Domestic fridge-freezer load aggregation to support ancillary services

Grid operators and electricity retailers in Ireland manage peak demand, power system balancing and grid congestion by offering relevant incentives to consumers to reduce or shift their load. The need for active consumers in the home using smart appliances has never been greater, due to increased variable renewable generation and grid constraints. In this paper an aggregated model of a single compressor fridge-freezer population is developed. A price control strategy is examined to quantify and value demand response savings during a representative winter and summer week for Ireland in 2020. The results show an average reduction in fridge-freezer operating cost of 8.2% during winter and significantly lower during summer in Ireland. A peak reduction of at least 68% of the average winter refrigeration load is achieved consistently during the week analysed using a staggering control mode. An analysis of the current ancillary service payments confirms that these are insufficient to ensure widespread uptake by the small consumer, and new mechanisms need to be developed to make becoming an active consumer attractive. Demand response is proposed as a new ancillary service called ramping capability, as the need for this service will increase with more renewable energy penetration on the power system.

Environmental and genetic control of arsenic accumulation and speciation in rice grain:comparing a range of common cultivars grown in contaminated sites across Bangladesh, China, and India

The concentration of arsenic (As) in rice grains has been identified as a risk to human health. The high proportion of inorganic species of As (As(i)) is of particular concern as it is a nonthreshold, class 1 human carcinogen. To be able to breed rice with low grain As, an understanding of genetic variation and the effect of different environments on genetic variation is needed. In this study, 13 cultivars grown at two field sites each in Bangladesh, India, and China are evaluated for grain As. There was a significant site, genotype, and site by genotype interaction for total grain As. Correlations were observed only between sites in Bangladesh and India, not between countries or within the Chinese sites. For seven cultivars the As was speciated which revealed significant effects of site, genotype, and site by genotype interaction for percentage As(i). Breeding low grain As cultivars that will have consistently low grain As and low As(i), over multiple environments using traditional breeding approaches may be difficult, although CT9993-5-10-1-M, Lemont, Azucena, and Te-qing in general had low grain As across the field sites.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.