Smart grids: Another step towards competition, energy security and climate change objectives

By C. Clastres. 2011

378 citations recorded by the source corpus.

The deployment of smart grids in electricity systems has given rise to much interdisciplinary research. The new technology is seen as an additional instrument available to States to achieve targets for promoting competition, increasing the safety of electricity systems and combating climate change. But the boom in smart grids also raises many economic questions. Public policies will need to be adapted, firstly to make allowance for the potential gains from smart grids and the associated information flow, and secondly to regulate the new networks and act as an incentive for investors. The new competitive offerings and end-user pricing systems will contribute to improving allocative and productive efficiency, while minimizing the risks of market power. With real-time data on output and consumption, generators and consumers will be able to adapt to market conditions. Lastly smart grids will boost the development of renewable energy sources and new technologies, by assisting their integration and optimal use.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c94f9e6bf51b906b57445b74b2f549f344548633

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In Electrical and Electronic Engineering

Citations in the corpus

Deep neural networks for energy load forecasting (2017, background): “Smart grids demand an unprecedented level of flexibility in the way energy is generated and distributed to minimize energy wastage and optimize usage [1]-[3].”
Prosumer Communities and Relationships in Smart Grids: A Literature Review, Evolution and Future Directions (2018, background): “Analysis revealed that majority of the literature addresses costs issues [96–98], cyber security [76,99,100], regulatory aspects [97,101,102], customer privacy [3,103,104], and consumers’ perception [105–107].”
A comparison of innovation policy in the smart grid industry across the pacific: China and the USA (2013, background): “In addition, Clastres (2011) demonstrates that the expanding use of smart grids will raise several new policy issues.”
Peak electricity demand and the flexibility of everyday life (2014, background): “The UK’s load curve, and in particular the evening demand peak, present a particular challenge in this context in that the predicted need to move heating and transport onto the grid - envisaged as key features of the low carbon transition - may fall precisely during the peak period (Clastres, 2011).”
Building energy load forecasting using Deep Neural Networks (2016, background): “At the grid level, to minimizing the energy wastage and making the power generation and distribution more efficient, the future of the power grid is moving to a new paradigm of smart grids [5], [6].”