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 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 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 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 Improved Compact Cuckoo Search Algorithm Applied to Location of Drone Logistics Hub

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 333 ◽  
Author(s):  
Jeng-Shyang Pan ◽  
Pei-Cheng Song ◽  
Shu-Chuan Chu ◽  
Yan-Jun Peng
Keyword(s):  
Rural Areas ◽  
Large Scale ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Development Stage ◽  
Cuckoo Search Algorithm ◽  
Initial Development ◽  
Logistics Systems ◽  
The Cost ◽  
The Village

Drone logistics can play an important role in logistics at the end of the supply chain and special environmental logistics. At present, drone logistics is in the initial development stage, and the location of drone logistics hubs is an important issue in the optimization of logistics systems. This paper implements a compact cuckoo search algorithm with mixed uniform sampling technology, and, for the problem of weak search ability of the algorithm, this paper combines the method of recording the key positions of the search process and increasing the number of generated solutions to achieve further improvements, as well as implements the improved compact cuckoo search algorithm. Then, this paper uses 28 test functions to verify the algorithm. Aiming at the problem of the location of drone logistics hubs in remote areas or rural areas, this paper establishes a simple model that considers the traffic around the village, the size of the village, and other factors. It is suitable for selecting the location of the logistics hub in advance, reducing the cost of drone logistics, and accelerating the large-scale application of drone logistics. This paper uses the proposed algorithm for testing, and the test results indicate that the proposed algorithm has strong competitiveness in the proposed model.

Research on the Optimal Dispatching Strategies of Power System with Large-Scale Wind Power

2013 ◽  
Vol 385-386 ◽  
pp. 1117-1121
Author(s):  
Lin Chuan Li ◽  
Kun Wang
Keyword(s):  
Power System ◽  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Flow Model ◽  
Thermal Power ◽  
Maximum Output ◽  
Generation Cost ◽  
Equivalent Load

Large-scale wind power connected to the power system is a challenge to the traditional dispatch mode which is based on the accuracy of load forecasting and the accessibility of power, how to deal with the randomness and volatility of wind power has become a new problem facing the dispatch of power system. In this paper, an optimal power flow model with the goal of minimizing the total generation cost is established under the environment of generation market. Consider a variety of power supply in the system, the hydro and wind power should be preferentially used; Thermal power units bid for the capacity which is determined when wind power reach its maximum output at the minimum equivalent load time, and then whether the booting units can satisfy the load is checked at the maximum equivalent load time, if not, wind power will be curtailed to boot new thermal units until the load is met. Finally the example shows the feasibility of the dispatching strategies.

Implementation of Smooth and Non-Smooth Fuel Cost Function for Economic Load Dispatch using Cuckoo Search Method

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Apurva Gautam ◽  
Anupam Masih
Keyword(s):  
Cost Function ◽  
Power Plants ◽  
Search Algorithm ◽  
Inequality Constraints ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Practical Applications ◽  
Equality And Inequality Constraints

Economic Load Dispatch (ELD) is an important topic in the operation of power plants which can help to build up effecting generating management plans. The ELD problem has no smooth cost function with equality and inequality constraints which make it difficult to be effectively solved. The paper presents an application of Cuckoo Search Algorithm (CSA) to solve Economic Load Dispatch (ELD) problems with smooth and non-smooth fuel cost objective functions. Main objective of ELD is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses over a certain period of time while relaxing various equality and inequality constraints. The unit Min/Max operational constraints, effects of valve-point loading ripples and line losses are considered for the practical applications. This paper describes the implementation of smooth and non smooth fuel cost function by CSA Method and its comparison with BAT method. We have used 6 and 12 bus system for calculating their total fuel cost.

Optimal Operation Model for Virtual Power Plant in Datong Area

2015 ◽  
Vol 785 ◽  
pp. 627-631 ◽  
Author(s):  
Hei Wei ◽  
Rasyidah Mohamed Idris
Keyword(s):  
Power Plant ◽  
Wind Power ◽  
Power Plants ◽  
Large Scale ◽  
Wind Farm ◽  
Thermal Power ◽  
Optimal Operation ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Pumped Storage

Datong area has abundant wind energy. Due to problem in large scale of wind power grid connection, this paper introduces virtual power plant concept. As for beginning, power source characteristics of the wind farm, pumped storage power station and the thermal power plant are taken for analysis. Three types of different power plants are chosen to represent the virtual power plant modeling as well as adopting the NSGA2 optimization. As a conclusion, this case study proved that virtual power plant can increase the benefits of each power plant and the wind power plant output power curve become smoother.

scholarly journals An improved evaporation rate-water cycle algorithm based genetic algorithm for solving generalized ratio problems

2020 ◽  
Author(s):  
Veeramani C ◽  
sharanya senthil
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Water Cycle ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Genetic Operators ◽  
Water Cycle Algorithm ◽  
Hybrid Techniques ◽  
Scale Ratio

This paper presents an efficient metaheuristic approach for optimizing the generalized ratio problems such as the sum and multiplicative of linear or nonlinear ratio objective function with affine constraints. This paper focuses on the significance of hybrid techniques, which are implemented by using GA and ER-WCA to increase efficiency and robustness for solving linear and nonlinear generalized ratio problems. Initially, GA starts with an initial random population and it is processed by genetic operators. ER-WCA will observe and preserve the GAs fittest chromosome in each cycle and every generation. This Genetic ER-WCA algorithm is provided with better optimal solutions while solving constrained ratio optimization problems. Also, the effectiveness of the proposed genetic ER-WCA algorithm is analyzed while solving the large scale ratio problems. The results and performance of the proposed algorithm ensures a strong optimization and improves the exploitative process when compared to the other existing metaheuristic techniques. Numerical problems and applications are used to test the performance of the convergence and the accuracy of the approached method. The behavior of this Genetic ER-WCA algorithm is compared with those of evolutionary algorithms namely Neural Network Algorithm, Grey Wolf Optimization, ER-WCA, Water Cycle Algorithm, Firefly algorithm, Cuckoo search algorithm. The evaluated results show that the proposed algorithm increases the convergence and accuracy more than other existing algorithms.

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