Forecasting in Blockchain-Based Local Energy Markets

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10406273" target="_blank" >RIV/00216208:11320/19:10406273 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=u.2EOV0thb" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=u.2EOV0thb</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/en12142718" target="_blank" >10.3390/en12142718</a>

Result language

angličtina

Original language name

Forecasting in Blockchain-Based Local Energy Markets

Original language description

Increasingly volatile and distributed energy production challenges traditional mechanisms to manage grid loads and price energy. Local energy markets (LEMs) may be a response to those challenges as they can balance energy production and consumption locally and may lower energy costs for consumers. Blockchain-based LEMs provide a decentralized market to local energy consumer and prosumers. They implement a market mechanism in the form of a smart contract without the need for a central authority coordinating the market. Recently proposed blockchain-based LEMs use auction designs to match future demand and supply. Thus, such blockchain-based LEMs rely on accurate short-term forecasts of individual households&apos; energy consumption and production. Often, such accurate forecasts are simply assumed to be given. The present research tested this assumption by first evaluating the forecast accuracy achievable with state-of-the-art energy forecasting techniques for individual households and then, assessing the effect of prediction errors on market outcomes in three different supply scenarios. The evaluation showed that, although a LASSO regression model is capable of achieving reasonably low forecasting errors, the costly settlement of prediction errors can offset and even surpass the savings brought to consumers by a blockchain-based LEM. This shows that, due to prediction errors, participation in LEMs may be uneconomical for consumers, and thus, has to be taken into consideration for pricing mechanisms in blockchain-based LEMs.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GX19-28231X" target="_blank" >GX19-28231X: DyMoDiF - Dynamic Models for the Digital Finance</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Energies

ISSN

1996-1073

e-ISSN

—

Volume of the periodical

12

Issue of the periodical within the volume

14

Country of publishing house

CH - SWITZERLAND

Number of pages

27

Pages from-to

2718

UT code for WoS article

000478999400078

EID of the result in the Scopus database

2-s2.0-85069612424