1,721,184 research outputs found
Delay-Tolerant Stochastic Algorithms for Parking Space Assignment
Get PDFThis paper introduces and illustrates some novel
stochastic policies that assign parking spaces to cars looking for
an available parking space. We analyze in detail both the main
features of a single park, i.e., how a car could conveniently decide
whether to try its luck at that parking lot or try elsewhere,
and the case when more parking lots are available, and how to
choose the best one. We discuss the practical requirements of
the proposed strategies in terms of infrastructure technology and
vehicles’ equipment and the mathematical properties of the proposed
algorithms in terms of robustness against delays, stability,
and reliability. Preliminary results obtained from simulations are
also provided to illustrate the feasibility and the potential of our
stochastic assignment policies
Optimal Distributed Consensus Algorithm for Fair V2G Power Dispatch in a Microgrid
Get PDFAmong the many motivations to encourage the use of Electric Vehicles (EVs) there is the attractive possibility to implement Vehicle-to-Grid (V2G) functionalities. They are attractive both for EV owners, who can sell their own energy to the grid when they do not need to travel, and also for the power grid, as the stored energy can be used to back-up the fluctuating energy produced from renewable sources or to improve the grid stability at critical times. In this paper we illustrate a distributed algorithm that solves the V2G problem in a fair manner, trying to achieve an optimal trade-off between power generation costs and inconvenience to the vehicle owner. Results are shown and discussed for a case study simulated in the OpenDSS power system environmen
Optimal Real-Time Distributed V2G and G2V Management of Electric Vehicles
No full textThis paper exploits the analogy between the electrical grid and modern communication networks to implement Electric
Vehicle (EV) battery charging scheduling algorithms inspired by popular communication network techniques. In preliminary
works, a similar approach was used to manage the Grid-to-Vehicle (G2V) active power flows. In this paper, we extend this
framework to both implement the Vehicle-to-Grid (V2G) concept and to provide reactive power compensation capabilities
that do not affect charging times. The ability of the proposed algorithms to optimally share the available/desired power in a
fair way, with minimum communication requirements, in a very uncertain, dynamically changing framework, is illustrated
through several examples for different scenarios of interest
Plug-and-Play Distributed Algorithms for Optimized Power Generation in a Microgrid
Get PDFThis paper introduces distributed algorithms that
share the power generation task in an optimised fashion among the several Distributed Energy Resources (DERs) within a microgrid.
We borrow certain concepts from communication network
theory, namely Additive-Increase-Multiplicative-Decrease
(AIMD) algorithms, which are known to be convenient in terms of communication requirements and network efficiency. We adapt the synchronised version of AIMD to minimise a cost utility function of interest in the framework of smart grids. We then implement the AIMD utility optimisation strategies in a realistic power network simulation in Matlab-OpenDSS environment, and we show that the performance is very close to the full communication centralised case
Optimal distributed power generation for thermal and electrical scheduling in a microgrid
No full textOn the preservation of co-positive Lyapunov functions under Padédiscretization for positive systems
Get PDFIn this paper the discretization of switched and
non-switched linear positive systems using Padé approximations
is considered. We show:
1) first order diagonal Padé approximation preserves both
linear and quadratic co-positive Lyapunov functions,
higher order transformations need an additional condition
on the sampling time1;
2) positivity need not be preserved even for arbitrarily small
sampling time for certain Padé approximations.
Sufficient conditions on the Padé approximations are given to
preserve positivity of the discrete-time system. Finally, some
examples are given to illustrate the efficacy of our results
A framework for real-time emissions trading in large-scale vehicle fleets
Get PDFIn this study a framework for the real-time trading of budgeted emission rights between a fleet of participating vehicles is presented. The trading problem is formulated as a utility maximisation or as a utility fairness problem, which can be solved in real time either in a centralised or in a distributed manner. In both cases, the authors illustrate the basic issues that arise when such a framework is realised in practice, and they show the efficacy of the approaches by providing several simulation examples and a realistic case study
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