Electricity Interconnection with Intermittent Renewables

Electricity interconnection has been recognized as a way to mitigate carbon emissions by dispatching more efficient electricity production and accommodating the growing share of renewables. I analyze the impact of electricity interconnection in the presence of intermittent renewables, such as wind and solar power, on renewable capacity and carbon emissions using a two-country model. I find that in the first-best, interconnection decreases investments in renewable capacity and exacerbates carbon emissions if the social cost of carbon (SCC) is low. Conversely, interconnection increases renewable capacity and reduces carbon emissions for a high SCC. Moreover, the intermittency of renewables generates an insurance gain from interconnection, which also implies that some renewable capacity is optimally curtailed in some states of nature when the SCC is high. The curtailment rate and the corresponding carbon emissions increase for more positively correlated intermittency. I calibrate the model using data from the European Union electricity market and simulate the outcome of expanding interconnection between Germany-Poland and France-Spain. I find that given the current level of SCC, the interconnection may increase carbon emissions. The net benefit of interconnection is positive, with uneven distribution across countries

Electricity Interconnection with Intermittent Renewables

Electricity interconnection has been recognized as a way to mitigate carbon emissions by dispatching more efficient electricity production and accommodating the growing share of renewables. I analyze the impact of electricity interconnection in the presence of intermittent renewables, such as wind and solar power, on renewable capacity and carbon emissions using a two-country model. I find that in the first-best, interconnection decreases investments in renewable capacity and exacerbates carbon emissions if the social cost of carbon (SCC) is low. Conversely, interconnection increases renewable capacity and reduces carbon emissions for a high SCC. Moreover, the intermittency of renewables generates an insurance gain from interconnection, which also implies that some renewable capacity is optimally curtailed in some states of nature when the SCC is high. The curtailment rate and the corresponding carbon emissions increase for more positively correlated intermittency. I calibrate the model using data from the European Union electricity market and simulate the outcome of expanding interconnection between Germany-Poland and France-Spain. I find that given the current level of SCC, the interconnection may increase carbon emissions. The net benefit of interconnection is positive, with uneven distribution across countries

Interactive visualization of metabolic networks using virtual reality

A combination of graph layouts in 3D space, interactive computer graphics, and virtual reality (VR) can increase the size of understandable networks for metabolic network visualization. Two models, the directed graph and the compound graph, were used to represent a metabolic network. The directed graph, or nonhierarchical visualization, considers the adjacency relationships. For the nonhierarchical visualization, the weighted GEM-3D layout was adopted to emphasize the reactions among metabolite nodes. The compound graph, or hierarchical visualization, explicitly takes the hierarchical relationships like the pathway-molecule hierarchy or the compartment-molecule hierarchy into consideration to improve the performance and perception. An algorithm was designed, which combines the hierarchical force model with the simulated annealing method, to efficiently generate an effective layout for the compound graph. A detail-on-demand method improved the rendering performance and perception of the hierarchical visualization. The directed graph was also used to represent a sub-network composed of reactions of interest (ROIs), which reveal reactions involving a specific node. The fan layout was proposed for ROIs focusing on a metabolite node. The radial layout was adopted for ROIs focusing on a gene node. Graphics scenes were constructed for the network. The shapes and material properties of geometric objects, such as colors, transparencies, and textures, can encode biological properties, such as node names, reaction edge types, etc. Graphics animations like color morph, shape morph, and edge vibration were used to superimpose gene expression profiling data to the network. Interactions for an effective visualization were defined and implemented using VR interfaces. A pilot usability study and some qualitative comparisons were conducted to show potential advantages of stereoscopic VR for metabolic network visualization

Channel characterization for 1D molecular communication with two absorbing receivers

This letter develops a one-dimensional (1D) diffusion-based molecular communication system to analyze channel responses between a single transmitter (TX) and two fully-absorbing receivers (RXs). Incorporating molecular degradation in the environment, rigorous analytical formulas for i) the fraction of molecules absorbed, ii) the corresponding hitting rate, and iii) the asymptotic fraction of absorbed molecules as time approaches infinity at each RX are derived when an impulse of molecules are released at the TX. By using particle-based simulations, the derived analytical expressions are validated. Simulations also present the distance ranges of two RXs that do not impact molecular absorption of each other, and demonstrate that the mutual influence of two active RXs reduces with the increase in the degradation rate

Simplified Cooperative Detection for Multi-Receiver Molecular Communication

Diffusion-based molecular communication (MC) systems experience significant reliability losses. To boost the reliability, an MC scheme where multiple receivers (RXs) work cooperatively to decide the signal of a transmitter (TX) by sending the same type of molecules to a fusion center (FC) is proposed in this paper. The FC observes the total number of molecules received and compares this number with a threshold to determine the TX's signal. The proposed scheme is more bio-realistic and requires relatively low computational complexity compared to existing cooperative schemes where the RXs send and the FC recognizes different types of molecules. Asymmetric and symmetric topologies are considered, and closed-form expressions are derived for the global error probability for both topologies. Results show that the trade-off for simplified computations leads to a slight reduction in error performance, compared to the existing cooperative schemes.Comment: 5 pages, 4 figures, Will be presented as an invited paper at the 2017 IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwa

Parameter Estimation in a Noisy 1D Environment via Two Absorbing Receivers

This paper investigates the estimation of different parameters, e.g., propagation distance and flow velocity, by utilizing two fully-absorbing receivers (RXs) in a one-dimensional (1D) environment. The time-varying number of absorbed molecules at each RX and the number of absorbed molecules in a time interval as time approaches infinity are derived. Noisy molecules in this environment, that are released by sources in addition to the transmitter, are also considered. A novel estimation method, namely difference estimation (DE), is proposed to eliminate the effect of noise by using the difference of received signals at the two RXs. For DE, the Cramer-Rao lower bound (CRLB) on the variance of estimation is derived. Independent maximum likelihood estimation is also considered at each RX as a benchmark to show the performance advantage of DE. Aided by particle-based simulation, the derived analytical results are verified. Furthermore, numerical results show that DE attains the CRLB and is less sensitive to the change of noise than independent estimation at each RX.Comment: 7 pages, 5 figures, accepted by Globecom 202