Charging Games in Networks of Electrical Vehicles

In this paper, a static non-cooperative game formulation of the problem of distributed charging in electrical vehicle (EV) networks is proposed. This formulation allows one to model the interaction between several EV which are connected to a common residential distribution transformer. Each EV aims at choosing the time at which it starts charging its battery in order to minimize an individual cost which is mainly related to the total power delivered by the transformer, the location of the time interval over which the charging operation is performed, and the charging duration needed for the considered EV to have its battery fully recharged. As individual cost functions are assumed to be memoryless, it is possible to show that the game of interest is always an ordinal potential game. More precisely, both an atomic and nonatomic versions of the charging game are considered. In both cases, equilibrium analysis is conducted. In particular, important issues such as equilibrium uniqueness and efficiency are tackled. Interestingly, both analytical and numerical results show that the efficiency loss due to decentralization (e.g., when cost functions such as distribution network Joule losses or life of residential distribution transformers when no thermal inertia is assumed) induced by charging is small and the corresponding "efficiency", a notion close to the Price of Anarchy, tends to one when the number of EV increases.Comment: 8 pages, 4 figures, keywords: Charging games - electrical vehicle - distribution networks - potential games - Nash equilibrium - price of anarch

Minimizing the impact of EV charging on the electricity distribution network

The main objective of this paper is to design electric vehicle (EV) charging policies which minimize the impact of charging on the electricity distribution network (DN). More precisely, the considered cost function results from a linear combination of two parts: a cost with memory and a memoryless cost. In this paper, the first component is identified to be the transformer ageing while the second one corresponds to distribution Joule losses. First, we formulate the problem as a non-trivial discrete-time optimal control problem with finite time horizon. It is non-trivial because of the presence of saturation constraints and a non-quadratic cost. It turns out that the system state, which is the transformer hot-spot (HS) temperature here, can be expressed as a function of the sequence of control variables; the cost function is then seen to be convex in the control for typical values for the model parameters. The problem of interest thus becomes a standard optimization problem. While the corresponding problem can be solved by using available numerical routines, three distributed charging policies are provided. The motivation is threefold: to decrease the computational complexity; to model the important scenario where the charging profile is chosen by the EV itself; to circumvent the allocation problem which arises with the proposed formulation. Remarkably, the performance loss induced by decentralization is verified to be small through simulations. Numerical results show the importance of the choice of the charging policies. For instance, the gain in terms of transformer lifetime can be very significant when implementing advanced charging policies instead of plug-and-charge policies. The impact of the accuracy of the non-EV demand forecasting is equally assessed.Comment: 6 pages, 3 figures, keywords: electric vehicle charging, electricity distribution network, optimal control, distributed policies, game theor

Occurrence of transparent exopolymer particles (TEP) through drinking water treatment plants

Numerous membrane fouling studies have been conducted to predict and prevent membrane fouling. It was only recently that a new parameter, TEP, was introduced in this research. The deposition of TEP on reverse osmosis (RO) membranes has already been imaged, correlations between ultrafiltration (UF) fouling and TEP concentrations have been reported. Furthermore, TEP deposition takes place in an early stage of biofilms formation, making TEP one of the accused in search for biofilm initiation factors. After literature reporting about TEP in marine, surface and wastewater, this is the first research focusing on TEP through in drinking water. Each treatment step in three completely different drinking water production plants was evaluated on TEP removal and it could be concluded that a limited restfraction or no TEP could reach the drinking water. Coagulation + sand filtration proved efficient in strongly reducing TEP levels, UF + RO can provide a total TEP removal

Occurrence of transparent exopolymer particles (TEP) in drinking water systems

Numerous membrane fouling studies have been conducted to predict and prevent membrane fouling. It was only recently that a new parameter, TEP, was introduced in this research. The deposition of TEP on reverse osmosis (RO) membranes has already been imaged, correlations between ultrafiltration (UF) fouling and TEP concentrations have been reported. Furthermore, TEP deposition takes place in an early stage of aquatic biofilm formation, making TEP one of the accused in search for biofilm initiation factors. After literature reporting about TEP in marine, surface and wastewater, this is the very first research focusing on TEP through in drinking water. Every single treatment step in three completely different drinking water production plants was scored on TEP removal. It could be concluded that TEP concentrations were very dependent of the raw water source but in none of the installations, TEP was able to reach the final drinking water in significant concentrations. The combination of coagulation and sand filtration proved efficient in strongly reducing TEP levels, while the combination of UF and RO could provide a total TEP removal

Sensitivity analysis of a simulation model for evaluating renewable distributed generation on a power network

International audienceWe present a sensitivity analysis of a simulation model for the evaluation of the performance of a renewable distributed generation (DG) network. Uncertainties in renewable energy sources, components failure and repair events, loads and grid power supply are taken into account. The sensitivity analysis is performed individually with respect to the characteristic uncertain variables associated to each type of DG technology available. The impact of these uncertain variables is evaluated in terms of two performance functions, global cost (C g) and energy not supplied (ENS). The results show the trends of performance of the DG-integrated network under different conditions. This allows evaluating the impact of the different DG technologies