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The aim of the work was to develop an Evolutionary Real-time Optimization System for Ecological Power Control for the area of Poland. The system belongs to the family of Integrated Assessment Models (IAMs) which provide a framework for bringing together disparate information related to a particular environmental problem. IAMs were used to help formulate the second sulphur protocol [UN-ECE EB.AIR/R.84, 1994] which derived cost-effective strategies for reducing SO2 emissions from coal-fired power stations across Europe. Similar methodologies were used to derive abatement strategies for the heavy polluted Black Triangle region of eastern Europe. In this current work the aim was to derive recommended level of produced energy for each particular pollution source from the public power generation sector (power plants and cogeneration plants) in Poland, with respect to actual country energy demand, which would minimize the sulphur dioxide exposure to ecosystems. Such a solution is possible as the country has an oversupply of the installed power with respect to the energy demand. System includes input data (data on emission sources, meteorological data, land-cover data), atmospheric pollution dispersion and deposition models as well as data on the capacity of the ecosystem to sustain certain level of concentration, so called critical levels. Evolutionary computation techniques (extended by genetic memory structures) are used for optimization process. |
