Game theory-based renewable multi-energy system design and subsidy strategy optimization

Liu, Zuming; Wang, Shukun; Lim, Mei Qi; Kraft, Markus; Wang, Xiaonan

doi:10.1016/j.adapen.2021.100024

Cited by 45 publications

(19 citation statements)

References 53 publications

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“…All particulars concerning decision making process and its models, methods as well as strategies that have been used in many research areas could be also applied in energy sustainability for Industry 4.0 (as presented in Table 2). Multi-criteria decision making (MCDA) model [87][88][89] Game Theory [90,91] Recognitionprimed model…”

Section: Prospect Theory In Decision Making In Energy 40mentioning

confidence: 99%

The Use of Prospect Theory for Energy Sustainable Industry 4.0

2021

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Industry 4.0 challenges facilities entrepreneurs to be competitive in the market in terms of energy by rational decision making. The goal of the paper is aimed at introducing Prospect Theory (PT) in Industry 4.0 for making decisions in order to select an optimal energy technology. To reach this goal, an approach for decision making on energy investment has been developed. In this paper, the authors have also provided a new opportunity to apply the new decision making method for strengthening Industry 4.0 by addressing energy concerns based on which rational decisions have been made. The study uses a fuzzy analytical hierarchy process for weighting the evaluation sub-criteria of energy technologies and a modified PT for making decisions related to the selection of one of the investigated technologies. The results show that it is possible to implement PT in Industry 4.0 via a decision making model for energy sustainability. Decision probability was achieved using a behavioral approach akin to Cumulative Prospect Theory (CPT) for the considered technology options. More specifically, the probability has created the same threshold-based decision possibilities. The authors used the case study method based on a company located in North America which produces hardwood lumber. The company uses a heating system containing natural gas-fired boilers. This study has also contributed to the literature on energy sustainable Industry 4.0 by demonstrating a new phenomenon/paradigm for energy sustainability-based Industry 4.0 through using PT. In this context, the main motivation of writing the article has been to promote energy sustainability via complex mechanisms and systems that involve interrelated functions.

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Section: Prospect Theory In Decision Making In Energy 40mentioning

confidence: 99%

The Use of Prospect Theory for Energy Sustainable Industry 4.0

2021

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“…Ref. [28] also addresses renewables issues by developing a game theory model for optimizing multi-energy system design and renewable subsidy strategies. A two-phase decarbonization pathway is recommended in ref.…”

Section: Introductionmentioning

confidence: 99%

“…A two-phase decarbonization pathway is recommended in ref. [28] , i.e., first focusing on increasing the integration of renewables and then imposing emissions limits. Such a framework proved to be highly effective and might be valuable in the context of the sustainable energy transition.…”

Section: Introductionmentioning

confidence: 99%

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Future assessment of the impact of the COVID-19 pandemic on the electricity market based on a stochastic socioeconomic model

et al. 2022

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“…The academic circles at home and abroad focus on the issue of carbon emission, which has won the strong support of governments all over the world. Facing this long-term and urgent carbon reduction goal, China has actively made response measures and put forward methods and ways to effectively reduce carbon dioxide emissions per unit of GDP [ 4 – 6 ].…”

Section: Introductionmentioning

confidence: 99%

Construction of Game Model between Carbon Emission Minimization and Energy and Resource Economy Maximization Based on Deep Neural Network

Ma¹,

Wang

2022

Computational Intelligence and Neuroscience

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Under this background, this paper tries to find countermeasures and ways for carbon reduction by observing and analyzing the influencing factors of carbon emissions, designing ways to minimize carbon emissions and maximize resources and energy. In view of the above problems, the carbon emission prediction research is closely combined with the research of deep neural network, the carbon emission prediction models based on deep neural network are established, respectively, and the game theory is introduced to maximize the resource economy. Based on the analysis of the cost of energy resources, this paper puts forward a model based on game theory and makes an overall planning of the bidding online auxiliary decision-making system in combination with the actual market demand. Build a big data analysis platform based on the Internet of things, collect the data related to carbon emission for normalization, analyze the influencing factors related to carbon emission by using the principal component analysis method, select the data with higher connection value, and take the time series data as the input of the deep neural network for simulation verification. The simulation results show that the game model of carbon emission minimization and energy resource economic maximization based on deep neural network can effectively improve the economic maximization of energy resources and reduce carbon emissions.

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Game theory-based renewable multi-energy system design and subsidy strategy optimization

Cited by 45 publications

References 53 publications

The Use of Prospect Theory for Energy Sustainable Industry 4.0

The Use of Prospect Theory for Energy Sustainable Industry 4.0

Future assessment of the impact of the COVID-19 pandemic on the electricity market based on a stochastic socioeconomic model

Construction of Game Model between Carbon Emission Minimization and Energy and Resource Economy Maximization Based on Deep Neural Network

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