Data-driven dynamic harmonic model for modern household appliances

Xie, Xiangmin; Chen, Daolian

doi:10.1016/j.apenergy.2022.118759

Cited by 29 publications

(9 citation statements)

References 29 publications

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“…Authors in [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] developed mathematical techniques to solve energy management problem in SG. In [7], Mixed Integer Linear Programming (MILP) is developed to solve energy management problem for PAR and cost minimization.…”

Section: Mathematical Techniquesmentioning

confidence: 99%

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Optimal Demand-Side Management Using Flat Pricing Scheme in Smart Grid

Albogamy

Ashfaq

Hafeez³

et al. 2022

Processes

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This work proposes a framework to solve demand-side management (DSM) problem by systematically scheduling energy consumption using flat pricing scheme (FPS) in smart grid (SG). The framework includes microgrid with renewable energy sources (solar and wind), energy storage systems, electric vehicles (EVs), and building appliances like time flexible, power flexible, and base/critical appliances. For the proposed framework, we develop an ant colony optimization (ACO) algorithm, which efficiently schedules smart appliances, and EVs batteries charging/discharging with microgrid and without (W/O) microgrid under FPS to minimize energy cost, carbon emission, and peak to average ratio (PAR). An integrated technique of enhanced differential evolution (EDE) algorithm and artificial neural network (ANN) is devised to predict solar irradiance and wind speed for accurate microgrid energy estimation. To endorse the applicability of the proposed framework, simulations are conducted. Moreover, the proposed framework based on the ACO algorithm is compared to mixed-integer linear programming (MILP) and W/O scheduling energy management frameworks in terms of energy cost, carbon emission, and PAR. The developed ACO algorithm reduces energy cost, PAR, and carbon emission by 23.69%, 26.20%, and 15.35% in scenario I, and 25.09%, 31.45%, and 18.50% in scenario II, respectively, as compared to W/O scheduling case. The results affirm the applicability of the proposed framework in aspects of the desired objectives.

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Section: Mathematical Techniquesmentioning

confidence: 99%

“…Equation ( 25) shows solar irradiance. The Equation (26) shows charging levels like maximum and minimum. Equation (43) shows energy consumption of EVs considering arrival and departure time.…”

Section: Objective Functionmentioning

confidence: 99%

Optimal Demand-Side Management Using Flat Pricing Scheme in Smart Grid

Albogamy

Ashfaq

Hafeez³

et al. 2022

Processes

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“…In [27], a multi-agent simulator capable of emulating different profiles of consumes and equipment is proposed. In [28], a harmonic coupled dynamic admittance matrix model based on voltage and current data was established to predict the consumption of household appliances. In [29], a domestic energy management model that was based on time perspective theory was developed, incorporating energy storage devices and flexible and smart appliances.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of Household Appliances Power Consumption

et al. 2022

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The consumption of household appliances tends to increase. Therefore, the application of energy efficiency measurements is urgently needed to reduce the levels of power consumption. Over the last years, various methods have been used to predict household electricity consumption. As a novelty, this paper proposed a method of predicting the consumption of household appliances by evaluating statistical distributions (Kolmogorov–Smirnov Test and Pearson’s X2 test). To test the veracity of the evaluations, first, a set of random values was simulated for each hour, and their respective averages were calculated. These were compared with the averages of the real values for each hour. With the exception of HVAC during working days, great results were obtained. For the refrigerator, the maximum error was 3.91%, while for the lighting, it was 4.27%. At the point of consumption, the accuracy was even higher, with an error of 1.17% for the dryer while for the washing machine and dishwasher, their minimum errors were less than 1%. The error results confirm that the applied methodology is perfectly acceptable for modeling household appliance consumption and consequently predicting it. However, these consumptions can be only extrapolated to dwellings with similar surface areas and habitats.

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“…It can organically combine computer technology, communication technology, display technology, and control technology, connects different functions and local computers, and has the advantages of good monitoring performance, high reliability, good expansibility, and easy maintenance [7][8][9]. With the interconnection of cross-regional power grids and constraints from economy and technology, in order to make the full use of existing system resources, power grids are often forced to operate near the critical point, and the voltage stability margin is very low, which increases the probability of power accidents such as voltage collapse [10][11][12]. In order to ensure voltage quality and reactive power balance, and realize the optimal coordination between voltage stability and reactive power optimization, the automatic distributed control of indoor low-voltage electricity system has become an important measure [13,14].…”

Section: Introductionmentioning

confidence: 99%

Automatic Distributed Control Method for Indoor Low-Voltage Electricity Based on Modal Symmetry Algorithm

Lian

2022

International Transactions on Electrical Energy Systems

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The traditional control method has a low margin of indoor voltage stability, which can easily lead to voltage collapse, and the control effect is not ideal. An automatic distributed control method for indoor low-voltage electricity system based on modal symmetry algorithm is proposed. In order to improve the voltage stability margin, the decoupling between the indoor low-voltage electricity characteristics and regions was analyzed. Based on the analysis results, the decoupling between regions and the robustness to faults of the distributed zone scheme were considered comprehensively, and the modularity and the optimal zoning scheme were screened. Based on the principle of modal symmetry, the original data of the distributed control matrix of low-voltage electricity was obtained. Mean standardization method was used to standardize the matrix, so as to realize the distributed control of indoor low-voltage electricity. The experimental results show that the proposed method improves the margin of voltage stability, overcomes the drawbacks of traditional methods, and reduces the probability of voltage accidents. It shows that this method has higher flexibility, higher reliability, and higher application value as well as improving the automatic control level of voltage.

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Data-driven dynamic harmonic model for modern household appliances

Cited by 29 publications

References 29 publications

Optimal Demand-Side Management Using Flat Pricing Scheme in Smart Grid

Optimal Demand-Side Management Using Flat Pricing Scheme in Smart Grid

Modeling and Simulation of Household Appliances Power Consumption

Automatic Distributed Control Method for Indoor Low-Voltage Electricity Based on Modal Symmetry Algorithm

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