Behavioral instruments in renewable energy and the role of big data: A policy perspective

Abstract

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Evolutionary Game Analysis of Co-Opetition Strategy in Energy Big Data Ecosystem under Government Intervention

“…The concept of co-opetition was proposed by Nalebuff and Brandenburger first [38]. They indicated that the essence of creating value is the process of cooperation, and the essence of striving for value is the process of competition [39]. When the cooperation strategy is adopted by the supply chain members, there will be problems of the benefit distribution and the contradiction between their interests and the overall interests [40].…”

Policy capacities and effective policy design: a review

“…An example of this latter context is the rise of ‘big data’ analytics that has also necessitated a parallel emphasis on big data readiness at all three levels of capacity (Clarke & Craft, 2017 ; Giest, 2017 ; Giest & Mukherjee, 2018 ; Golan et al, 2017 ). For example, policy responses to the Covid-19 pandemics in countries like Singapore have included combining mobile-phone-tower data and machine learning to develop social graphs that track propinquity to improve contact-tracing (The Economist, 2020 ; see also Woo, 2020 on the Singapore case).…”

Tackling the Risk of Stranded Electricity Assets with Machine Learning and Artificial Intelligence

“…Tackling the Risk of Stranded Electricity Assets with Machine Learning and Artificial Intelligence DOI: http://dx.doi.org /10.5772/intechopen.93488 expected that as this shift continues, new opportunities for ML and AI applications will become available, including in modeling consumer behavior and facilitating sustainable behavior change energy consumption action [3, 65,118,119], estimating and predicting the marginal emissions of residential energy utilization and thermal comfort in buildings in real time, on a scale of hours [57,118], and game-theoretic modeling and design of socially beneficial energy policies like social norms, public opinions, stakeholder engagement, and education efforts [120][121][122]. Other breakthrough innovations might displace fossil fuels leading to stranding, and creating opportunities for ML-based electricity pricing techniques and rate design to set dynamic pricing of carbon, electricity, and consumer choice [1,[123][124][125][126][127], and multiobjective optimization to compute Pareto-optimal solutions for climate engineering, climate informatics, and solar geoengineering [58,[128][129][130].…”