Secure Real-Time Monitoring and Management of Smart Distribution Grid Using Shared Cellular Networks
Electricity production and distribution is facing two major changes. First, production is shifting from classical energy sources such as coal and nuclear power toward renewable resources such as solar and wind. Second, consumption in the low voltage grid is expected to grow significantly due to the expected introduction of electrical vehicles. The first step toward more efficient operational capabilities is to introduce an observability of the distribution system and allow for leveraging the flexibility of end connection points with manageable consumption, generation, and storage capabilities. Thanks to advanced measurement devices, management framework, and secure communication infrastructure developed in the FP7 SUNSEED project, the distribution system operator (DSO) now has full observability of the energy flows in the medium/low voltage grid. Furthermore, the prosumers are able to participate pro-actively and coordinate with the DSO and other stakeholders in the grid. The monitoring and management functionalities have strong requirements for communication latency, reliability, and security. This article presents novel solutions and analyses of these aspects for the SUNSEED scenario, where smart grid ICT solutions are pr
PMU-Based Estimation of Voltage-to-Power Sensitivity for Distribution Networks Considering the Sparsity of Jacobian Matrix
With increasing integration of various distributed energy resources, electric distribution networks are changing to an energy exchange platform. Accurate voltage-to-power sensitivities play a vital role in system operation and control. Relative to the off-line method, measurement-based sensitivity estimation avoids the errors caused by incorrect device parameters and changes in network topology. An online estimation of the voltage-to-power sensitivity based on phasor measurement units is proposed. The sparsity of the Jacobian matrix is fully used by reformulating the original least-squares estimation problem as a sparse-recovery problem via compressive sensing. To accommodate the deficiency of the existing greedy algorithm caused by the correlation of the sensing matrix, a modified sparse-recovery algorithm is proposed based on the mutual coherence of the phase angle and voltage magnitude variation vectors. The proposed method can ensure the accuracy of estimation with fewer measurements and can improve the computational efficiency. Case studies on the IEEE 33-node test feeder verify the correctness and effectiveness of the proposed method.
Wall-to-bed heat transfer in circulating fluidized beds
Heat Transfer from the wall of a circulating fluidized bed to the fast bed suspension has been investigated for several materials. The range of investigation includes dense and dilute phase fast fluidization and pneumatic transport. The overall heat transfer coefficient was found to be a function mainly of cross-sectional average suspension density. Effects of superficial velocity and solids mass flux were obscured by their interrelationship to the suspension density. Two models from the literature are evaluated using present and published data.