6,304 research outputs found
An Approximately Optimal Algorithm for Scheduling Phasor Data Transmissions in Smart Grid Networks
In this paper, we devise a scheduling algorithm for ordering transmission of
synchrophasor data from the substation to the control center in as short a time
frame as possible, within the realtime hierarchical communications
infrastructure in the electric grid. The problem is cast in the framework of
the classic job scheduling with precedence constraints. The optimization setup
comprises the number of phasor measurement units (PMUs) to be installed on the
grid, a weight associated with each PMU, processing time at the control center
for the PMUs, and precedence constraints between the PMUs. The solution to the
PMU placement problem yields the optimum number of PMUs to be installed on the
grid, while the processing times are picked uniformly at random from a
predefined set. The weight associated with each PMU and the precedence
constraints are both assumed known. The scheduling problem is provably NP-hard,
so we resort to approximation algorithms which provide solutions that are
suboptimal yet possessing polynomial time complexity. A lower bound on the
optimal schedule is derived using branch and bound techniques, and its
performance evaluated using standard IEEE test bus systems. The scheduling
policy is power grid-centric, since it takes into account the electrical
properties of the network under consideration.Comment: 8 pages, published in IEEE Transactions on Smart Grid, October 201
Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid
Recently there has been increasing interest in improving smart grids
efficiency using computational intelligence. A key challenge in future smart
grid is designing Optimal Power Flow tool to solve important planning problems
including optimal DG capacities. Although, a number of OPF tools exists for
balanced networks there is a lack of research for unbalanced multi-phase
distribution networks. In this paper, a new OPF technique has been proposed for
the DG capacity planning of a smart grid. During the formulation of the
proposed algorithm, multi-phase power distribution system is considered which
has unbalanced loadings, voltage control and reactive power compensation
devices. The proposed algorithm is built upon a co-simulation framework that
optimizes the objective by adapting a constriction factor Particle Swarm
optimization. The proposed multi-phase OPF technique is validated using IEEE
8500-node benchmark distribution system.Comment: IEEE PES GM 2014, Washington DC, US
Paradigm and paradox in topology control of power grids
Corrective Transmission Switching can be used by the grid operator to relieve line overloading and voltage violations, improve system reliability, and reduce system losses. Power grid optimization by means of line switching is typically formulated as a mixed integer programming problem (MIP). Such problems are known to be computationally intractable, and accordingly, a number of heuristic approaches to grid topology reconfiguration have been proposed in the power systems literature. By means of some low order examples (3-bus systems), it is shown that within a reasonably large class of “greedy” heuristics, none can be found that perform better than the others across all grid topologies. Despite this cautionary tale, statistical evidence based on a large number of simulations using IEEE 118-bus systems indicates that among three heuristics, a globally greedy heuristic is the most computationally intensive, but has the best chance of reducing generation costs while enforcing N-1 connectivity. It is argued that, among all iterative methods, the locally optimal switches at each stage have a better chance in not only approximating a global optimal solution but also greatly limiting the number of lines that are switched.First author draf
EV charging stations and RES-based DG: A centralized approach for smart integration in active distribution grids
Renewable Energy Sources based (RES-based) Dispersed Generation (DG) and Electrical Vehicles (EVs) charging systems diffusion is in progress in many Countries around the word. They have huge effects on the distribution grids planning and operation, particularly on MV and LV distribution grids. Many studies on their impact on the power systems are ongoing, proposing different approaches of managing. The present work deals with a real application case of integration of EVs charging stations with ES-based DG. The final task of the integration is to be able to assure the maximum utilization of the distribution grid to which both are connected, without any upgrading action, and in accordance with Distribution System Operators (DSOs) needs. The application of the proposed approach is related to an existent distribution system, owned by edistribuzione, the leading DSO in Italy. Diverse types of EVs supplying stations, with diverse diffusion scenarios, have been assumed for the case study; various Optimal Power Flow (OPF) models, based on diverse objective functions, reflecting DSO necessities, have been applied and tried. The obtained results demonstrate that a centralized management approach by the DSO, could assure the respect of operation limits of the system in the actual asset, delaying or avoiding upgrading engagements and charges
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