60,753 research outputs found
Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems
© 2017 IEEE. This brief proposes a new convex model predictive control (MPC) strategy for dynamic optimal power flow between battery energy storage (ES) systems distributed in an ac microgrid. The proposed control strategy uses a new problem formulation, based on a linear d-q reference frame voltage-current model and linearized power flow approximations. This allows the optimal power flows to be solved as a convex optimization problem, for which fast and robust solvers exist. The proposed method does not assume that real and reactive power flows are decoupled, allowing line losses, voltage constraints, and converter current constraints to be addressed. In addition, nonlinear variations in the charge and discharge efficiencies of lithium ion batteries are analyzed and included in the control strategy. Real-time digital simulations were carried out for an islanded microgrid based on the IEEE 13 bus prototypical feeder, with distributed battery ES systems and intermittent photovoltaic generation. It is shown that the proposed control strategy approaches the performance of a strategy based on nonconvex optimization, while reducing the required computation time by a factor of 1000, making it suitable for a real-time MPC implementation
Distributed reactive power feedback control for voltage regulation and loss minimization
We consider the problem of exploiting the microgenerators dispersed in the
power distribution network in order to provide distributed reactive power
compensation for power losses minimization and voltage regulation. In the
proposed strategy, microgenerators are smart agents that can measure their
phasorial voltage, share these data with the other agents on a cyber layer, and
adjust the amount of reactive power injected into the grid, according to a
feedback control law that descends from duality-based methods applied to the
optimal reactive power flow problem. Convergence to the configuration of
minimum losses and feasible voltages is proved analytically for both a
synchronous and an asynchronous version of the algorithm, where agents update
their state independently one from the other. Simulations are provided in order
to illustrate the performance and the robustness of the algorithm, and the
innovative feedback nature of such strategy is discussed
Improving the Performance of Low Voltage Networks by an Optimized Unbalance Operation of Three-Phase Distributed Generators
This work focuses on using the full potential of PV inverters in order to improve the efficiency of low voltage networks. More specifically, the independent per-phase control capability of PV three-phase four-wire inverters, which are able to inject different active and reactive powers in each phase, in order to reduce the system phase unbalance is considered. This new operational procedure is analyzed by raising an optimization problem which uses a very accurate modelling of European low voltage networks. The paper includes a comprehensive quantitative comparison of the proposed strategy with two state-of-the-art methodologies to highlight the obtained benefits. The achieved results evidence that the proposed independent per-phase control of three-phase PV inverters improves considerably the network performance contributing to increase the penetration of renewable energy sources.Ministerio de EconomĂa y Competitividad ENE2017-84813-R, ENE2014-54115-
A goal programming methodology for multiobjective optimization of distributed energy hubs operation
This paper addresses the problem of optimal energy flow management in multicarrier energy networks
in the presence of interconnected energy hubs. The overall problem is here formalized by a nonlinear
constrained multiobjective optimization problem and solved by a goal attainment based methodology.
The application of this solution approach allows the analyst to identify the optimal operation state of the
distributed energy hubs which ensures an effective and reliable operation of the multicarrier energy
network in spite of large variations of load demands and energy prices. Simulation results obtained on
the 30 bus IEEE test network are presented and discussed in order to demonstrate the significance and
the validity of the proposed method
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