Visible to the public Multi-objective dynamic unit commitment optimization for energy-saving and emission reduction with wind power

TitleMulti-objective dynamic unit commitment optimization for energy-saving and emission reduction with wind power
Publication TypeConference Paper
Year of Publication2015
AuthorsWang, J., Zhou, Y.
Conference Name2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)
Date Publishednov
Keywordsair pollution, carbon compounds, CO2, commitment discrete magnitude, double optimization, double-optimization strategy, emission reduction, energy-saving, energy-saving and emission reducing, fault time, fuzzy satisfaction-maximizing method, fuzzy set theory, genetic algorithms, Heuristic algorithms, Linear programming, load distribution, mixed-integer variable, multi-objective, multiobjective dynamic unit commitment optimization, multiobjective unit commitment modeling, nondominated sorting genetic algorithm-II, NSGA-D, NSGA-II algorithm, Optimization, Pareto optimisation, Pareto solution, pollution emission, power generation dispatch, power generation scheduling, pubcrawl170110, satisfaction-maximizing decision, SO2, Spinning, sulphur compounds, unit commitment optimization, Wind power generation, wind power integrated system, wind power plants, Wind speed, wind turbines

As a clean energy, wind power is massively utilized in net recent years, which significantly reduced the pollution emission created from unit. This article referred to the concept of energy-saving and emission reducing; built a multiple objective function with represent of the emission of CO2& SO2, the coal-fired from units and the lowest unit fees of commitment; Proposed a algorithm to improving NSGA-D (Non-dominated Sorting Genetic Algorithm-II) for the dynamic characteristics, consider of some constraint conditions such as the shortest operation and fault time and climbing etc.; Optimized and commitment discrete magnitude and Load distribution continuous quantity with the double-optimization strategy; Introduced the fuzzy satisfaction-maximizing method to reaching a decision for Pareto solution and also nested into each dynamic solution; Through simulation for 10 units of wind power, the result show that this method is an effective way to optimize the Multi-objective unit commitment modeling in wind power integrated system with Mixed-integer variable.

Citation Keywang_multi-objective_2015