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

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.

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Optimization of Reservoir Operation Using Cuckoo Search Algorithm: Example of Adiguzel Dam, Denizli, Turkey

Mathematical Problems in Engineering ◽

10.1155/2016/1316038 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7 ◽

Cited By ~ 8

Author(s):

Mutlu Yasar

Keyword(s):

Energy Production ◽

Heuristic Algorithms ◽

Search Algorithm ◽

Cuckoo Search ◽

Complex Problem ◽

Cuckoo Search Algorithm ◽

Optimal Operation ◽

Operating Rules ◽

Operation Rule ◽

Production Regime

The Adiguzel Dam is located in Denizli in the western part of Turkey. It was built for irrigation purposes, but it also produces energy at the same time. The dam’s energy-production regime is not regular since there are no reservoir-operating rules. Thus, this study develops a reservoir optimization rule to generate a corresponding gain in energy production. It is well known that operating a reservoir is a complex problem that depends on many parameters such as inflow, storage capacity, water elevation, tailwater elevation, and evaporation. Therefore, in order to optimize energy production, there is a need to use heuristic algorithms such as the Cuckoo Search (CS). This study develops a CS algorithm-based solution to optimize the reservoir’s operational system and generate an optimal operation rule curve. Results show that the CS algorithm improves the system operation, and the energy production will be increased by about 10% to a value of 160000 MWh with a corresponding economic gain of about $12 × 106in total for 183 months.

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

Applied Sciences ◽

10.3390/app10082964 ◽

2020 ◽

Vol 10 (8) ◽

pp. 2964 ◽

Cited By ~ 5

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.

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

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v11i3.pp1905-1911 ◽

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.

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

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v11i2.pp1022-1028 ◽

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.

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Non dominated Cuckoo search algorithm optimized controllers to improve the frequency regulation characteristics of wind thermal power system

Engineering Science and Technology an International Journal ◽

10.1016/j.jestch.2017.05.005 ◽

2017 ◽

Vol 20 (3) ◽

pp. 1092-1105 ◽

Cited By ~ 4

Author(s):

S. Chaine ◽

M. Tripathy ◽

Divesh Jain

Keyword(s):

Power System ◽

Search Algorithm ◽

Thermal Power ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Frequency Regulation ◽

Thermal Power System

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

International Journal of Current Engineering and Technology ◽

10.14741/ijcet/v.8.3.23 ◽

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.

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A Review of Cuckoo Search Algorithm Based Optimal Siting and Sizing of Shunt Capacitors in Radial Distribution Systems

UNIOSUN Journal of Engineering and Environmental Sciences ◽

10.36108/ujees/9102.10.0260 ◽

2019 ◽

Vol 1 (2) ◽

Author(s):

O.E. Olabode

Keyword(s):

Radial Distribution ◽

Distribution Systems ◽

Reactive Power ◽

Heuristic Algorithms ◽

Search Algorithm ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Sensitivity Factor ◽

Voltage Profile ◽

Shunt Capacitors

Compensating reactive power deficiency on power grids is a central concern in the distribution of energy management systems. Several approaches have been adopted over time to minimize the total real power loss and enhancing bus voltage profile. Shunt capacitor has been used from time immemorial for addressing issue of reactive power compensation at the distribution end of power systems, and the extent of benefits derivable from its usage depend solely on correct siting and sizing. To this effect, meta-heuristic algorithms are promising optimization tools for achieving these objectives. This paper, therefore, presents a comprehensive review of cuckoo search algorithm based on optimal siting and sizing of shunt capacitors in radial distribution systems. The suitability, in addition to strengths and weakness of each approaches reported in the reviewed articles have been painstakingly x-rayed. Based on the review, it was observed that a two-stage approach is always adopted in the compensation process: the pre-selection of potential or sensitive nodes and the optimal sizing of shunt capacitors needed for the compensation. For the pre-location, Voltage Stability Index and Loss Sensitivity Factor were found to be comparatively less complex and highly suitable techniques. Another cogent discovery from this review is that less attention has been drawn to the use of cuckoo search algorithm by Nigerian researchers. Therefore, regarding Nigerian electric grid system, the use of cuckoo search algorithm in reactive power support presents a research gap for further investigations.

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