Digital Twins for Flexibility Service Provision from Industrial Energy Systems

Zhou, Yue; Su, Pengfei; Wu, Jianzhong; Sun, Weiqiang; Xu, Xiandong; Abeysekera, Muditha

doi:10.1109/dtpi52967.2021.9540158

Cited by 2 publications

(2 citation statements)

References 20 publications

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“…The authors of [14] concentrated on a steel plant and streamlined its scheduling with the goal of maximizing profits in both the energy and spinning reserve markets. The authors of [15] illustrated how digital twins hold promise in enabling the provision of flexibility services from industrial energy systems. Reference [16] proposed a data-driven procedure to support energyintensive industrial plants to offer energy flexibility in the joint energy and reserve market.…”

Section: A Literature Reviewmentioning

confidence: 99%

Optimal Medium-Term Electricity Procurement for Cement Producers

Arellano,

Carrión,

García-Cerezo

2024

IEEE Access

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In the current economic and energy situation, it is imperative for major electricity consumers to meticulously determine their electricity procurement. This is the case for cement producers. This work intends to determine the most efficient approach to electricity acquisition, considering their involvement in the electricity pool, power-purchase agreements, and the potential installation of a photovoltaic selfproduction unit and a battery storage system. To achieve this, we model the electricity consumption flexibility of cement producers, accounting for all production processes associated with cement and clinker manufacturing. This results in the formulation of a mid-term decision-making problem under uncertainty, which is addressed through the application of a two-stage risk-averse stochastic programming formulation. In order to reduce the computational size of the resulting optimization problem, the planning horizon is characterized by a set of representative periods obtained through a procedure based on chronological time-period clustering. To analyze the practical viability of the proposed approach, a realistic case study is solved featuring an existing cement producer, real-world energy pool prices, and data pertaining to renewable energy production. The findings derived from this case study highlight the viability of installing a photovoltaic self-production unit as a strategic measure to reduce the expected procurement expenses for the cement producer. Moreover, the photovoltaic self-production unit proves instrumental in mitigating the vulnerability to elevated procurement costs. It has been also observed that an imprecise modeling of the technical characteristics within the cement manufacturing processes can lead to a substantial underestimation of procurement costs.INDEX TERMS large electricity consumer, power purchase agreements, cement plant, self-generation facility, stochastic programming NOTATION

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Section: A Literature Reviewmentioning

confidence: 99%

Optimal Medium-Term Electricity Procurement for Cement Producers

Arellano,

Carrión,

García-Cerezo

2024

IEEE Access

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“…Aghazadeh Ardebili et al [36] used DTs as a tool to predict energy production in power systems with a high volume of RES. Zhou et al [37] highlighted the benefits of DTs for providing flexibility in industrial power systems.…”

Section: Consumer Digital Twinmentioning

confidence: 99%

Local Energy Market-Consumer Digital Twin Coordination for Optimal Energy Price Discovery under Thermal Comfort Constraints

et al. 2023

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The upward trend of adopting Distributed Energy Resources (DER) reshapes the energy landscape and supports the transition towards a sustainable, carbon-free electricity system. The integration of Internet of Things (IoT) in Demand Response (DR) enables the transformation of energy flexibility, originated by electricity consumers/prosumers, into a valuable DER asset, thus placing them at the center of the electricity market. In this paper, it is shown how Local Energy Markets (LEM) act as a catalyst by providing a digital platform where the prosumers’ energy needs and offerings can be efficiently settled locally while minimizing the grid interaction. This paper showcases that the IoT technology, which enables control and coordination of numerous devices, further unleashes the flexibility potential of the distribution grid, offered as an energy service both to the LEM participants as well as the external grid. This is achieved by orchestrating the IoT devices through a Consumer Digital Twin (CDT), which facilitates the optimal adjustment of this flexibility according to the consumers’ thermal comfort level constraints and preferences. An integrated LEM-CDT platform is introduced, which comprises an optimal energy scheduler, accounts for the Renewable Energy System (RES) uncertainty, errors in load forecasting, Day-Ahead Market (DAM) feed in/out the tariff, and a fair price settling mechanism while considering user preferences. The results prove that IoT-enabled consumers’ participation in the energy markets through LEM is flexible, cost-efficient, and adaptive to the consumers’ comfort level while promoting both energy transition goals and social welfare. In particular, the paper showcases that the proposed algorithm increases the profits of LEM participants, lowers the corresponding operating costs, addresses efficiently the stochasticity of both energy demand and generation, and requires minimal computational resources.

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Digital Twins for Flexibility Service Provision from Industrial Energy Systems

Cited by 2 publications

References 20 publications

Optimal Medium-Term Electricity Procurement for Cement Producers

Optimal Medium-Term Electricity Procurement for Cement Producers

Local Energy Market-Consumer Digital Twin Coordination for Optimal Energy Price Discovery under Thermal Comfort Constraints

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