Fuzzy Model Predictive Control Applied to Piecewise Linear Systems

Costa, Thiago V.; Tizzo, Lívia M.; Oliveira-Lopes, Luís Cláudio

doi:10.1016/s1570-7946(09)70625-x

Cited by 1 publication

(1 citation statement)

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“…The method of neural networks with the exposure into a neural network logical basis was chosen as the forecasting method [4][5][6][7][8]. The time frame was provisionally divided into 3 equal sequences to make independent forecasting.…”

Section: Forecasting and Optimization Resultsmentioning

confidence: 99%

Assessment of the Charging Policy in Energy Efficiency of the Enterprise

Shutov

Turukina

Anisimov

2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Abstract. The forecasting problem for energy facilities with a power exceeding 670 kW is currently one of the main. In connection with rules of the retail electricity market such customers also pay for actual energy consumption deviations from plan value. In compliance with the hierarchical stages of the electricity market a guaranteeing supplier is to respect the interests of distribution and generation companies that require load leveling. The answer to this question for industrial enterprise is possible only within technological process through implementation of energy-efficient processing chains with the adaptive function and forecasting tool. In such a circumstance the primary objective of a forecasting is reduce the energy consumption costs by taking account of the energy cost correlation for 24 hours for forming of pumping unit work schedule. The pumping unit virtual model with the variable frequency drive is considered. The forecasting tool and the optimizer are integrated into typical control circuit. Economic assessment of the optimization method was estimated.

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