Artificial Intelligence for Electricity Supply Chain automation

Richter, Lucas; Lehna, Malte; Marchand, Sophie; Scholz, Christoph; Dreher, Alexander; Klaiber, Stefan; Lenk, Steve

doi:10.1016/j.rser.2022.112459

Cited by 46 publications

(16 citation statements)

References 134 publications

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“…The challenge of energy access can be broadly divided into three categories: energy production, predictive maintenance, and communication infrastructure [59,60]. AI techniques may outperform traditional models for energy production by defining local control strategies, automating the management of variable energy sources, and ensuring optimal continuous (incl.…”

Section: The Milestones Of the Lithuanian Artificial Intelligence Str...mentioning

confidence: 99%

A National Innovation System Concept-Based Analysis of Autonomous Vehicles’ Potential in Reaching Zero-Emission Fleets

Venkatesh,

Raslavičius

2024

Technologies

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Change management for technology adoption in the transportation sector is often used to address long-term challenges characterized by complexity, uncertainty, and ambiguity. Especially when technology is still evolving, an analysis of these challenges can help explore different alternative future pathways. Therefore, the analysis of development trajectories, correlations between key system variables, and the rate of change within the entire road transportation system can guide action toward sustainability. By adopting the National Innovation System concept, we evaluated the possibilities of an autonomous vehicle option to reach a zero-emission fleet. A case-specific analysis was conducted to evaluate the industry capacities, performance of R&D organizations, main objectives of future market-oriented reforms in the power sector, policy implications, and other aspects to gain insightful perspectives. Environmental insights for transportation sector scenarios in 2021, 2030, and 2050 were explored and analyzed using the COPERT v5.5.1 software program. This study offers a new perspective for road transport decarbonization research and adds new insights to the obtained correlation between the NIS dynamics and achievement of sustainability goals. In 2050, it is expected to achieve 100% carbon neutrality in the PC segment and ~85% in the HDV segment. Finally, four broad conclusions emerged from this research as a consequence of the analysis.

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Section: The Milestones Of the Lithuanian Artificial Intelligence Str...mentioning

confidence: 99%

A National Innovation System Concept-Based Analysis of Autonomous Vehicles’ Potential in Reaching Zero-Emission Fleets

Venkatesh,

Raslavičius

2024

Technologies

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“…and reinforcement learning (e.g., Markov decision process, Q-learning, deep deterministic policy gradient, etc.). Various surveys in the literature reviewed the applications of AI in smart grids that span from data pre-processing, anomaly detection, load/generation forecasting, stability analysis, to automated control [83], [84], [85]. Meanwhile, blockchain was also enhanced with AI techniques, where for instance the authors in [86] provided the design of a blockchain-based framework that utilized deep learning to protect smart grid network with an anomaly detection module.…”

Section: ) Big Data and Artificial Intelligencementioning

confidence: 99%

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

et al. 2022

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The concept of the internet of energy (IoE) emerged as an innovative paradigm to encompass all the complex and intertwined notions relevant to the transition of current smart grids towards more decarbonization, digitalization and decentralization. With a focus on the two last aspects, the amount of intelligent devices being connected in a scattered way to the existing power grid is ever-growing. Nevertheless, guaranteeing a cyber-secure and resilient control of these IoE components as well as a seamless and reliable delivery of electricity services, such as renewable energy exchange, electric vehicles charging, demand response, and so forth; might be the bottleneck of current power systems that are largely still functioning following a centralized approach. Thus, the future power grid would gradually incorporate a growing number of distributed-based control schemes to deal with this challenge. And many believe that blockchain could be a key-enabler in this transition, due to its consistent characteristics with multiple requirements of future power systems. In this paper, we provide an extensive state-of-the-art of blockchain-based additions to the IoE. Where, we first introduce various concepts related to blockchain and discuss the rationale behind its adoption in the context of IoE. Then, differently from the existing body of literature surveys, we do not only provide a taxonomy and evaluate a wide range of recent research outputs that integrated blockchain within modern power systems. But we also draw some valuable lessons learned for each studied category and discuss the intersection of blockchain with various emerging paradigms that have the potential of radically impacting the smart grid. In addition, we present some real-world industrial initiatives and ongoing projects built on top of blockchain, dedicated for offering diverse electricity services with a case study of a pilot project on energy trading in Amsterdam. Finally, we discuss the remaining challenges and worthwhile opportunities of deploying blockchain in this particular area, with a focus on the aspect of operational cyber-security.

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“…These businesses include power generation, electric power transmission, distribution of electricity, planning, and construction of electricity supply facilities, development of electricity supply, and sales of electricity. In the company's supply chain activities, electricity distribution activities are the final stage in the delivery of electric power, namely the process of delivering electricity from the electricity distribution system to the electricity consumers [1]. The distribution unit makes direct contact with the final consumer so that the success of the distribution unit affects the service to the customer.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the supply chain performance measurement system using the SCOR 12.0 and the value stream mapping method approach towards sustainability strategy (case study: power generation company in Indonesia)

Khair

Rini

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Indonesia’s electrical energy potential is very significant in supporting the manufacturing and service industries. The efforts of state power companies to manage their supply chain systems require a sustainable strategy to increase end-customer satisfaction in global competition. One strategy in achieving sustainable competence can be done through measuring and managing supply chain performance using the SCOR Method and Value Stream Mapping (VSM). The implementation of these two methods will be able to integrate every process and decision making in increasing productivity, especially in the company’s supply chain activities. Measurements result of the supply chain performance on XYZ Berau Company from 2019 to 2021 by implementing the SCOR 12.0 and the value stream mapping (VSM) method showed an increase, where the realization of supply chain performance in 2021 was 91.42 with a good category. However, there is still a gap in the KPI value of 8.58, where the highest Gap value is in KPI P-3 material fulfillment duration. For 2021, the Gap Value for KPI P-3 material fulfillment duration is 4.17 or 48.60% of the total existing gap. The application of the VSM method shows that for KPI P-3 material fulfillment duration, the value-added ratio current state is 63.57% with a value-added activity of 44.5 days, compared to the total process cycle time of 70 days. Research recommendations have brought improvement, resulting in the value-added ratio future state increased by 98.89%, with value-added activity for 44.5 days, from the total process cycle time of 45 days. So, the 45 days target for KPI P-3 material fulfillment duration can be achieved.

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Artificial Intelligence for Electricity Supply Chain automation

Cited by 46 publications

References 134 publications

A National Innovation System Concept-Based Analysis of Autonomous Vehicles’ Potential in Reaching Zero-Emission Fleets

A National Innovation System Concept-Based Analysis of Autonomous Vehicles’ Potential in Reaching Zero-Emission Fleets

A Taxonomy and Lessons Learned From Blockchain Adoption Within the Internet of Energy Paradigm

Analysis of the supply chain performance measurement system using the SCOR 12.0 and the value stream mapping method approach towards sustainability strategy (case study: power generation company in Indonesia)

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