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The School carries out applied research with the purpose of developing economically, legally, and socially-sound regulation and policy, using a multidisciplinary approach.

Independent aggregation in the nordic day-ahead market : what is the welfare impact of socializing supplier compensation payments?

This paper addresses the participation of independent aggregators (IAs) for demand response (DR) in European electricity markets. An IA is an aggregator trading the...

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Tim Schittekatte KB ZB
Article
Environmental insurance and resilience in the age of natural disasters
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Evaluating models of CO2 transport governance : from state-led to market-based approaches
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How can regulated electricity network companies promote innovation? : lessons from the field of practice

Electricity network companies can innovate their own network business or stimulate system innovation, including by facilitating market activities and the integration of renewable energy sources. Regulation is essential to turn this potential into reality by providing adequate incentives to network companies. Regulators can change the mandate of network companies, allow commercial activities that go beyond the regulated ones, or provide financial rewards and penalties associated with input or output-based measures of innovation. Regulators can also introduce sandboxes, where specific rules are relaxed and innovation can be tested. Experience accumulated in Europe and elsewhere after the liberalization of the electricity industry suggests that the type of targeted innovation matters: a regulatory measure can be effective in promoting one type of innovation but less so in promoting another one.

MEEUS, Leonardo; ROSSETTO, Nicolò, How can regulated electricity network companies promote innovation? : lessons from the field of practice, Jean-Michel GLACHANT, Paul L. JOSKOW and Michael POLLITT (eds), Handbook on electricity regulation, Cheltenham ; Northampton : Edward Elgar Publishing, 2025, pp. 371-385 - hdl.handle.net

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Tim Schittekatte KB ZB
Nicolò Rossetto TJ ML LS AS
ECSM
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