To shape a low carbon energy future has been a crucial and urgent task under Paris Global Agreement. Numerous optimisation problems have been formulated and solved to effectively save the fossil fuel cost and relief energy waste from power system and energy application side. However, some key problems are of strong non-convex, non-smooth or mixed integer characteristics, leading to significant challenging issues for system operators and energy users. This competition aims to encourage the relevant researchers to present their state-of-the-art optimisation tools for solving three featured complicated optimisation tasks including unit commitment, economic load dispatch and parameter identification for photovoltaic models and PEV fuel cells.
Unit commitment (UC) problem aims to minimize the economic cost by optimally determining the online/offline status and power dispatch of each unit, while maintaining various system constraints, formulating a large scale mixed-integer problem. Economic load dispatch is a power system operation task aiming to minimize the fossil fuel economic cost by determining the day-ahead and/or hourly power generation for each power generator. Fuel cell is one of most important energy storages in the future, particularly with the applications to vehicles and robotics. Proton Exchange Membrane is the key component of fuel cell however is of significant difficulties to be accurately modelled due to the nonlinearity, multivariate and strongly coupled characteristics. Evolutionary computation is immune from complex problem modelling formulation, and is therefore promising to provide powerful optimisation tools for intelligently and efficiently solving problems such as smart grid and various energy systems scheduling to reduce carbon consumption.
A brief list of potential submission topic is shown below:
• Unit commitment
Code (Link:UC Problem Benchmark.zip)
Code description (Link: UC Problem Benchmark.pdf)
• Economic load dispatch
Code (Link:Economic load dispatch Benchmark.zip)
Code description (Link: Economic load dispatch Benchmark.pdf)
• Parameters identification for photovoltaic models and PEM fuel cells
Code (Link:Parameters identification Benchmark.zip)
Code description (Link: Parameters identification Benchmark.pdf)
This competition intends to reflect the state-of-the-art advances of evolutionary optimisation approaches for solving emerging problems in complex modern power and energy system. In this competition, we choose the above three questions as the optimization object, in order to make it easier for comparative studies of different algorithms using the same platform, and get the better optimization results. The simulate experiment and data should be expressed on MATLAB platforms or other software platforms, therefore be ranked by the results according to the competition evaluation criteria. Interested participants are strongly encouraged to report their approaches and results in a paper and submit it to our special session CEC-17: Special Session on Evolutionary Computations on Smart Grid and Sustainable Energy Systems in the conference submission system, and also send their codes to the competition organizer at zl.yang@siat.ac.cn for verification. All the papers should be submitted before the conference paper submission deadline.
Should you have any other inquiries, please also contact Dr. Zhile Yang at: zl.yang@siat.ac.cn
Jan 21st, 23:59 (GMT)
Call for paper (http://www.cec2019.org/assets/downloads/CEC2019_CFP.pdf)
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