This paper studies the impact of access to electricity via solar-powered home systems (SHSs) in rural communities in Peru. Applying propensity score matching at the community as well as at the household level, the authors find that households with SHSs spend less on traditional sources of...

The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study...

The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study...

The European Commission is introducing new regulations on submission and publication of data in electricity markets (SPDEM) and on wholesale energy market integrity and transparency (REMIT). I discuss issues relevant for undertaking an evaluation such regulations. I argue that, for market...

While achieving the ambitious energy transition targets is important to society, it is also costly. To keep these costs as low as possible and, thus, increase the chances of successfully accomplishing the energy transition, upholding the basic principles of the organisation of the electricity...

We analyse the drivers of European Power Exchange (EPEX) retail electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

The benefits of smoothing demand peaks in the electricity market has been widely recognised. European countries such Spain and some of the Scandinavian countries have recently given to the consumers the possibility to face the spot prices instead of having a fixed tariffs determined by...

We analyse the drivers of European Power Exchange (EPEX) wholesale electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

We analyse the drivers of European Power Exchange (EPEX) wholesale electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

In most wholesale electricity markets generators must submit step-function offers of supply to a uniform price auction, and the market is cleared at the price of the most expensive offer needed to meet realised demand. Such markets can most elegantly be modelled as the pure-strategy, Nash...