Machine Learning for Energy Systems

Sidorov, Denis; Liu, Fang; Sun, Yonghui

doi:10.3390/en13184708

Cited by 13 publications

(5 citation statements)

References 14 publications

(14 reference statements)

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“…Different multi-objective optimization approaches and state-of-the-art techniques are used for the selection of CES technologies [17][18][19][20][21], conversely, with numerous conflicting aspects. Stakeholders find it challenging to directly select a suitable CES strategic location for energy loss minimization in a local distribution system.…”

Section: Literature Review 21 Overview Of Community Energy Storage An...mentioning

confidence: 99%

Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach

Bhola,

Chronis,

Kotsampopoulos

et al. 2023

Energies

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This paper explores business models for community energy storage (CES) and examines their potential and feasibility at the local level. By leveraging Multi Criteria Decision Making (MCDM) approaches and real-world case studies in Europe and India, it presents insights into CES deployment opportunities, challenges, and best practices. Different business models, including community energy cooperatives, utility–community partnerships, demand response, energy services, and market mechanisms, are analyzed. The proposed method combines the MCDM method PROMETHEE II with the fuzzy set theory to obtain a complete CES business model ranking, addressing project uncertainties. The analysis emphasizes CES’s role in balancing local renewable energy supply and demand, facilitating energy sharing, and achieving energy independence. Findings prioritize models like Community Cooperative, Energy Arbitrage, and Energy Arbitrage Peak Shaving for CES with renewables. Environmental benefits include reduced diesel use and greenhouse gas emissions. Efficient cooperatives are advocated to recover costs and enable competitive energy prices. The paper highlights the need for novel value propositions to boost the energy transition in local communities. This research contributes to the discourse on CES business models, fostering knowledge exchange and promoting effective strategies for sustainable energy systems.

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Section: Literature Review 21 Overview Of Community Energy Storage An...mentioning

confidence: 99%

Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach

Bhola,

Chronis,

Kotsampopoulos

et al. 2023

Energies

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show abstract

“…The great role of vision and learning of machines, connected by the Internet of Things, in Surface Mining 4.0 makes it possible to move to a deep integration of drilling and blasting, excavation and loading, and transportation processes among themselves, as well as planning and management systems. It gives a chance to optimize the sequence of preparatory, overburdened, and mineral extraction operations in the dangerous and harmful zones performed in unmanned mode [98,99].…”

Section: Machine Vision and Learning Unmanned Systems In Surface Mini...mentioning

confidence: 99%

Development of Surface Mining 4.0 in Terms of Technological Shock in Energy Transition: A Review

Zhironkin

Taran

2023

Energies

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The expansion of end-to-end Industry 4.0 technologies in various industries has caused a technological shock in the mineral resource sector, wherein itsdigital maturity is lower than in the manufacturing sector. As a result of the shock, the productivity and profitability of raw materials extraction has begun to lag behind the industries of its deep processing, which, in the conditions of volatile raw materials markets, can provoke sectoral crises. The diffusion of Industry 4.0 technologies in the mining sector (Mining 4.0) can prevent a technological shock if they are implemented in all segments, including quarrying (Surface Mining 4.0). The Surface Mining 4.0 technological platform would connect the advanced achievements of the Fourth Industrial Revolution (end-to-end digital artificial intelligence technologies, cyber-physical systems and unmanned production with traditional geotechnology) without canceling them, but instead bringing them to a new level of productivity, resource consumption, and environmental friendliness. In the future, the development of Surface Mining 4.0 will provide a response to the technological shock associated with the acceleration of the digital modernization of the mining sector and the increase in labor productivity, which are reducing the operating costs of raw materials extraction. In this regard, the given review is an attempt to analyze the surface mining digital transformation over the course of the diffusion of Industry 4.0 technologies covered in scientific publications. The authors tried to show the core and frontiers of Surface Mining 4.0 development to determine the production, economic, and social effect of replacing humans with digital and cyber-physical systems in the processes of mineral extraction. Particular attention was paid to the review of research on the role of Surface Mining 4.0 in achieving sustainable development goals.

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“…Figure 1 shows the WEO-2021 scenario for CO 2 emissions. This review describes which methods should be used to achieve the goal [11]. Hydrogen is gaining popularity in many national and international climate strategies.…”

Section: Power-to-x Ineratec -Power To Liquidmentioning

confidence: 99%

A study of innovative technologies in the fuel and energy sector

Dyukova

Mongush

Haustovich

2022

IOP Conf. Ser.: Earth Environ. Sci.

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In our changing world, innovative technologies play an important role in the development of the fuel and energy industry. The use of green energy and the gradual abandonment of hydrocarbons are gaining popularity due to their negative impact on the environmental situation in the world. This phenomenon gives a new direction in the development of innovative technologies whose main purposes are to improve efficiency of energy consumption, to reduce costs and emissions into the atmosphere. The problems of the fuel and energy sector are serious, as this sector is a dangerous polluter of the environment. According to the Paris Agreement, governments have adopted laws and created zero-emission roadmaps to reduce emissions and support developing countries. The article describes innovative technologies that contribute to the development of the global fuel and energy sector, and forecasts when this sector will become environmentally friendly. At the current stage of development of the fuel and energy sector, the most popular energy source is hydrogen, as it is considered to be an incentive to improve efficiency of traditional energy consumption.

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Machine Learning for Energy Systems

Cited by 13 publications

References 14 publications

Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach

Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach

Development of Surface Mining 4.0 in Terms of Technological Shock in Energy Transition: A Review

A study of innovative technologies in the fuel and energy sector

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