Optimal Scheduling Method of Controllable Loads in Smart Home Considering Re-Forecast and Re-Plan for Uncertainties

Autor: Kosuke Uchida, Mitsunaga Kinjo, Akihiro Yoza, Narayanan Krishna, Zengfeng Yan, Tomonobu Senjyu, Shantanu Chakraborty
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Battery (electricity)
Computer science
smart home
020209 energy
forecast
02 engineering and technology
lcsh:Technology
Automotive engineering
lcsh:Chemistry
020401 chemical engineering
Robustness (computer science)
Home automation
0202 electrical engineering
electronic engineering
information engineering
General Materials Science
0204 chemical engineering
Instrumentation
lcsh:QH301-705.5
Fluid Flow and Transfer Processes
business.industry
lcsh:T
Process Chemistry and Technology
Photovoltaic system
General Engineering
uncertainties
lcsh:QC1-999
Computer Science Applications
Renewable energy
Smart grid
lcsh:Biology (General)
lcsh:QD1-999
lcsh:TA1-2040
optimal scheduling
Electricity
business
lcsh:Engineering (General). Civil engineering (General)
Decision model
lcsh:Physics
photovoltaic generation
Zdroj: Applied Sciences, Vol 9, Iss 19, p 4064 (2019)
Applied Sciences
Volume 9
Issue 19
ISSN: 2076-3417
Popis: Renewable energies (REs) such as photovoltaic generation (PV) have been gaining attention in distribution systems. Recently, houses with PV and battery systems, as well as electric vehicles (EV) are expected to contribute to not only the suppression of global warming but also reducing electricity bill on the consumer side. However, there are numerous challenges with the introduction of REs at the demand side such as the actual output of REs often deviating from the forecasted output, which causes fluctuation of the power flow and this is challenging for the distribution or transmission system operator. For this challenge, it is expected that smart grid technology using controllable loads such as a fixed battery or EV battery, can suppress fluctuation of power flow. This paper presents a decision method of optimal scheduling of controllable loads to suppress the fluctuation of power flow by PV output in the smart home. An optimization method to cope with uncertainties such as variability of PV power and effective forecasting methods are considered in the proposed scheme. In order to decrease the expected operational cost and to validate the robustness for the uncertainty&rsquo
s optimization approach, statistical analysis is executed for the optimal scheduling scheme. From the optimization results, the proposed methodology suppressed the fluctuation of power flow in the smart home and also minimized the consumer operational cost.
Databáze: OpenAIRE
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