Energy Management and Control for Islanded Microgrid Using Multi-Agents

This paper presents a multi-agent system for real-time operation of simulated microgrid using the Smart-Grid Test Bed at Washington State University. The multi-agent system (MAS) was developed in JADE (Java Agent DEvelopment Framework) which is a Foundation for Intelligent Physical Agents (FIPA) compliant open source multi-agent platform. The proposed operational strategy is mainly focused on using an appropriate energy management and control strategies to improve the operation of an islanded microgrid, formed by photovoltaic (PV) solar energy, batteries and resistive and rotating machines loads. The focus is on resource management and to avoid impact on loads from abrupt variations or interruption that changes the operating conditions. The management and control of the PV system is performed in JADE, while the microgrid model is simulated in RSCAD/RTDS (Real-Time Digital Simulator). Finally, the outcome of simulation studies demonstrated the feasibility of the proposed multi-agent approach for real-time operation of a microgrid.

Energy Restriction During Breeding Gilt Development: An Economic Analysis

Swine production has increasingly become a lowmargin business. As costs of production have increased, producers are continuing to increase efficiency in both market pig production and gilt development. Restricting energy during gilt development reduces feeding costs and can enhance some productivity measures, but can also negatively impact other areas of production. Thus, the net economic returns from a restricted energy gilt development program are unclear. This study utilized gilt development and market pig production data for two genetic lines of hogs, LWxLR (a cross between industry Large White and Landrace) and L45X (a Nebraska line selected 23 generations for increased litter size) from Johnson and Miller and Johnson et al., to estimate the returns to finishing market hogs using conventional and restricted energy gilt development programs.

Looming Changes in the Energy Economy

Over the next decade or two, the energy sector on which the world economy is based will undergo significant transformations. The fossil fuels on which the industrial revolution was built are on their way out. Nebraskans will face higher energy prices, but they will also produce more energy.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Quantum Energy Teleportation Between Spin Particles in a Gibbs State

Energy in a multipartite quantum system appears from an operational perspective to be distributed to some extent non-locally because of correlations extant among the system's components. This non-locality allows users to transfer, in effect, locally accessible energy between sites of different system components by local operations and classical communication (LOCC). Quantum energy teleportation is a three-step LOCC protocol, accomplished without an external energy carrier, for effectively transferring energy between two physically separated, but correlated, sites. We apply this LOCC teleportation protocol to a model Heisenberg spin particle pair initially in a quantum thermal Gibbs state, making temperature an explicit parameter. We find in this setting that energy teleportation is possible at any temperature, even at temperatures above the threshold where the particles' entanglement vanishes. This shows for Gibbs spin states that entanglement is not fundamentally necessary for energy teleportation; correlation other than entanglement can suffice. Dissonance-quantum correlation in separable states-is in this regard shown to be a quantum resource for energy teleportation, more dissonance being consistently associated with greater energy yield. We compare energy teleportation from particle A to B in Gibbs states with direct local energy extraction by a general quantum operation on B and find a temperature threshold below which energy extraction by a local operation is impossible. This threshold delineates essentially two regimes: a high temperature regime where entanglement vanishes and the teleportation generated by other quantum correlations yields only vanishingly little energy relative to local extraction and a second low-temperature teleportation regime where energy is available at B only by teleportation.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

Integrated solar energy and absorption cooling model for HVAC (heating, ventilating, and air conditioning) applications in buildings

The demands in production and associate costs at power generation through non renewable resources are increasing at an alarming rate. Solar energy is one of the renewable resource that has the potential to minimize this increase. Utilization of solar energy have been concentrated mainly on heating application. The use of solar energy in cooling systems in building would benefit greatly achieving the goal of non-renewable energy minimization. The approaches of solar energy heating system research done by initiation such as University of Wisconsin at Madison and building heat flow model research conducted by Oklahoma State University can be used to develop and optimize solar cooling building system. The research uses two approaches to develop a Graphical User Interface (GUI) software for an integrated solar absorption cooling building model, which is capable of simulating and optimizing the absorption cooling system using solar energy as the main energy source to drive the cycle. The software was then put through a number of litmus test to verify its integrity. The litmus test was conducted on various building cooling system data sets of similar applications around the world. The output obtained from the software developed were identical with established experimental results from the data sets used. Software developed by other research are catered for advanced users. The software developed by this research is not only reliable in its code integrity but also through its integrated approach which is catered for new entry users. Hence, this dissertation aims to correctly model a complete building with the absorption cooling system in appropriate climate as a cost effective alternative to conventional vapor compression system.

Energy, Complexity and Strategies of Evolution. En: Avá, nº 14

Cultural evolution has long been among the themes of anthropology but it has never ranked high. It is left mainly to archaeologists because they have to make sense of how society works and survives through time–a concern that has pretty much been abandoned by many cultural anthropologists. Anthropologists today seem little motivated to find out how society works, but rather to make the world a better place to live in for a particular population. The challenges of atmospheric change, nuclear proliferation, environmental degradation and resource exhaustion, the emergence of life threatening species–these challenges of contemporary evolution have awakened less interest in anthropology. The concern with cultural evolution seems to be of greater interest to non-anthropologists, such as in the work of Jarrod Diamond (2005), a biologist, and the genre that as emerged as Big History, with the works of David Christian (2005) and others. Among the few contemporary anthropologists who have sought the dynamics of cultural evolution, the work of Joseph Tainter (1996) stands out.

