Issue |
MATEC Web Conf.
Volume 95, 2017
2016 the 3rd International Conference on Mechatronics and Mechanical Engineering (ICMME 2016)
|
|
---|---|---|
Article Number | 15004 | |
Number of page(s) | 5 | |
Section | Power System and Electrical Engineering | |
DOI | https://doi.org/10.1051/matecconf/20179515004 | |
Published online | 09 February 2017 |
Multi-Objective Low-Carbon Economic Dispatch Considering Demand Response with Wind Power Integrated Systems
1 Provincial Electric Power Co. Ltd, Shenyang 110006, China
2 Electric Power Research institute Liaoning Electric Power Company Limited, Shenyang 110006, China
3 Electric Power Research institute of Jilin Electric Power Co.of State Grid, Changchun 130021, China
The generation cost, carbon emissions and customers’ satisfaction are considered in this paper. On the basis of this, the multi-objective and low-carbon economic dispatch model with wind farm, this considers demand response, is established. The model user stochastic programming theory to describe the uncertainty of the wind power and converts it into an equivalent deterministic model by using distribution function of wind power output, optimizes demand side resources to adjust the next day load curve and to improve load rate and absorptive capacity of wind power, introduce customers’ satisfaction to ensure that the scheduling scheme satisfies customer and integrate the resources of source and load to unify coordination wind farm access to network and to meet the requirements of energy saving and emission reduction. The search process of artificial fish school algorithm introducing Tabu search and more targeted search mechanism, an multi-objective improved artificial fish school algorithm is proposed to solve this model. Using the technique for order preference by similarity to ideal solution (TOPSIS) to sort the Pareto frontier, the optimal scheduling scheme is determined. Simulation results verify the rationality and validity of the proposed model and algorithm.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.