An operational optimization method of regional multi-energy system considering thermal quasi-dynamic characteristics

Chen, Xingying; Bu, Le; Chen, Cheng; Gan, Lei; Yu, Kun

doi:10.17775/cseejpes.2020.03830

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…The enclosure structure of a building endows the internal airconditioning system with the ability to store and release energy, thereby exhibiting characteristics similar to a VES system. This enables it to be considered VES and participate in DR (Chen et al, 2021). In commercial buildings, the internal tenants are dispersed and occupy smaller spaces, making it inconvenient to regulate the temperature control load.…”

Section: Air-conditioning Modelmentioning

confidence: 99%

Dynamic pricing optimization for commercial subcontracting power suppliers engaging demand response considering building virtual energy storage

Huang,

Ning,

Jiang

et al. 2024

Front. Energy Res.

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Commercial buildings have abundant flexible energy resources for demand response (DR). The electricity price for tenants in the commercial building is generally issued by a subcontracting power supplier (SPS), and the tenants cannot directly interact with the energy retailer. Therefore, the incentive for tenants to participate in DR is insufficient, and their potential is not fully explored. To address these issues, this paper proposes a dynamic pricing method based on the Stackelberg game, helping tenants actively participate in DR. Then, with the optimized energy consumption of the tenants, a virtual energy storage model of the commercial building is constructed by aggregating the adjustable capabilities of flexible energy resources such as air-conditioning (AC) and electric vehicles (EVs) in the public area. Finally, simulation tests are conducted based on a real commercial building to demonstrate the effectiveness of the game-theoretic pricing approach and validate the role of virtual energy storage of the building in DR.

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Section: Air-conditioning Modelmentioning

confidence: 99%

Dynamic pricing optimization for commercial subcontracting power suppliers engaging demand response considering building virtual energy storage

Huang,

Ning,

Jiang

et al. 2024

Front. Energy Res.

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Adaptive Voltage Regulation Scheme for Improved Power Management in Metropolitan

Madhukar Haval,

Chopra

2024

E3S Web of Conf.

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The problem of voltage regulation in metropolitan cities has been well studied. There exist different models to handle this problem, which consider the available voltage and number of connections in the part of city as the key in voltage regulation. However, the methods suffer to achieve higher performance in voltage regulation. To handle this issue, an Adaptive Voltage Regulation Scheme (AVRS) is presented in this article. The proposed method considers the number of high load connections, number of low load connections, no of commercial connections, no of household connections and so on. Based on the connection details, the method categorizes the micro grids into two categories like commercial support grid and household support grid. Based on the category of the grid identified, the method computes the Adaptive Voltage Rate (AVR) for various grids, which represent the voltage to be regulated for the grid at particular time. The AVRS scheme performs voltage regulation according to the value of AVR. This process is iterated at different time stamp of a day. This will be analyzed in different times like business hours and normal hours. Based on the AVR measured, the method performs voltage regulation and produces higher performance.

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Machine Learning Based Power Regulation for Smart Multi Storage Building

Mishra,

Choubey

2024

E3S Web of Conf.

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The problem of power regulation has been well studied and there exist number of approaches in regulating the power supply to multi storage buildings. Some of the method uses number of supply units present in each floor, and number of control units present in the floors of the building. However, they suffer to achieve higher performance in power regulation. To handle this issue, a Genetic Algorithm Based power regulation model (GAPRM) is presented in this paper. The model considers various factors like number of electric stoves, no of heater, no of iron, no of vacuum cleaner, no of television, no of hair dryer, no of refrigerator, no of electric kettle, no of microwave oven, no of washing machines and Voltage requirement of each towards power regulation. The model fetches the details of each storage level and identifies the set of all electric devices present in the floor. Using these details, the method converts them into feature vector. With the incoming voltage, the method applies genetic algorithm to identify maximum units can be triggered with the supply at each floor. The genetic algorithm generates number of mutations and for each mutation; the method computes the fitness value in the name of Smart Voltage Fitness (SVF) measure. Based on the value of SVF, the method populates a subset of population. For the selected population, the method computes Power Regulation Value (PRV). According to the value of PRV, specific voltage has been regulated to the specific storage. This will be iterated for each storage level of the building. The proposed method improves the performance of power regulation in smart multi storage building.

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An operational optimization method of regional multi-energy system considering thermal quasi-dynamic characteristics

Cited by 3 publications

References 11 publications

Dynamic pricing optimization for commercial subcontracting power suppliers engaging demand response considering building virtual energy storage

Dynamic pricing optimization for commercial subcontracting power suppliers engaging demand response considering building virtual energy storage

Adaptive Voltage Regulation Scheme for Improved Power Management in Metropolitan

Machine Learning Based Power Regulation for Smart Multi Storage Building

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