Binary Search Algorithm for Mixed Integer Optimization: Application to energy management in a microgrid

This paper presents a binary search algorithm to deal with binary variables in mixed integer optimization problems. One example of this kind of problem is the optimal operation of hydrogen storage and energy sale and purchase into a microgrids context. In this work was studied a system composed by a microgrid that has a connection with the external electrical network and a charging station for electric cars. The system modeling was carried out by the Energy Hubs methodology. The proposed algorithm transforms the MIQP (Mixed Integer Quadratic Program) problem into a QP (Quadratic Program) that is easier to solve. In this way the overall control task is carried out the electricity purchase and sale to the power grid, maximizes the use of renewable energy sources, manages the use of energy storages and supplies the charge of the parked vehicles.Ministerio de Economía y Competitividad DPI2013-46912-C2-1-RUniversidad de Sevilla CNPq401126/2014-5Universidad de Sevilla CNPq303702/2011-

HYBRID MODEL OF IRRIGATION CANAL AND ITS CONTROLLER USING MODEL PREDICTIVE CONTROL

In this paper, we formulate a hybrid model of irrigation canal that contains four reaches where each of reach has two state events. These state events of this hybrid model are triggered by the height of the water level which has two different surfaces. We formulate this hybrid model in piecewise affine (PWA) form, transform it into mixed logical dynamic (MLD) form using hybrid system description language (HYSDEL) that was embedded in hybrid toolbox for MATLAB and control this MLD using model predictive control (MPC). We control this irrigation canal so that the water level on each reach will be located at the desired level. Finally, we simulate this system and its controller to desire given desired level or set point. From the simulation results, the water level of all reaches are located at the desired level

Real-time receding horizon optimisation of gas pipeline networks

Real-time optimisation of gas pipelines in transient conditions is considered to be a challenging problem. Many pipeline systems are, however, only mildly non-linear. It is shown, that even the shutdown event of a compressor station can be described using a linear model. A dynamic, receding horizon optimisation problem is defined, where the free response prediction of the pipeline is obtained from a pipeline simulator and the optimal values of the decision variables are obtained solving a Quadratic Programming (QP) problem set up by using linear models, linearised constraints and quadratic approximations of the cost function, which is the energy consumption of the compressor stations (CSs). The problem is extended with discrete decision variables, the shutdown/start-up commands of CSs. A Mixed Logical Dynamical (MLD) system is defined, but the resulting Mixed Integer QP problem is shown to be very high-dimensional. Instead, a series of QP problems, each containing linear constraints modelling the shut down state of CSs, results in an optimisation problem with considerably smaller dimension. The receding horizon optimisation is tested in a simulation environment and comparison with data from the Finnish natural gas pipeline shows that 5 to 8 % savings in compressor energy consumption can be achieved using optimisation. A new idea, maximisation of energy consumption, is used to calculate maximal energy savings potential of the pipeline. A new result is that step response models used in conjunction with MLD systems do not produce the same model change behaviour than state space models.reviewe

Characterizing phytoplankton biomass seasonal cycles in two NE Atlantic coastal bays

