Multi-interval schedule of economic dispatch for cogeneration systems

2015 ◽  
pp. 33-37
Author(s):  
Ming-Tang Tsai ◽  
Fu-Sheng Chen ◽  
Chi-Chun Lo
Keyword(s):  
Economic Dispatch ◽  
Interval Schedule

The Effects of Variable-Interval and Fixed-Interval Signal Presentation Schedules on the Auditory Evoked Response

1969 ◽  
Vol 12 (1) ◽  
pp. 199-209 ◽  
Author(s):  
David A. Nelson ◽  
Frank M. Lassman ◽  
Richard L. Hoel
Keyword(s):  
Variable Interval ◽  
Tone Burst ◽  
Signal Amplitude ◽  
Fixed Interval ◽  
Interval Schedule ◽  
Sensation Level ◽  
Fixed Interval Schedule ◽  
Auditory Evoked Responses ◽  
Auditory Evoked Response ◽  
Signal Presentation

Averaged auditory evoked responses to 1000-Hz 20-msec tone bursts were obtained from normal-hearing adults under two different intersignal interval schedules: (1) a fixed-interval schedule with 2-sec intersignal intervals, and (2) a variable-interval schedule of intersignal intervals ranging randomly from 1.0 sec to 4.5 sec with a mean of 2 sec. Peak-to-peak amplitudes (N 1 — P 2 ) as well as latencies of components P 1 , N 1 , P 2 , and N 2 were compared under the two different conditions of intersignal interval. No consistent or significant differences between variable- and fixed-interval schedules were found in the averaged responses to signals of either 20 dB SL or 50 dB SL. Neither were there significant schedule differences when 35 or 70 epochs were averaged per response. There were, however, significant effects due to signal amplitude and to the number of epochs averaged per response. Response amplitude increased and response latency decreased with sensation level of the tone burst.

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.

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