Loss allocation in a distribution system with distributed generation units

In Denmark, a large part of the electricity is produced by wind turbines and combined heat and power plants (CHPs). Most of them are connected to the network through distribution systems. This paper presents a new algorithm for allocation of the losses in a distribution system with distributed generation. The algorithm is based on a reduced impedance matrix of the network and current injections from loads and production units. With the algorithm, the effect of the covariance between production and consumption can be evaluated. To verify the theoretical results, a model of the distribution system in Brønderslev in Northern Jutland, including measurement data, has been studied

Projection of primary and revision hip arthroplasty surgery in Denmark from 2020 to 2050

BACKGROUND AND PURPOSE: The incidence of primary and revision total hip arthroplasty (THA) has increased over the last decades. Previous forecasts from different healthcare systems have predicted a continuous increase. We present a forecast of both primary and revision surgery from 2020 to 2050 based on 25 years data from the healthcare system in Denmark. PATIENTS AND METHODS: We retrieved data from the Danish Hip Arthroplasty Register on 198,835 primary and 29,456 revision surgeries. Historical censuses and population forecasts were retrieved from Statistics Denmark. Logistic and Gompertz regression analysis was used to forecast incidence rates (IR) and total numbers in the next 30 years. RESULTS: Our forecast predicts an increase in IR of 3–9% and an increase in total numbers of primary THA of between 12% and 19% in 2050. For revision THA the IRs have reached a plateau but total numbers are predicted to increase by 19% in 2050. CONCLUSION: Our forecast shows that both primary and revision THA will increase in total numbers in the next decades, but the IR for primary THA is near its plateau and for revision THA the plateau has already been reached. The forecast may aid in healthcare resource planning for the decades to come

Constructing General Unitary Maps from State Preparations

We present an efficient algorithm for generating unitary maps on a $d$-dimensional Hilbert space from a time-dependent Hamiltonian through a combination of stochastic searches and geometric construction. The protocol is based on the eigen-decomposition of the map. A unitary matrix can be implemented by sequentially mapping each eigenvector to a fiducial state, imprinting the eigenphase on that state, and mapping it back to the eigenvector. This requires the design of only $d$ state-to-state maps generated by control waveforms that are efficiently found by a gradient search with computational resources that scale polynomially in $d$. In contrast, the complexity of a stochastic search for a single waveform that simultaneously acts as desired on all eigenvectors scales exponentially in $d$. We extend this construction to design maps on an $n$-dimensional subspace of the Hilbert space using only $n$ stochastic searches. Additionally, we show how these techniques can be used to control atomic spins in the ground electronic hyperfine manifold of alkali atoms in order to implement general qudit logic gates as well to perform a simple form of error correction on an embedded qubit.Comment: 9 pages, 3 figure