31 ground-penetrating radar lines of Area 3 - Beach ridge plain (high wave energy) from Maxwell Bay, King George Island, Antarctic Peninsula

During a field campaign in the Austral spring 2012 the sedimentary architecture of a polar gravel-beach system at the southern coast of Potter Peninsula (Area 3) was revealed using ground-penetrating radar (GPR, Geophysical Survey Systems, Inc. SIR-3000). 31 profiles were collected using a mono-static 200 MHz antenna operated in common offset mode. Trace increment was set to 0.05 m. A differential global-positioning system (dGPS, Leica GS09) was used to obtain topographical information along the GPR lines. GPR data are provided in RADAN-Format, dGPS coordinates are provided in ascii format; projection is UTM (WGS 84, zone 21S).

Seawater carbonate chemistry and resource allocation and extracellular acid-base status in the sea urchin Strongylocentrotus droebachiensis during experiments, 2012

Anthropogenic CO2 emission will lead to an increase in seawater pCO2 of up to 80-100 Pa (800-1000 µatm) within this century and to an acidification of the oceans. Green sea urchins (Strongylocentrotus droebachiensis) occurring in Kattegat experience seasonal hypercapnic and hypoxic conditions already today. Thus, anthropogenic CO2 emissions will add up to existing values and will lead to even higher pCO2 values >200 Pa (>2000 µatm). To estimate the green sea urchins' potential to acclimate to acidified seawater, we calculated an energy budget and determined the extracellular acid base status of adult S. droebachiensis exposed to moderately (102 to 145 Pa, 1007 to 1431 µatm) and highly (284 to 385 Pa, 2800 to 3800 µatm) elevated seawater pCO2 for 10 and 45 days. A 45 - day exposure to elevated pCO2 resulted in a shift in energy budgets, leading to reduced somatic and reproductive growth. Metabolic rates were not significantly affected, but ammonium excretion increased in response to elevated pCO2. This led to decreased O:N ratios. These findings suggest that protein metabolism is possibly enhanced under elevated pCO2 in order to support ion homeostasis by increasing net acid extrusion. The perivisceral coelomic fluid acid-base status revealed that S. droebachiensis is able to fully (intermediate pCO2) or partially (high pCO2) compensate extracellular pH (pHe) changes by accumulation of bicarbonate (maximum increases 2.5 mM), albeit at a slower rate than typically observed in other taxa (10 day duration for full pHe compensation). At intermediate pCO2, sea urchins were able to maintain fully compensated pHe for 45 days. Sea urchins from the higher pCO2 treatment could be divided into two groups following medium-term acclimation: one group of experimental animals (29%) contained remnants of food in their digestive system and maintained partially compensated pHe (+2.3 mM HCO3), while the other group (71%) exhibited an empty digestive system and a severe metabolic acidosis (-0.5 pH units, -2.4 mM HCO3). There was no difference in mortality between the three pCO2 treatments. The results of this study suggest that S. droebachiensis occurring in the Kattegat might be pre-adapted to hypercapnia due to natural variability in pCO2 in its habitat. We show for the first time that some echinoderm species can actively compensate extracellular pH. Seawater pCO2 values of >200 Pa, which will occur in the Kattegat within this century during seasonal hypoxic events, can possibly only be endured for a short time period of a few weeks. Increases in anthropogenic CO2 emissions and leakages from potential sub-seabed CO2 storage (CCS) sites thus impose a threat to the ecologically and economically important species S. droebachiensis.

Interactive effects of light, nitrogen source, and carbon dioxide on energy metabolism in the diatom Thalassiosira pseudonana

Due to the ongoing effects of climate change, phytoplankton are likely to experience enhanced irradiance, more reduced nitrogen, and increased water acidity in the future ocean. Here, we used Thalassiosira pseudonana as a model organism to examine how phytoplankton adjust energy production and expenditure to cope with these multiple, interrelated environmental factors. Following acclimation to a matrix of irradiance, nitrogen source, and CO2 levels, the diatom's energy production and expenditures were quantified and incorporated into an energetic budget to predict how photosynthesis was affected by growth conditions. Increased light intensity and a shift from inline image to inline image led to increased energy generation, through higher rates of light capture at high light and greater investment in photosynthetic proteins when grown on inline image. Secondary energetic expenditures were adjusted modestly at different culture conditions, except that inline image utilization was systematically reduced by increasing pCO2. The subsequent changes in element stoichiometry, biochemical composition, and release of dissolved organic compounds may have important implications for marine biogeochemical cycles. The predicted effects of changing environmental conditions on photosynthesis, made using an energetic budget, were in good agreement with observations at low light, when energy is clearly limiting, but the energetic budget over-predicts the response to inline image at high light, which might be due to relief of energetic limitations and/or increased percentage of inactive photosystem II at high light. Taken together, our study demonstrates that energetic budgets offered significant insight into the response of phytoplankton energy metabolism to the changing environment and did a reasonable job predicting them.