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 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.

scholarly journals Optimal Scheduling of Solar-Wind-Thermal Integrated System Using α-Constrained Simplex Method

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sunimerjit Kaur ◽  
Yadwinder Singh Brar ◽  
Jaspreet Singh Dhillon
Keyword(s):  
Solar Wind ◽  
Simplex Method ◽  
Thermal Power ◽  
Test System ◽  
Integrated System ◽  
Optimal Scheduling ◽  
Fuel Cost ◽  
Test Systems ◽  
Power Scheduling ◽  
Conflicting Objectives

In this paper, multi-objective economic-environmental solar-wind-thermal power scheduling model was developed and it was optimized for five test systems. First test system was based upon a purely thermal power generating system and its problem was formulated to satisfy three conflicting objectives: (i) fuel cost, (ii)  emission, and (iii)  emission. The second, third and fourth test systems were comprised of optimal scheduling of integrated solar-thermal, wind-thermal and solar-wind-thermal power systems, respectively. Uncertainty costs were also considered in the renewable power based systems. These four test systems were examined for five power demands i.e. 200 MW, 225 MW, 250 MW, 275 MW, & 300 MW. Fifth test system was also deployed upon a renewable-thermal power scheduling. The effects of variation in number of thermal generators on fuel cost and  emission were perceived, for a power demand of 400 MW. The values of fuel cost (4067.98 Rs/h) and  emission (2,441.05 kg/h) reduced to 3,232.94 Rs/h and 1,939.30 kg/h, respectively, when number of thermal generators were reduced from four to two. The -constrained simplex method (ACSM) was used for simulation and the results were compared with simplex method (SM). The results clearly depict the dominance of ACSM over SM in almost all the fields.

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.

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>

Economic and Reliable Preventive Maintenance Scheduling in Power Systems by Using Binary Crow Search Algorithm

2021 ◽  
Vol 56 ◽  
pp. 182-198
Author(s):  
Adel A. Abou El Ela ◽  
Ragab El-Sehiemy ◽  
Abdullah M. Shaheen ◽  
Ayman S. Shalaby
Keyword(s):  
Power System ◽  
Preventive Maintenance ◽  
Search Algorithm ◽  
Economic Cost ◽  
Economic Benefits ◽  
Test System ◽  
Optimization Techniques ◽  
Maintenance Scheduling ◽  
Scheduling Problem ◽  
Matlab Programming

The generation system is an important part of the power system. The problem of generator maintenance scheduling is provided to construct optimal generators preventive maintenance schedules. It aims to improve economic benefits and achieve reliable operation of the power system while satisfying the system and maintenance constraints. In this paper, the binary crow search algorithm is proposed for solving the scheduling problem. This model would schedule maintenance scheme and commitment status of generating units while the objective functions are achieved. The crow search algorithm is a new meta-heuristic optimizer, which has its implementation very simple and easy compared to other optimization techniques. To verify the robustness and effectiveness of the proposed binary crow search optimizer, three test systems namely 6–unit, 21–unit system, and IEEE reliability test system are considered over the planning horizon of 52 weeks. The proposed optimizer is implemented in the MATLAB programming environment. Techno-economic aspects are considered for the generator's maintenance scheduling problem as reliability enhancement economic cost-minimizing issues. The proposed binary crow search optimizer is developed for single and multi-objective frameworks. The simulation results show the proposed binary crow search technique effectiveness and feasibility compared with previously optimizer in solving the generators maintenance scheduling problem with better convergence rate.

Investigation of Transmission Line Models for Switching Overvoltages Studies

2013 ◽  
Vol 14 (3) ◽  
pp. 231-238
Author(s):  
Iman Sadeghkhani ◽  
Abbas Ketabi ◽  
Rene Feuillet
Keyword(s):  
Power System ◽  
New England ◽  
Transmission Line ◽  
Test System ◽  
Shunt Reactor ◽  
Power System Restoration ◽  
System Restoration ◽  
Transmission Line Models ◽  
Simulation Time

Abstract Overvoltages caused by switching operation of power system equipments might damage some equipment and delay power system restoration. This paper presents a comparison between transmission line (TL) models for overvoltages study and investigates which TL model is most proper for every case study. Both simulation time and accuracy factors of TL models are considered for selecting best TL model. Various cases of switching of transformer, shunt reactor, capacitor bank, and transmission line are investigated and simulation results for a partial of 39-bus New England test system, ‎show that the proposed TL model evaluation increase accuracy and reduce simulation time (accelerate power system restoration) properly.

scholarly journals Generation-Load Coordinative Scheduling considering the Demand-Response Uncertainty of Inverter Air Conditioners

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wei Hu ◽  
Jin Yang ◽  
Yi Wu ◽  
Weiguo Zhang ◽  
Xueming Li ◽  
...  
Keyword(s):  
Power System ◽  
Demand Response ◽  
Load Scheduling ◽  
Air Conditioners ◽  
Power Scheduling ◽  
Scheduling Model ◽  
Conditioning Equipment ◽  
The Cost ◽  
First Time

Inverter air conditioners (IACs) have gradually become the mainstream of resident air-conditioning equipment. Similar to traditional fixed-frequency air conditioners, IACs have the potential for demand response and load scheduling. However, the uncertainty of IACs is nonnegligible in generation-load scheduling. In this paper, the uncertain demand-response cost of IACs is studied for the first time. Meanwhile, based on the cost, a generation-load coordinative day-ahead scheduling model is proposed. In the scheduling, an IACs aggregator and traditional generators are coordinately dispatched to minimize the expected scheduling cost of the power system. The case study shows that the coordinative scheduling model can reduce the scheduling cost of the power system and encourage the IACs aggregator to improve their responsiveness or reduce their uncertainty, so as to improve the economy and reliability of power scheduling.

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