The seasonal and interannual variability of chlorophyll a was studied between 2008 and 2016 in two coastal bays located in the northeastern limit of the Iberia/Canary upwelling ecosystem. The work aims (i) to understand if small latitudinal distances and/or coastline orientation can promote different chlorophyll a seasonal cycles; and (ii) to investigate if different meteorological and oceanographic variables can explain the differences observed on seasonal cycles. Results indicate three main biological seasons with different patterns in the two studied bays. A uni-modal pattern with a short early summer maximum and relatively low chlorophyll a concentration characterized the westernmost sector of the South coast, while a uni-modal pattern characterized by high biomass over a long period, slightly higher in spring than in summer, and high chlorophyll a concentration characterized the central West coast. Comparisons made between satellite estimates of chlorophyll a and in situ data in one of the bays revealed some important differences, namely the overestimation of concentrations and the anticipation of the beginning and end time of the productive period by satellite. Cross-correlation analyses were performed for phytoplankton biomass and different meteorological and oceanographic variables (SST, PAR, UI, MLD and precipitation) using different time lags to identify the drivers that promote the growth and the high levels of phytoplankton biomass. PAR contributed to the increase of phytoplankton biomass observed during winter/midspring, while upwelling and SST were the main explanatory drivers to the high Chl-a concentrations observed in late-spring/summer. Zonal transport was the variable that contributed most to the phytoplankton biomass during late-spring/summer in Lisbon Bay, while the meridional transport combined with SST was more important in Lagos Bay.FCT: SFRH/BD/52560/2014/ IPMA-BCC-2016-35/ UIDB/04292/2020/ UID/Multi/04326/2020/ UID/MAT/04561/2020 LISBOA-01-0145FEDER-031265 IPMA: MAR2020PO2M01-1490 Pinfo:eu-repo/semantics/publishedVersio

Comparison of the Observed Mixe Layer Depth in the Lee of the Hawaiian Island to the Modeled Mixed Layer Depth of the Regional Navy Coastal Ocean Model

Accurately modeling the depth of the surface mixed layer in the lee of the Hawaiian Islands is important to naval operations because the area hosts numerous training exercises. Providing an accurate picture of the environment aids naval operators in making important tactical decisions. This study evaluates the ability of the Hawaii Regional Navy Coastal Ocean Model to accurately predict the depth of the surface mixed layer in this complex, wake island environment. The model was compared to CTD data collected from sea gliders and tests for correlation were conducted. For mixed layer depths that did show correlation, match paired t tests were used to determine the significance of the correlations. It was determined that the Hawaii Regional Navy Coastal Ocean Model has difficulty accurately predicting the depth of the surface mixed layer, however, it does show considerable skill when compared to the results of alternate models. It was also determined that the model has difficulty with unusual oceanographic features such as mode water eddies. These features are too uncommon and short-lived to be depicted in the climatology data. This climatology data is a major component of the synthetic profiles that the model generates and these profiles tend to smooth out the unusual subsurface isothermal layer

Self-Assembled Monolayers for Phosphorus Doping of Silicon for Field Effect Devices

Moore\u27s law continues to drive the semiconductor industry to create smaller transistors and improve device performance. Smaller transistors require shallower junctions, especially for the non-planar geometries such as FinFETs and nanowires which are becoming more common. Conventional doping techniques such as ion implantation and spin-on diffusants have difficulty producing shallow junctions, especially for conformal doping of non-planar structures. Molecular monolayer doping (MLD) is presented as an alternative doping method with the capability to produce ultra-shallow junctions with low sheet resistances for planar and non-planar structures. MLD relies on the formation of a self-assembled monolayer of a dopant-containing compound which is annealed to diffuse dopants into the substrate, forming an ultra-shallow junction with a high surface concentration. This work fabricates and characterizes field effect devices using MLD to dope the source and drain regions. To support this goal, a low-cost reaction chamber for MLD is developed using materials that are commonly found in chemistry stockrooms and local home goods stores. The results of the MLD process are quantified using four point probe measurements and SIMS profiles, with diffused layers measured to have sheet resistances on the order of 1000 Ω/□ and surface concentrations on the order of 1020 cm-3. MLD is demonstrated to be patternable using SiO2 as a masking layer, verified with four point probe measurements, electrical testing, and thin oxide growth over a wafer with heavily doped and lightly doped areas to reproduce the original doping pattern. A fabrication process and mask design compatible with the MLD process is created to fabricate NMOSFETs. The NMOSFETs are electrically tested and show field effect behavior with threshold voltages around -0.3 V and subthreshold swing of 150 mV/dec. The devices do show high series resistance, due to an unintended 13.1 Å interfacial layer of SiO2 in the contact cuts, discovered by STEM images. Future work proposes process revisions to mitigate this issue and scale down the size of the FETs to further explore MLD\u27s potential for creating cutting edge field effect devices