Forecasting of the group of power system’s technical condition composite index and demand for heat energy by office buildings using an artificial neural network
| Autor: | T Y Andreeva, A P Sofronitsky, S V Guzhov |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Materials Science and Engineering. 1089:012035 |
| ISSN: | 1757-899X 1757-8981 |
| Popis: | Support of a sustained reduction of energy resource consumption by implementing advanced energy-efficient technologies, including alternative and renewable energy sources, requires a well-reasoned selection of the cost-effective measures so it can be replicated at the «green construction» sites. One of the basic approaches in forming of the present-day policy in the ecofriendly and energy-saving trends became a scaling effect of what has been achieved from the «green construction» technologies implementation at similar sites in Moscow. The actuality and scientific novelty of this paper lie in the development of the evaluation algorithm of energy and as a result of echo-economic efficiency of different measures for energy-saving, the adaptation of the forecasting methodology for building’s technical condition index application, review of the alternative and renewable energy source technologies implementation at the «green construction» sites in the Moscow region, analysis of the technical and ecological efficiency actual values of the utilized energy-saving methods and technologies. Monitoring and dispatching of a large number of separate power plants require special ways of collecting, processing, and analyzing information about the condition of water, heat, fuel, and electricity supply systems to ensure reliability and stability of the equipment functioning. Failures necessitate maintenance works at facilities by way of equipment repair as well as replacement. The consumers may impose penalties on the heat supply company for violating heat energy supply obligations as well as on the building’s owner for incorrect equipment maintenance. The objective of this paper is to determine an approach that helps to develop a software program, based on the neural network programming, to calculate the forecasting composite index of building’s energy system, «green construction» facilities ecological and economic efficiency examination and feasibility evaluation of their further replication in Moscow region. |
| Databáze: | OpenAIRE |
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