Optimal sizing of PV-wind-battery power system considering demand response programs

Tobaru, Shota; Conteh, Foday; Senjyu, Tomonobu; Howlader, Abdul Motin; Funabashi, Toshihisa

doi:10.1109/peds.2017.8289232

Cited by 6 publications

(1 citation statement)

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“…Reference [13] provides an independent management for minimizing the electricity bill and purchased power from the grid by employing PV and ESS. An optimization methodology for PV, wind generation, and ESS has been proposed in [14], which is completely based on RERs and is isolated from the grid. In [15], the authors proposed an optimization algorithm for the lighting system of an office building based on the user preferences and comforts, with respect to the RERs.…”

Section: Introductionmentioning

confidence: 99%

optimization-Based Home Energy Management System Under Different Electricity Pricing Schemes

Khorram

Faria

Vale

2018

2018 IEEE 16th International Conference on Industrial Informatics (INDIN)

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This paper represents an optimization-based home energy management system, by taking advantages of renewable resources and energy storage system for optimally managing the energy consumption and generation of the house. The surplus of renewable generation will be stored in energy storage system or will be injected into the main grid. An optimization algorithm is developed for this system in order to minimize the electricity bill of the house considering electricity tariffs. Four home appliances are considered to be controlled by this system for reducing the consumption in critical periods. The outcomes of optimization problem would be the optimal scheduling of the resources including renewable generations, energy storage system, consumption reduction, and power transactions with the grid. In the case studies, the developed model will be employed in three different scenarios, which considers simple electricity prices and time-of-use tariffs in order to test and validate the performance of the developed model.

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Section: Introductionmentioning

confidence: 99%