Large Scale Optimization Problems for Central Energy Facilities with Distributed Energy Storage

On large campuses, energy facilities are used to serve the heating and cooling needs of all the buildings, while utilizing cost savings strategies to manage operational cost. Strategies range from shifting loads to participating in utility programs that offer payouts. Among available strategies are central plant optimization, electrical energy storage, participation in utility demand response programs, and manipulating the temperature setpoints in the campus buildings. However, simultaneously optimizing all of the central plant assets, temperature setpoints and participation in utility programs can be a daunting task even for a powerful computer if the desire is real time control. These strategies may be implemented separately across several optimization systems without a coordinating algorithm. Due to system interactions, decentralized control may be far from optimal and worse yet may try to use the same asset for different goals. In this work, a hierarchal optimization system has been created to coordinate the optimization of the central plant, the battery, participation in demand response programs, and temperature setpoints. In the hierarchal controller, the high level coordinator determines the load allocations across the campus or facility. The coordinator also determines the participation in utility incentive programs. It is shown that these incentive programs can be grouped into reservation programs and price adjustment programs. The second tier of control is split into 3 portions: control of the central energy facility, control of the battery system, and control of the temperature setpoints. The second tier is responsible for converting load allocations into central plant temperature setpoints and flows, battery charge and discharge setpoints, and temperature setpoints, which are delivered to the Building Automation System for execution. It is shown that the whole system can be coordinated by representing the second tier controllers with a smaller set of data that can be used by the coordinating controller. The central plant optimizer must supply an operational domain which constrains how each group of equipment can operate. The high level controller uses this information to send down loadings for each resource a group of equipment in the plant produces or consumes. For battery storage, the coordinating controller uses a simple integrator model of the battery and is responsible for providing a demand target and the amount of participation in any incentive programs. Finally, to perform temperature setpoint optimization a dynamic model of the zone is provided to the coordinating controller. This information is used to determine load allocations for groups of zones. The hierarchal control strategy is successful at optimizing the entire energy facility fast enough to allow the algorithms to control the energy facility, building setpoints, and program bids in real-time

Use caution when applying behavioural science to policy

Social and behavioural scientists have attempted to speak to the COVID-19 crisis. But is behavioural research on COVID-19 suitable for making policy decisions? We offer a taxonomy that lets our science advance in ‘evidence readiness levels’ to be suitable for policy. We caution practitioners to take extreme care translating our findings to applications

Use of online cultural content for mental health and well-being during COVID-19 restrictions : cross-sectional survey

AIMS AND METHOD: To gain a deeper understanding of the use of online culture and its potential benefits to mental health and well-being, sociodemographic characteristics and self-reported data on usage, perceived mental health benefits and health status were collected in an online cross-sectional survey during COVID-19 restrictions in the UK in June-July 2020. RESULTS: In total, 1056 people completed the survey. A high proportion of participants reported finding online culture helpful for mental health; all but one of the benefits were associated with regular use and some with age. Reported benefits were wide-ranging and interconnected. Those aged under 25 years were less likely to be regular users of online culture or to have increased their use during lockdown. CLINICAL IMPLICATIONS: There may be benefits in targeting cultural resources for mental health to vulnerable groups such as young adults

A weak scientific basis for gaming disorder: let us err on the side of caution

We greatly appreciate the care and thought that is evident in the 10 commentaries that discuss our debate paper, the majority of which argued in favor of a formalized ICD-11 gaming disorder. We agree that there are some people whose play of video games is related to life problems. We believe that understanding this population and the nature and severity of the problems they experience should be a focus area for future research. However, moving from research construct to formal disorder requires a much stronger evidence base than we currently have. The burden of evidence and the clinical utility should be extremely high, because there is a genuine risk of abuse of diagnoses. We provide suggestions about the level of evidence that might be required: transparent and preregistered studies, a better demarcation of the subject area that includes a rationale for focusing on gaming particularly versus a more general behavioral addictions concept, the exploration of non-addiction approaches, and the unbiased exploration of clinical approaches that treat potentially underlying issues, such as depressive mood or social anxiety first. We acknowledge there could be benefits to formalizing gaming disorder, many of which were highlighted by colleagues in their commentaries, but we think they do not yet outweigh the wider societal and public health risks involved. Given the gravity of diagnostic classification and its wider societal impact, we urge our colleagues at the WHO to err on the side of caution for now and postpone the formalization

Measuring the Neutrino Cross Section Using 8 years of Upgoing Muon Neutrinos Observed with IceCube

The IceCube Neutrino Observatory detects neutrinos at energies orders of magnitude higher than those available to current accelerators. Above 40 TeV, neutrinos traveling through the Earth will be absorbed as they interact via charged current interactions with nuclei, creating a deficit of Earth-crossing neutrinos detected at IceCube. The previous published results showed the cross section to be consistent with Standard Model predictions for 1 year of IceCube data. We present a new analysis that uses 8 years of IceCube data to fit the ν$_{μ}$ absorption in the Earth, with statistics an order of magnitude better than previous analyses, and with an improved treatment of systematic uncertainties. It will measure the cross section in three energy bins that span the range 1 TeV to 100 PeV. We will present Monte Carlo studies that demonstrate its sensitivity