The deployment of distributed energy resources, combined with a more proactive demand side, is inducing a new paradigm in power system operation and electricity markets. Within a consumer-centric market framework, peer-to-peer approaches have gained substantial interest. Peer-to-peer markets rely on multi-bilateral direct negotiation among all players to match supply and demand, and with product differentiation. These markets can yield a complete mapping of exchanges onto the grid, hence allowing to rethink our approach to sharing costs related to usage of common infrastructure and services. We propose here to attribute such costs in a number of alternative ways that reflects different views on usage of the grid and on cost allocation, i.e., uniformly and based on the electrical distance between players. Since attribution mechanisms are defined in an exogenous manner and made transparent they eventually affect the trades of the market participants and related grid usage. The interest of our approach is illustrated on a test case using the IEEE 39 bus test system, underlying the impact of attribution mechanisms on trades and grid usage.
This article focuses on the computation time and precision of a linear 2D magnetic gear analytical model. Two main models of magnetic gears are studied: the first with an infinite relative permeability of yokes, and the second with a finite relative permeability of yokes. These models are based on the subdomain resolution of Laplace and Poisson equations. To accurately compute the magnetic field distribution, it is necessary to take into account certain harmonics of the various rings and other system harmonics due to modulation. Global system harmonics, which increase the value of computation time, must also be taken into account. If the magnetic gear has a high pole number, then computation time increases even more and no longer allows for system optimization. This article proposes to compute magnetic field distribution using different harmonic selection methods in order to significantly reduce the computation time for the magnetic torque without any loss of accuracy.
This article focuses on the design and optimization of magnetic and mechanical (structural) parts of magnetic gears for wind turbine applications. In particular, this design takes into account the structural aspects of magnetic gears as well as the system's mechanical constraints (deformation and stress). Geometric parameters have been optimized in order to minimize the material costs for a 3.9 MW, 15 rpm wind turbine. This optimization strategy includes both magnetostatic and mechanical stationary finite element analyses. Optimization results underscore the necessity to take mechanical constraints into account, especially for the fixed ferromagnetic pole pieces.
Peer-to-peer markets are a promising approach for integrating decentralized generation and prosumers into electricity markets. However, these markets require a very large number of messages to be exchanged in order to find a solution that respects the constraint of power balance in power systems. This study first establishes the shape of the compromise between communication costs and residual power imbalance resulting from a P2P market. Secondly alternative stopping criteria are proposed in order to reduce the cost of communication. The most effective approach is to ratify each trade independently using a threshold on its primary and dual residues, while continuing to negotiate the other trades. With the same residual imbalance, this stopping criterion results in a tenfold reduction of the number of messages exchanged on the basis of a Monte Carlo simulation. This reduction factor seems independent of the number of market participants.
This article deals with the dynamic behaviour of magnetic gear. This study is based on a nonlinear analytical model of magnetic gear which gives an analytical expression of the magnetic torque for a step disturbance. From this expression, various criteria will be defined in order to reach a good performance of the magnetic gear with step or sinusoidal disturbance. These results will be compared with a nonlinear simulation. Simulations show that it is possible to have, in a transitory regime, a load angle higher than the limit load angle maintaining a coupling between the low speed and the high speed rotor. Simulations will illustrate the importance of defining design rules based on the system application domain. A high power wind turbine (MW) example is proposed. In that case studies, loads generated by wind induce strong disturbances.
Abstract-Simultaneous development of photovoltaic generation and electric vehicles strengthens the solicitations on the electric power system. This paper investigates the possible synergy between these players to jointly improve the production predictability while ensuring a low carbon mobility. It stands for a step towards a quantification of its economic and environmental fallout. First a context is described for a PV-EV collaboration. Then this is gathered into an optimization problem. Grid commitment constraints, battery aging and mobility needs are here considered from the environmental point of view of equivalent primary energy. Finally, a resolution method is presented which achieve an time-efficient optimization of the power flow for each vehicle, based on upstream computed charging policies. It relies on a stochastic modeling of both vehicles availability and forecast error of the PV production. The resolution framework is the stochastic dynamic programming, coupled with on-line minimization so as to avoid the curse of dimensionality. The proposed resolution enables to compute optimal power flow for each vehicle, even among large fleets. The emphasis is here set on a versatile resolution method which could take over many detailed objective functions.
Simultaneous upcoming of photovoltaic generation and electric vehicles increases constraints on electric power system. This paper explores the possible synergy between these players so as to jointly improve the production predictability while ensuring a low carbon mobility. First a context is defined for this collaboration. It consists in the association of a photovoltaic producer and some electric vehicles owners so as to both manage the EV recharge and meet a day-ahead production commitment. Several currently studied questions such as commitment strategies or optimal charging can be transposed into the proposed context called collaborative system. Here, we mainly focus on its sizing in terms of PV rated power and number of vehicles. A simplified model of the system is thus realised, including a day ahead commitment and an optimal vehicle charging planning, based on deterministic vehicle characteristics.First results show a strong influence of the sizing on the potential added value of vehicles in this association. Then, we assess the impact of day-ahead production forecast quality by comparing persistence forecast with some meteorological data. It appears that other things remaining equal, an imprecise forecast will increase the optimal number of vehicles that are supposed to get into the collaborative system. Finally, the robustness of the charging planning is investigated.
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