Research of Building Load Optimal Scheduling Based on Multi-objective Estimation of Distributed Algorithm

In the centralized scheduling of multi-residents, the complexity of scheduling time will be greatly increased as the number of resident increases. In order to reduce the time complexity caused by centralized scheduling, a probability model based on the Time-of-use electricity tariff difference is pr...

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Bibliographic Details
Published in:Journal of electrical engineering & technology Vol. 16; no. 2; pp. 647 - 658
Main Authors: Yi, Lingzhi, Liu, Jiankang, Yi, Fang, Lin, Jiahao, Li, Wang, Fan, Lǜ
Format: Journal Article
Language:English
Published: Singapore Springer Singapore 01.03.2021
대한전기학회
Subjects:
Electrical Engineering
Electrical Machines and Networks
Electronics and Microelectronics
Engineering
Instrumentation
Original Article
Power Electronics
전기공학
Probabilistic model method
Time-of-use electricity tariff
Estimation of distributed algorithm
Optimization
ISSN:1975-0102, 2093-7423
Online Access:Get full text
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Summary:In the centralized scheduling of multi-residents, the complexity of scheduling time will be greatly increased as the number of resident increases. In order to reduce the time complexity caused by centralized scheduling, a probability model based on the Time-of-use electricity tariff difference is proposed and applied to distributed estimation of the algorithm. According to the impact factor mechanism of the probability model of Time-of-use electricity tariff difference, not only the time complexity of centralized scheduling is reduced, but also the optimization of the algorithm will not fall into a local optimal situation. In the centralized scheduling model of building residents, the controllable load of residents and new energy are centralized. The consumption rate of new energy was improved by changing the new energy power supply mechanism. Under the conditions of ensuring the comfort of household electricity consumption, three objective functions of the model include: (a) to reduce the total daily electricity consumption, (b) to flatten the peak-to-valley difference of daily electricity, (c) to decrease the discarded rate of new energy. The simulation of the calculation example verifies the feasibility and effectiveness of the proposed method.
ISSN:1975-0102
2093-7423
DOI:10.1007/s42835-020-00594-4