Investigation on electric load peak and valley characters and demand response evaluation based on spectral analysis

Cheng, Yu; Dong, Nan; Ren, Yong

doi:10.1109/apap.2011.6180571

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…For spray tower, since liquid area (slurry pond) contains gas phase and gas phase area contains slurry, there is no clear boundary between them. Indirect measurement method is commonly used at present which is that liquid level of absorption tower is calculated by making use of the density of slurry and pressure of certain liquid level [3] . Fig.…”

Section: Current Measuring Methods Of Absorption Tower Liquid Levelmentioning

confidence: 99%

New Method for Measuring Liquid Level in WFGD System

Tan

Liu

2011

AMR

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Traditional method for measuring liquid level of absorption tower in wet flue gas desulfurization (WFGD) system is introduced in this paper, and it's found that measuring accuracy of the method exists in large deviation. A new method is proposed to measure liquid level of absorption tower for this situation. The local test results show that not only measurement result of new method is more close to the actual liquid level than traditional method, but also using new method can save operation cost and ensure the safety, stability, and economic operation of WFGD system.

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Section: Current Measuring Methods Of Absorption Tower Liquid Levelmentioning

confidence: 99%

New Method for Measuring Liquid Level in WFGD System

Tan

Liu

2011

AMR

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“…IBP assume that users are separately or conjointly committed to lower their consumption during a certain peak time period. Price based and incentive based methods are collectively called hybrid DR program [19][20][21][22][23].…”

Section: Market and Remunerationmentioning

confidence: 99%

A demand side management control strategy using Whale optimization algorithm

Sharma

2019

SN Appl. Sci.

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In recent years, demand side management programs are in the spotlight due to the evolution of the smart grid and consumer-centric policies. Demand side management program contains many objectives one of the prime objective is to manage energy demand by certain change in consumer demand. This can be achieved by various methods such as financial discount and change in behavior through imparting education to support the stressed conditions of the grid. This paper demonstrates demand side management strategies based upon strategic conservation, peak clipping and load shifting techniques for future smart grids. The grid contains large number of controllable devices. The day before strategic conservation, peak clipping and load shifting techniques discussed in this paper are mathematically derived for minimization problem. A heuristic-based Whale optimization algorithm (WOA) was developed for solving this problem of minimization. Simulations are conducted on a test smart grid that contains a variation in loads in two service areas, one with residential consumers, and another with commercial consumers. WOA proves its efficacy by comparing the results with spider monkey optimization and biogeography based optimization. The simulation results show that proposed demand side management strategies achieve substantial savings, while reducing the peak load demand of the smart grid.

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“…(ii) On the other hand, the optimization objective-oriented methods allow for the allocation of periods to achieve the interests of policy maker. To reflect the connection between period partition and demand response, and maximize the utility of TOU, Literature [25] proposes the index of demand response to modify the period partition obtained only based on the membership functions. Literature [26] identifies valley periods by analyzing the redundancy of new energy generation, which can give full play to the demand response resources and promote renewable energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Time-of-Use Period Partition Based on Improved Fuzzy C-Means and Abnormal Period Correction

Wang,

Ma,

Ling

et al. 2023

Preprint

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In time-of-use tariff period partition, clustering algorithms are commonly used. However, as load demands become more diverse in this big data era, large amount of non-linear data makes conventional clustering algorithms methods no longer be applicable in this field alone. Facing high-time-resolution daily load data with strong non-linearity, we propose a new method to partition periods. It consists of an improved fuzzy c-means clustering algorithm and a correction method for abnormal periods. Firstly, we propose modified fuzzy membership functions to improve the initialization of clustering for operation efficiency. Secondly, the method for calculating the fuzzy parameters based on the loss function is given. Thirdly, the initial period partition is obtained by the improved clustering. Next, the recognition model and fuzzy subsethood-based correction model for abnormal periods are structed, then the corrected period partition is confirmed. Finally, the effectiveness of the proposed methods is verified by two daily load data with a time resolution of 5 minutes.

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Investigation on electric load peak and valley characters and demand response evaluation based on spectral analysis

Cited by 7 publications

References 3 publications

New Method for Measuring Liquid Level in WFGD System

New Method for Measuring Liquid Level in WFGD System

A demand side management control strategy using Whale optimization algorithm

Time-of-Use Period Partition Based on Improved Fuzzy C-Means and Abnormal Period Correction

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