Novel Functionalities of Smart Home Devices for the Elastic Energy Management Algorithm

Powroźnik, Piotr; Szcześniak, Paweł; Sobolewski, Łukasz; Piotrowski, Krzysztof

doi:10.3390/en15228632

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…It used thermal energy storage for the air conditioning. In [32], the authors proposed an energy management with new functionalities based on programing and postponing the activation of smart home appliances.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Energy Management in Microgrids Based on Different Load Types in Smart Buildings

et al. 2022

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This paper presents an energy management strategy (EMS) based on the Stackelberg game theory for the microgrid community. Three agents or layers are considered in the proposed framework. The microgrid cluster (MGC) refers to the agent that coordinates the interactions between the microgrids and the utility grid. The microgrid agent manages the energy scheduling of its own consumers. The third agent represents the consumers inside the microgrids. The game equilibrium point is solved between different layers and each layer will benefit the most. First, an algorithm performs demand response in each microgrid according to load models in smart buildings and determines the load consumption for each consumer. Then, each microgrid determines its selling price to the consumers and the amount of energy required to purchase from the utility grid to achieve the maximum profit. Finally, the balance point will be obtained between microgrids by the microgrid cluster agent. Moreover, the proposed method uses various load types at different times based on real-life models. The result shows that considering these different load models with demand response increased the profit of the user agent by an average of 22%. The demand response is implemented by the time of use (TOU) model and real-time pricing (RTP) in the microgrid.

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Section: Introductionmentioning

confidence: 99%

Optimizing Energy Management in Microgrids Based on Different Load Types in Smart Buildings

et al. 2022

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Quality evaluation of the forecasting system for the Polish Timescale by means of the Group Method of Data Handling type neural network

Sobolewski

2024

Engineering Applications of Artificial Intelligence

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An Elastic Energy Management Algorithm in a Hierarchical Control System with Distributed Control Devices

et al. 2022

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In modern Electric Power Systems, emphasis is placed on the increasing share of electricity from renewable energy sources (PV, wind, hydro, etc.), at the expense of energy generated with the use of fossil fuels. This will lead to changes in energy supply. When there is excessive generation from RESs, there will be too much energy in the system, otherwise, there will be a shortage of energy. Therefore, smart devices should be introduced into the system, the operation of which can be initiated by the conditions of the power grid. This will allow the load profiles of the power grid to be changed and the electricity supply to be used more rationally. The article proposes an elastic energy management algorithm (EEM) in a hierarchical control system with distributed control devices for controlling domestic smart appliances (SA). In the simulation part, scenarios of the algorithm’s operation were carried out for 1000 households with the use of the distribution of activities of individual SAs. In experimental studies, simplified results for three SA types and 100 devices for each type were presented. The obtained results confirm that, thanks to the use of SAs and the appropriate algorithm for their control, it is possible to change the load profile of the power grid. The efficacious operation of SAs will be possible thanks to the change of habits of electricity users, which is briefly described in the article.

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Novel Functionalities of Smart Home Devices for the Elastic Energy Management Algorithm

Cited by 6 publications

References 18 publications

Optimizing Energy Management in Microgrids Based on Different Load Types in Smart Buildings

Optimizing Energy Management in Microgrids Based on Different Load Types in Smart Buildings

Quality evaluation of the forecasting system for the Polish Timescale by means of the Group Method of Data Handling type neural network

An Elastic Energy Management Algorithm in a Hierarchical Control System with Distributed Control Devices

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