The optimization problem of two or more special-purpose functions of the energy system is subjected to an analysis. Based on experience of our research and general knowledge of partial solutions of energy system optimization at the level of control of production and power energy supply by energy companies in the Czech Republic, a special-purpose (cost) function has been defined. By analysing the special-purpose function, penalty and limitations have been defined. Using the fuzzy logic, a set of suitable solutions for the special-purpose function is accepted. An optimum of the special-purpose function is looked for using the simulated annealing method. The history of electricity consumption is sorted by day and by hour, representing the multidimensional data. When using the cluster analysis, type daytime diagrams of consumption are defined. Type daytime diagrams form prototypes of identified clusters. The so-called self-organizing neural network with Kohonen map attached is used to perform the cluster analysis. The result of our research is presented by an experiment.
Simulated annealing construction of shortest (spanning/nonspanning
and closed/open) paths on generál connected graphs is discussed. A brief graphtheoretical analysis of the problem is given. A theorem has been proved that for connected graphs the shortest paths are semielementary, that is each edge on the path is visited at most twice in opposite directions. This observation considerably reduces the search space. Tasks may be further specified depending on whether the initial and terminal vertices are given or not. Similarly, in construction of shortest open paths a subtask is considered when the path must visit a prescribed subset of graph vertices. Illustrative calculations demonstrate that the proposed method results for incomplete graphs in the paths that are dosely related to optimal solutions.
The text describes the optimization task of renewable energy sources distributed to electrical microgrid of fictitious intelligent area that consists of intelligent buildings. Firstly, to solve this task a general optimization heuristic method of simulated annealing will be described. Testing was performed on the analytical functions but those will be only covered marginally. Of the tests on the approximation functions the method of simulated annealing would be the most suitable algorithm for the optimization task. Furthermore, two experiments were introduced. The first lies in the application of cluster analysis on daily diagrams of electricity consumption in intelligent buildings. Because the modeled year history of hourly electricity consumption is represented by multidimensional data this data forms the training set during the adaptive dynamics submitted to a competence model of neural network by days. After the network adaptation process the Kohonen's map during the adaptive dynamics will be drawn, from which required clusters can be read. In the second experiment a sorting design of the resources for typical days of a week is performed in the computer program UniCon.
Presented study is aimed at using additional information to improve process represen-tativity of hydrological modelling. The study region is the Haute-Mentue catchment lo-cated in the western part of Switzerland, 20 km north of Lausanne. Previous research in this catchment allowed improving of the understanding of the runoff generation by combining point soil moisture measurements (TDR) and integrating measurements both at the hillslope scale (dye tracing) and at the catchment scale (environmental tracing). In this work, environmental tracing information will be integrated into a semi-distributed hydrological model, which is a modified version of TOPMODEL taking into account a rapid stormflow generation above a less permeable soil horizon. Additional information has been incorporated by using a version of simulated annealing adapted for multi-criteria optimisation. and Štúdia je venovaná využitiu dodatkových informácií pri reálnejšej simulácii hydrologických procesov v zrážkovo-odtokovom modeli. Študovanou oblasťou je povodie Haute-Mentue, ležiace v západnej časti Švajčiarska, 20 km od Lausanne. Predchádzajúci výskum v tomto povodí, založený na kombinácii bodových meraní (TDR) a integrovaných meraní v mierke svahu (farbiace skúšky) a povodia (prirodzené stopovače), zlepšil vedomosti o tvorbe odtoku. V tejto štúdii sú informácie získané prirodzenými stopovačmi použité pri posudzovaní výsledkov simulácie odtoku pomocou semidistribuovaného hydrologického modelu (modifikovaná verzia modelu TOPMODEL, ktorá uvažuje s mechanizmom tvorby odtoku nasýtením nad vrstvou pôdy s nižšou priepustnosťou). Ďalšou dodatkovou informáciou boli výsledky automatickej optimalizácie parametrov modelu pmocou metódy vychádzajúcej z analógie medzi optimalizáciou parametrov modelu a rozdelením častíc v tuhnúcej kvapaline (tzv. simulated annealing), adaptovanej na optimalizáciu podľa viacerých kritérií.