The European Union is implementing ambitious programs to tackle energy efficiency, energy independence, and climate change challenges. To reach the 20/20/20 targets, the EU aims at modernizing power grids to make them 'smart' by collecting close to real-time data and subsequently operate grids more optimally. One of the smart grid purposes is to integrate a growing share of renewable generation while efficiently accommodating their variability and limited predictability through the actuation of consumer flexibility. Hence, the success of energy programs relies on customer involvement in altering their energy consumption through the use of analytics and incentive-based demand-side management. The rollout of smart meters throughout Europe should provide the necessary information to implement them. This is without accounting for a possible backlash of customers in response to bad practices of utilitie when it comes to digitization and smart meter rollout, also associated with the potential distrust of digital products. Beyond legal binds and technical obstacles, the possible ways of handling the rollout of smart meters and metering, which defines the relationship between customers and utilities, are multiple. However, only the practices that exhibit ethical behavior of the utilities towards customers, and consider them as stakeholders in smart grids will lead to a fruitful and long-lasting relationship between customers and utilities.

No abstract

No abstract

Abstract-Increased emphasis is placed today on various types of demand response, motivated by the integration of renewable energy generation and efficiency improvements in electricity markets. Some advocated for the development of price-based approaches, where the conditional dynamic elasticity of final users is exploited in the power system, e.g. for system balancing. However, very few real-world experiments have been carried out and price-based demand response has consistently been found difficult to assess and quantify. It is our aim here to describe an approach to do so, as motivated by the large-scale EcoGrid EU experiment. In this project, 1900 houses were equipped with smart meters and other automation devices in order to adapt consumption to real-time electricity prices every five minutes, while monitoring it with the same resolution. Our approach first relies on the clustering of residential load observations that behave similarly within a given experiment. Then, a clinical testing approach, based on a test and a control group, is adapted to assess whether price-responsive loads were actually responsive or not. Interestingly, in the deployment phase of the project, the results show that houses could be deemed price-responsive on some test days, while results were inconclusive on some others.

No abstract