Speaker: Daniel Gerbi Duguma from IFI, UiO.
Abstract:
Increasing integration of Distributed Energy Resources (DERs) such as grid connected solar, battery systems, and electric vehicles (EVs) offers both opportunities (such as enhanced grid efficiency and sustainability) and challenges (such as congestion management, voltage stability and peak shaving demand) for the local electricity distribution networks. In addressing these challenges, the Local Flexibility Markets (LFMs) have emerged as a promising solution to Distribution System Operators (DSOs) who are in need of flexibilities.
However, the success of LFMs depends on accurate forecasting by DSOs, as forecasting errors can disrupt the supply-demand balance in the distribution network, which may lead to potential grid instability and increased operational costs. To minimize these errors, the availability of high-quality, granular data from prosumers is essential. However, incorporating such data into the forecasting process is challenging due to privacy concerns and lack of incentives for data sharing.
This presentation outlines a work-in-progress research into a blockchain-assisted, privacy-preserving and data-constrained framework for LFMs. The framework aims to introduces an incentive system that rewards prosumers for flexibility services and willingness to share granular data through innovative market-clearing algorithms that integrate data-sharing preferences and flexibility offers. The reasearch work further envisions leveraging blockchain technology, combined with smart contracts, to ensures secure, transparent, and automated market operations including bid-offer matching, market clearing and settlement.