Optimal Location of Energy Storage Systems with Robust Optimization

The integration of intermittent sources of energy and responsive loads in distribution system make the traditional deterministic optimization-based optimal power flow no longer suitable for finding the optimal control strategy for the power system operation. This paper presents a tool for energy storage planning in the distribution network based on AC OPF algorithm that uses a convex relaxation for the power flow equations to guarantee exact and optimal solutions with high algorithmic performances and exploits robust optimization approach to deal with the uncertainties related to renewables and demand. The proposed methodology is applied for storage planning on a distribution network that is representative of a class of networks

Data analytics for profiling low‐voltage customers with smart meter readings

The energy transition for decarbonization requires consumers’ and producers’ active par-ticipation to give the power system the necessary flexibility to manage intermittency and non‐pro-grammability of renewable energy sources. The accurate knowledge of the energy demand of every single customer is crucial for accurately assessing their potential as flexibility providers. This topic gained terrific input from the widespread deployment of smart meters and the continuous development of data analytics and artificial intelligence. The paper proposes a new technique based on advanced data analytics to analyze the data registered by smart meters to associate to each customer a typical load profile (LP). Different LPs are assigned to low voltage (LV) customers belonging to nominal homogeneous category for overcoming the inaccuracy due to non‐existent coincident peaks, arising by the common use of a unique LP per category. The proposed methodology, starting from two large databases, constituted by tens of thousands of customers of different categories, clusters their consumption profiles to define new representative LPs, without a priori preferring a specific clustering technique but using that one that provides better results. The paper also proposes a method for associating the proper LP to new or not monitored customers, considering only few features easily available for the distribution systems operator (DSO)

Gauss-Bonnet gravity renders negative tension braneworlds unstable

We show that the Gauss-Bonnet correction to Einstein gravity induces a gravitational tachyon mode, namely an unstable spin 2 fluctuation, in the Randall-Sundrum I model. We demonstrate that this instability is generically related to the presence of a negative tension brane in the set-up, with or without $Z_2$-symmetry across it. Indeed it is shown that the tachyon mode is a bound state localised on any negative tension brane of co-dimension one, embedded in anti-de Sitter background. We discuss the possible resolution of this instability by the inclusion of induced gravity terms on the branes or by an effective four-dimensional cosmological constant.Comment: published versio