Dynamic economic dispatch for wind-thermal power system using a novel bi-population chaotic differential evolution algorithm

2012 ◽  
Vol 42 (1) ◽  
pp. 119-126 ◽  
Author(s):  
Chunhua Peng ◽  
Huijuan Sun ◽  
Jianfeng Guo ◽  
Gang Liu
Keyword(s):  
Power System ◽  
Differential Evolution ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Thermal Power System ◽  
Evolution Algorithm ◽  
Dynamic Economic Dispatch

Differential evolution algorithm based tilt integral derivative control for LFC problem of an interconnected hydro-thermal power system

2017 ◽  
Vol 24 (17) ◽  
pp. 3952-3973 ◽  
Author(s):  
Pretty Neelam Topno ◽  
Saurabh Chanana
Keyword(s):  
Power System ◽  
Differential Evolution ◽  
Pid Control ◽  
Thermal Power ◽  
Differential Evolution Algorithm ◽  
Operating Conditions ◽  
Proportional Integral ◽  
Load Frequency ◽  
Thermal Power System ◽  
Evolution Algorithm

Conventional control techniques such as proportional integral (PI) control and proportional integral derivative (PID) control are widely used as the load frequency controller in power system control applications; however, the increase in complexity of the power system is degrading the performance of classical control. Therefore, in this paper a new control approach using fractional calculus has been proposed for the load frequency control problem of two-area hydro-thermal power system. The paper presents an interconnected hydro-thermal power system working under different operating conditions introduced in the form of various nonlinearities. Four case studies have been presented in this paper considering transient analysis with (i) different loading conditions, (ii) parameter variations, (iii) different nonlinearities (governor dead band nonlinearity, time delay and generation rate constraints), and (iv) superconducting magnetic energy storage (SMES) device. A tilt integral derivative (TID) control has been presented as a secondary controller to stabilize the frequency deviations occurring in the two-area power system with the above-mentioned different operating conditions. The parameters of TID controller have been optimized using a differential evolution algorithm which solves an optimization problem formulated using the integral of time-weighted absolute error (ITAE) performance index. In addition, a comparison of dynamic system response obtained using TID control and PID control has been presented, which focusses on the better performance of TID control over PID control in an interconnected power system.

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

2020 ◽  
Vol 13 (3) ◽  
pp. 384-395
Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li
Keyword(s):  
Differential Evolution ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Bee Colony ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Dynamic Economic Dispatch ◽  
Integrated Power System

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

scholarly journals Dynamic Economic Dispatch in Thermal-Wind-Small Hydropower Generation System

2018 ◽  
Vol 246 ◽  
pp. 01085
Author(s):  
Guangbiao Liu ◽  
Jianzhong Zhou ◽  
Xiaogang Xiao ◽  
Li Mo ◽  
Yang Yuqi ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Wind Power ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Small Hydropower ◽  
Hydro Power ◽  
Thermal Wind ◽  
Hydropower System ◽  
Evolution Algorithm ◽  
Dynamic Economic Dispatch

With the large-scale wind power integration, the uncertainty of wind power poses a great threat to the safe and stable operation of the system. This paper proposes dynamic economic dispatch problem formulation in thermal power system incorporating stochastic wind and small-hydro (run-in-river) power, called thermal-wind-small hydropower system (TWSHS). Weibull and Gumbel probability density functions are used to calculate available wind and small-hydro power respectively. An improved differential evolution algorithm based on gradient descent information (DE-GD) is proposed to solve the dynamic economic dispatch (DED) problem considering uncertainty of wind power and small-hydro power, as well as complicated constraints in TWSHS. Based on the traditional differential evolution algorithm, the gradient information of the objective function is introduced after the mutation process to enrich the diversity of the population, thus increasing the possibility of convergence to the global optimization. Generation scheduling is simulated on a TWSHS with the proposed approach. Simulation results verify feasibility and effectiveness of the proposed method while considering various complex constraints in the thermal-windsmall hydropower system.

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