scholarly journals Optimal Scheduling of Large-Scale Wind-Hydro-Thermal Systems with Fixed-Head Short-Term Model

2020 ◽  
Vol 10 (8) ◽  
pp. 2964 ◽  
Author(s):  
Thang Trung Nguyen ◽  
Ly Huu Pham ◽  
Fazel Mohammadi ◽  
Le Chi Kien
Keyword(s):  
Power Plants ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimal Scheduling ◽  
Thermal Power Plants ◽  
Short Term ◽  
Thermal Systems ◽  
Hydropower Plants

In this paper, a Modified Adaptive Selection Cuckoo Search Algorithm (MASCSA) is proposed for solving the Optimal Scheduling of Wind-Hydro-Thermal (OSWHT) systems problem. The main objective of the problem is to minimize the total fuel cost for generating the electricity of thermal power plants, where energy from hydropower plants and wind turbines is exploited absolutely. The fixed-head short-term model is taken into account, by supposing that the water head is constant during the operation time, while reservoir volume and water balance are constrained over the scheduled time period. The proposed MASCSA is compared to other implemented cuckoo search algorithms, such as the conventional Cuckoo Search Algorithm (CSA) and Snap-Drift Cuckoo Search Algorithm (SDCSA). Two large systems are used as study cases to test the real improvement of the proposed MASCSA over CSA and SDCSA. Among the two test systems, the wind-hydro-thermal system is a more complicated one, with two wind farms and four thermal power plants considering valve effects, and four hydropower plants scheduled in twenty-four one-hour intervals. The proposed MASCSA is more effective than CSA and SDCSA, since it can reach a higher success rate, better optimal solutions, and a faster convergence. The obtained results show that the proposed MASCSA is a very effective method for the hydrothermal system and wind-hydro-thermal systems.

scholarly journals Optimal generation for wind-thermal power plant systems with multiple fuel sources

2021 ◽  
Vol 11 (2) ◽  
pp. 1022
Author(s):  
Phan Nguyen Vinh ◽  
Bach Hoang Dinh ◽  
Van-Duc Phan ◽  
Hung Duc Nguyen ◽  
Thang Trung Nguyen
Keyword(s):  
Power Plant ◽  
Thermal Power Plant ◽  
Power Plants ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Thermal Power Plants ◽  
Two Systems ◽  
Loading Effects

In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants.

scholarly journals Short–Term Planning of Hybrid Power System

2016 ◽  
Vol 67 (4) ◽  
pp. 234-245 ◽  
Author(s):  
Goran Knežević ◽  
Zoran Baus ◽  
Srete Nikolovski
Keyword(s):  
Power System ◽  
Power Plants ◽  
Thermal Power ◽  
Optimization Process ◽  
Thermal Power Plants ◽  
Short Term ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Hydropower Plants ◽  
Pumped Storage

Abstract In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

scholarly journals Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms

2020 ◽  
Vol 10 (5) ◽  
pp. 5123
Author(s):  
Thuan Thanh Nguyen ◽  
Van-Duc Phan ◽  
Bach Hoang Dinh ◽  
Tan Minh Phan ◽  
Thang Trung Nguyen
Keyword(s):  
Power Plants ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimal Operation ◽  
Total Cost ◽  
Lower Total Cost ◽  
Operation Parameters

In this paper, Cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIWPSO) and Social Ski-Driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS.

scholarly journals Minimize electricity generation cost for large scale wind- thermal systems considering prohibited operating zone and power reserve constraints

2021 ◽  
Vol 11 (3) ◽  
pp. 1905
Author(s):  
Phan Nguyen Vinh ◽  
Bach Hoang Dinh ◽  
Van-Duc Phan ◽  
Hung Duc Nguyen ◽  
Thang Trung Nguyen
Keyword(s):  
Wind Power ◽  
Electricity Generation ◽  
Power Plants ◽  
Large Scale ◽  
Search Algorithm ◽  
Thermal Power ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Working Zone ◽  
Generation Cost

Wind power plants (WPs) play a very important role in the power systems because thermal power plants (TPs) suffers from shortcomings of expensive cost and limited fossil fuels. As compared to other renewable energies, WPs are more effective because it can produce electricity all a day from the morning to the evening. Consequently, this paper integrates the optimal power generation of TPs and WPs to absolutely exploit the energy from WPs and reduce the total electricity generation cost of TPs. The target can be reached by employing a proposed method, called one evaluation-based cuckoo search algorithm (OEB-CSA), which is developed from cuckoo search algorithm (CSA). In addition, conventional particle swarm optimization (PSO) is also implemented for comparison. Two test systems with thirty TPs considering prohibited working zone and power reserve constraints are employed. The first system has one wind power plant (WP) while the second one has two WPs. The result comparisons indicate that OEB-CSA can be the best method for the combined systems with WPs and TPs.

scholarly journals A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem

2021 ◽  
Vol 13 (8) ◽  
pp. 4277
Author(s):  
Cui Zheyuan ◽  
Ali Thaeer Hammid ◽  
Ali Noori Kareem ◽  
Mingxin Jiang ◽  
Muamer N. Mohammed ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Superior Performance ◽  
Electricity Production ◽  
Short Term ◽  
Power Generators ◽  
Hydrothermal Scheduling ◽  
Solution State ◽  
Hydropower Plants

The key criteria of the short-term hydrothermal scheduling (StHS) problem is to minimize the gross fuel cost for electricity production by scheduling the hydrothermal power generators considering the constraints related to power balance; the gross release of water, and storage limitations of the reservoir, and the operating limitations of the thermal generators and hydropower plants. For addressing the same problem, numerous algorithms were being used, and related studies exist in the literature; however, they possess limitations concerning the solution state and the number of iterations it takes to reach the solution state. Hence, this article proposes using an enhanced cuckoo search algorithm (CSA) called the rigid cuckoo search algorithm (RCSA), a modified version of the traditional CSA for solving the StHS problem. The proposed RCSA improves the solution state and decreases the iteration numbers related to the CSA with a modified Lévy flight. Here, the movement distances are divided into multiple possible steps, which has infinite diversity. The effectiveness of RCSA has been validated by considering the hydrothermal power system. The observed results reveal the superior performance of RCSA among all other compared algorithms that recently have been used for the StHS problem. It is also observed that the RCSA approach has achieved minimum gross costs than other techniques. Thus, the proposed RCSA proves to be a highly effective and convenient approach for addressing the StHS problems

scholarly journals Short-term optimal scheduling of hydro-thermal power plants using artificial bee colony algorithm

2020 ◽  
Vol 6 ◽  
pp. 984-992 ◽  
Author(s):  
Tehzeeb-ul-Hassan ◽  
Thamer Alquthami ◽  
Saad Ehsan Butt ◽  
Muhammad Faizan Tahir ◽  
Kashif Mehmood
Keyword(s):  
Power Plants ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Thermal Power ◽  
Optimal Scheduling ◽  
Thermal Power Plants ◽  
Short Term ◽  
Bee Colony
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