A Framework for Enabling Manufacturing Flexibility and Optimizing Industrial Demand Response Services

Wan, Paul Kengfai; Ranaboldo, Matteo; Burgio, Alessandro; Caccamo, Chiara; Fragapane, Giuseppe

doi:10.1007/978-3-031-43688-8_44

IFIP Advances in Information and Communication Technology

2023

DOI: 10.1007/978-3-031-43688-8_44

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A Framework for Enabling Manufacturing Flexibility and Optimizing Industrial Demand Response Services

Paul Kengfai Wan,

Matteo Ranaboldo,

Alessandro Burgio

et al.

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2024

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Cited by 1 publication

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Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling

Taltavull-Villalonga,

Bullich-Massagué,

Saldaña-González

et al. 2024

Electricity

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The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the efficiency and reliability of electricity distribution. In order to mitigate these congestions, novel approaches by using flexibility sources such as battery energy storage can be used. This involves the use of battery storage systems to absorb excess energy at times of low demand and release it at peak times, effectively balancing the load and reducing the stress on the grid. In this paper, two optimal power flow formulations are discussed: the branch flow model (non-convex) and the relaxed bus injection model (convex). These formulations determine the optimal operation of the flexibility sources, i.e., battery energy storage, with the objective of minimizing power losses while avoiding congestions. Furthermore, a comparison of the performance of these two formulations is performed, analyzing the objective function results and the flexibility operation. For this purpose, a real Spanish distribution network with its corresponding load data for seven days has been used.

show abstract

Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling

Taltavull-Villalonga,

Bullich-Massagué,

Saldaña-González

et al. 2024

Electricity

View full text Add to dashboard Cite

show abstract

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A Framework for Enabling Manufacturing Flexibility and Optimizing Industrial Demand Response Services

Cited by 1 publication

References 55 publications

Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling

Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling

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