intelligent energy management

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INTROUCTION Industrial plants have put continuous pressure on the advanced process automation. However, there has not been so much focus on the automation of the electricity distribution networks. Although, the uninterrupted electricity distribution is one basic requirement for the process. A disturbance in electricity supply causing the" downrun" of the process may cost huge amount of money. Thus the intelligent management of electricity distribution including, for example, preventive condition monitoring and on-line reliability analysis has a great importance. Nowadays the above needs have aroused the increased interest in the electricity distribution automation of industrial plants. The automation of public electricity distribution has developed very rapidly in the past few years. Very promising results has been gained, for example, in decreasing outage times of customers. However, the same concept as such cannot be applied in the field of industrial electricity distribution, although the bases of automation systems are common. The infrastructures of different industry plants vary more from each other as compared to the public electricity distribution, which is more homogeneous domain. The automation devices, computer systems, and databases are not in the same level and the integration of them is more complicated. Applications for supporting the public distribution network management It was seen already in the end of 80's that the conventional automation system (i.e. SCADA) cannot solve all the problems regarding to network operation. On the other hand, the different computer systems (e.g. AM/FM/GIS) include vast amount of data which is useful in network operation. The operators had considerable heuristic knowledge to be utilized, too. Thus new tools for practical problems were called for, to which AI-based methods (e.g. object-oriented approach, rule-based technique, uncertainty modeling and fuzzy sets, hypertext technique, neural networks and genetic algorithms) offers new problem solving methods.

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Abstract for Intelligent energy management of electrical power system

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INTROUCTIONIndustrial plants have put continuous pressure on the advanced process automation. However, therehas not been so much focus on the automation of the electricity distribution networs. !lthou"h, the uninterrupted electricity distribution is one basic re#uirement for the process. ! disturbance in electricity supply causin" the$ downrun$ of the process may cost hu"e amount of money. Thus the intelli"ent mana"ement of electricity distribution includin", for e%ample, preventive condition monitorin" and on&line reliability analysis has a "reat importance.Nowadays the above needs have aroused the increased interest in the electricity distribution automation of industrial plants. The automation of public electricity distribution has developed very rapidly in the past few years. 'ery promisin" results has been "ained, for e%ample, in decreasin" outa"e times of customers. However, the same concept as such cannot be applied in thefield of industrial electricity distribution, althou"h the bases of automation systems are common. The infrastructures of different industry plants vary more from each other as compared to the public electricity distribution, which is more homo"eneous domain. The automation devices, computer systems, and databases are not in the same level and the inte"ration of them is more complicated.!pplications for supportin" the public distribution networ mana"ementIt was seen already in the end of ()*s that the conventional automation system +i.e. ,C!-!. cannot solve all the problems re"ardin" to networ operation. On the other hand, the different computer systems +e.". !/01/02I,. include vast amount of data which is useful in networ operation. The operators had considerable heuristic nowled"e to be utili3ed, too. Thus new tools for practical problems were called for, to which !I&based methods +e.". ob4ect&oriented approach, rule&based techni#ue, uncertainty modelin" and fu33y sets, hyperte%t techni#ue, neural networs and "enetic al"orithms. offers new problem solvin" methods.,o far a computer system entity, called as a distribution mana"ement system +-/,., has been developed. The -/, is a part of an inte"rated environment composed of the ,C!-!, distribution automation +e.". microprocessor&based protection relays., the networ database +i.e. !/01/02I,., the "eo"raphical database, the customer database, and the automatic telephone answerin" machine system. The -/, includes many intelli"ent applications needed in networ operation. ,uchapplications are, for e%ample, normal state&monitorin" and optimi3ation, real&time networ calculations, short term load forecastin", switchin" plannin", and fault mana"ement.The core of the whole -/, is the dynamic ob4ect&oriented networ model. The distribution networis modeled as dynamic ob4ects which are "enerated based on the networ data read from the networ database. The networ model includes the real&time state of the networ +e.". topolo"y and loads.. -ifferent networ operation tass call for different inds of problem solvin" methods. 'arious modules can operate interactively with each other throu"h the networ model, which worsas a blacboard +e.". the results of load flow calculations are stored in the networ model, where they are available in all other modules for different purposes..The present -/, is a 5indows NT &pro"ram implemented by 'isual C66. The prototypin" meant the iteration loop of nowled"e ac#uisition, modelin", implementation, and testin". 7rototype versions were tested in a real environment from the very be"innin". Thus the feedbac on new inference models, e%ternal connections, and the user&interface was obtained at a very early sta"e. The aim of a real application in the technical sense was thus been achieved. The -/, entity was tested in the pilot company, 8oillis&,ataunnan ,9h: Oy, havin" about ;))) distribution substations and ;