM, SM, and EM are evaluated as 8438.76 $/day, 19017.42 $/day, 476.69 MW/day & 15.6 seconds; 8439.61 $/day, 19019.33 $/day, 476.74 MW/day and 16.8 sec; and 8447.20 $/day, 19036.43 $/day, 477.17 MW/day and 17.3 sec, respectively. The solutions portray the sovereignty of ACSM over the other two methods in the entire process.

Short-term Hydro-Thermal-Wind-Solar Power Scheduling: A Case Study of Kanyakumari Region of India

2021 ◽  
Author(s):  
Sunimerjit Kaur ◽  
Yadwinder Singh Brar ◽  
Jaspreet Singh Dhillon
Keyword(s):  
Solar System ◽  
Power System ◽  
Simplex Method ◽  
Solar Power ◽  
Test System ◽  
Scheduling Problem ◽  
Fuel Cost ◽  
Thermal Wind ◽  
Power Scheduling

In this paper, a multi-objective hydro-thermal-wind-solar power scheduling problem is established and optimized for the Kanyakumari (Tamil Nadu, India) for the 18th of September of 2020. Four contrary constraints are contemplated for this case study (i) fuel cost and employing cost of wind and solar power system, (ii) NOx emission, (iii) SO2 emission, and (iv) CO2 emission. An advanced hybrid simplex method named as-the -constrained simplex method (ACSM) is deployed to solve the offered problem. To formulate this technique three amendments in the usual simplex method (SM) are adopted (i) -level differentiation, (ii) mutations of the worst point, and (iii) the incorporation of multi-simplexes. The fidelity of the projected practice is trailed upon two test systems. The first test system is hinged upon twenty-four-hour power scheduling of a pure thermal power system. The values of total fuel cost and emissions (NOx, SO2, CO2) are attained as 346117.20 Rs, 59325.23 kg, 207672.70 kg, and 561369.20 kg, respectively. In the second test system, two thermal generators are reintegrated with renewable energy resources (RER) based power systems (hydro, wind, and solar system) for the same power demands. The hydro, wind, and solar data are probed with the Glimn-Kirchmayer model, Weibull Distribution Density Factor, and Normal Distribution model, respectively. For this real-time hydro-thermal-wind-solar power scheduling problem the values of fuel cost and emissions (Nox, SO2, CO2) are shortened to 119589.00 Rs, 24262.24 kg, 71753.80 kg, and 196748.20 kg, respectively for the specified interval. The outturns using ACSM are contrasted with the SM and evolutionary method (EM). The values of the operating cost of solar system, wind system, total system transmission losses, and computational time of test system-2 with ACSM, SM, and EM are evaluated as 620497.40 Rs, 1398340.00 Rs, 476.6948 MW & 15.6 seconds; 620559.45 Rs, 1398479.80 Rs, 476.7425 MW & 16.8 seconds; and 621117.68 Rs, 1399737.80 Rs, 477.1715 MW and 17.3 seconds, respectively. The solutions portray the sovereignty of ACSM over the other two methods in the entire process.

scholarly journals Handling Initial Conditions in Vector Fitting for Real Time Modeling of Power System Dynamics

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2471
Author(s):  
Tommaso Bradde ◽  
Samuel Chevalier ◽  
Marco De Stefano ◽  
Stefano Grivet-Talocia ◽  
Luca Daniel
Keyword(s):  
Dynamical Systems ◽  
Power System ◽  
System Dynamics ◽  
Real Time ◽  
Initial Conditions ◽  
Test System ◽  
Initial State ◽  
Power System Dynamics ◽  
Vector Fitting ◽  
Time Modeling

This paper develops a predictive modeling algorithm, denoted as Real-Time Vector Fitting (RTVF), which is capable of approximating the real-time linearized dynamics of multi-input multi-output (MIMO) dynamical systems via rational transfer function matrices. Based on a generalization of the well-known Time-Domain Vector Fitting (TDVF) algorithm, RTVF is suitable for online modeling of dynamical systems which experience both initial-state decay contributions in the measured output signals and concurrently active input signals. These adaptations were specifically contrived to meet the needs currently present in the electrical power systems community, where real-time modeling of low frequency power system dynamics is becoming an increasingly coveted tool by power system operators. After introducing and validating the RTVF scheme on synthetic test cases, this paper presents a series of numerical tests on high-order closed-loop generator systems in the IEEE 39-bus test system.

A new approach for near real-time micro-CHP management in the context of power system imbalances – A case study

2015 ◽  
Vol 89 ◽  
pp. 270-280 ◽  
Author(s):  
J. Zapata Riveros ◽  
R. Donceel ◽  
J. Van Engeland ◽  
W. D’haeseleer
Keyword(s):  
Power System ◽  
Real Time ◽  
New Approach

scholarly journals A Novel Extension Decision-Making Method for Selecting Solar Power Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Meng-Hui Wang
Keyword(s):  
Decision Making ◽  
Solar System ◽  
Power Systems ◽  
Power System ◽  
Solar Power ◽  
Important Task ◽  
Extension Theory ◽  
Solar Systems ◽  
Load Demand ◽  
Generating Capacity

Due to the complex parameters of a solar power system, the designer not only must think about the load demand but also needs to consider the price, weight, and annual power generating capacity (APGC) and maximum power of the solar system. It is an important task to find the optimal solar power system with many parameters. Therefore, this paper presents a novel decision-making method based on the extension theory; we call it extension decision-making method (EDMM). Using the EDMM can make it quick to select the optimal solar power system. The paper proposed this method not only to provide a useful estimated tool for the solar system engineers but also to supply the important reference with the installation of solar systems to the consumer.

Optimal scheduling of thermal-wind-solar power system with storage

2017 ◽  
Vol 101 ◽  
pp. 1357-1368 ◽  
Author(s):  
S. Surender Reddy
Keyword(s):  
Power System ◽  
Solar Power ◽  
Optimal Scheduling ◽  
Thermal Wind

PSS with SVC Damping Controllers Coordinated Design and Real-Time Implementation in Multi-Machine Power System Using Advanced Adaptive PSO

2013 ◽  
Vol 14 (5) ◽  
pp. 487-498
Author(s):  
Rajendraprasad Narne ◽  
P.C. Panda
Keyword(s):  
Power System ◽  
Real Time ◽  
Optimization Problem ◽  
Test System ◽  
Swarm Optimization ◽  
Damping Controllers ◽  
Control Schemes ◽  
Controller Performance ◽  
Adaptive Pso ◽  
System Stabilizer

Abstract This article proposed coordinated tuning and real-time implementation of power system stabilizer (PSS) with static var compensator (SVC) in multi-machine power system. The design of proposed coordinated damping controller is formulated as an optimization problem, and the controller gains are optimized instantaneously using advanced adaptive particle swarm optimization. Here, PSS with SVC installed in multi-machine system is examined. The coordinated tuning among the damping controllers is performed on the non-linear power system dynamic model. Finally, the proposed coordinated controller performance is discussed with time-domain simulations. Different loading conditions are employed on the test system to test the robustness of proposed coordinate controller, and the simulation results are compared with four different control schemes. To validate the proposed controller, the test power system is also implemented on real-time (OPAL-RT) simulator, and acceptable results are reported for its verifications.

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

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