Hierarchical demand response using dantzig-wolfe decomposition

Demand Side Management (DSM) programmes are designed to shift electrical loads from peak times. Demand Response (DR) algorithms automate this process for controllable loads. DR can be implemented explicitly in terms of Peak to Average Ratio Reduction (PARR), in which case the maximum peak load is minimised over a prediction horizon by manipulating the amount of energy given to controllable loads at different times. A hierarchical predictive PARR algorithm is presented here based on Dantzig-Wolfe decomposition. © 2013 IEEE.

Efficient predictive demand response using laguerre functions

Predictive Demand Response (DR) algorithms allow schedulable loads in power systems to be shifted to off-peak times. However, the size of the optimisation problems associated with predictive DR can grow very large and so efficient implementations of algorithms are desirable. In this paper Laguerre functions are used to significantly reduce the size of the optimisation needed to implement predictive DR, thus significantly increasing the efficiency of the implementation. © 2013 IEEE.

After the Male Breadwinner Model? Childcare Services and the Division of Labor in European Countries

Fundamental reforms in childcare services appear to have eroded traditional
support to the male breadwinner model across European states. There has been a strong debate about the direction of these changes, and the ways in which childcare services can alter the division of labor and promote gender equality. This paper deals with these issues by using fuzzy set ideal-type analysis to assess the conformity of childcare service provisions in European economies to Fraser’s four ideal typical models: male breadwinner, caregiver parity, universal breadwinner, and universal caregiver. We find that there is resilience of traditional gender roles in the majority of European countries, while there are different variants of the universal breadwinner shaping different forms of childcare policies. The more equalitarian universal caregiver model maintains its utopian character.

Process efficiency in polymer extrusion: Correlation between the energy demand and melt thermal stability

Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel. 

Investigation of the process energy demand in polymer extrusion: a brief review and an experimental study

Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditions is a key to reducing operating costs. Usually, extruders consume energy through the drive motor, barrel heaters, cooling fans, cooling water pumps, gear pumps, etc. Typically the drive motor is the largest energy consuming device in an extruder while barrel/die heaters are responsible for the second largest energy demand. This study is focused on investigating the total energy demand of an extrusion plant under various processing conditions while identifying ways to optimise the energy efficiency. Initially, a review was carried out on the monitoring and modelling of the energy consumption in polymer extrusion. Also, the power factor, energy demand and losses of a typical extrusion plant were discussed in detail. The mass throughput, total energy consumption and power factor of an extruder were experimentally observed over different processing conditions and the total extruder energy demand was modelled empirically and also using a commercially available extrusion simulation software. The experimental results show that extruder energy demand is heavily coupled between the machine, material and process parameters. The total power predicted by the simulation software exhibits a lagging offset compared with the experimental measurements. Empirical models are in good agreement with the experimental measurements and hence these can be used in studying process energy behaviour in detail and to identify ways to optimise the process energy efficiency.

Effects of a demand-led evidence briefing service on the uptake and use of research evidence by commissioners of health services: protocol for a controlled before and after study

Background: Clinical Commissioning Groups (CCGs) are mandated to use research evidence effectively to ensure optimum use of resources by the National Health Service (NHS), both in accelerating innovation and in stopping the use of less effective practices and models of service delivery. We intend to evaluate whether access to a demand-led evidence service improves uptake and use of research evidence by NHS commissioners compared with less intensive and less targeted alternatives. 

Methods/design: This is a controlled before and after study involving CCGs in the North of England. Participating CCGs will receive one of three interventions to support the use of research evidence in their decision-making:1) consulting plus responsive push of tailored evidence; 2) consulting plus an unsolicited push of non-tailored evidence; or 3) standard service unsolicited push of non-tailored evidence. Our primary outcome will be changed at 12 months from baseline of a CCGs ability to acquire, assess, adapt and apply research evidence to support decision-making. Secondary outcomes will measure individual clinical leads and managers’ intentions to use research evidence in decision making. Documentary evidence of the use of the outputs of the service will be sought. A process evaluation will evaluate the nature and success of the interactions both within the sites and between commissioners and researchers delivering the service. 

Discussion: The proposed research will generate new knowledge of direct relevance and value to the NHS. The findings will help to clarify which elements of the service are of value in promoting the use of research evidence.Those involved in NHS commissioning will be able to use the results to inform how best to build the infrastructure they need to acquire, assess, adapt and apply research evidence to support decision-making and to fulfil their statutory duties under the Health and Social Care Act.

Wind generation and electricity demand during the severe winter of 2009/10 in Ireland

Throughout the world the share of wind power in the generation mix is increasing. In the All Island Grid, of the Republic of Ireland and Northern Ireland there is now over 1.5 GW of installed wind power. As the penetration of these variable, non-dispatchable generators increases, power systems are becoming more sensitive to weather events on the supply side as well as on the demand side. In the temperate climate of Ireland, sensitivity of supply to weather is mainly due to wind variability while demand sensitivity is driven by space heating or cooling loads. The interplay of these two weather-driven effects is of particular concern if demand spikes driven by low temperatures coincide with periods of low winds. In December 2009 and January 2010 Ireland experienced a prolonged spell of unusually cold conditions. During much of this time, wind generation output was low due to low wind speeds. The impacts of this event are presented as a case study of the effects of weather extremes on power systems with high penetrations of variable renewable generation.

Barriers to Subcontracted Labor Productivity in Urban Development Projects: An On-site Project Management Perspective

Considering the confined and complex nature of urban construction projects, labor productivity is one of the key factors attributing to project success. With the proliferation of sub-contracted labor, there is a necessity to consider the ramifications of this practice to the sector. This research aims to outline how project managers can optimise productivity levels of sub-contracted labor in urban construction projects, by addressing the barriers that most restrict these efficiency levels. A qualitative research approach is employed, incorporating semi-structured interviews based on three case studies from an urban context. The results are scrutinised using mind mapping software and accompanying analytical techniques. The findings from this research indicate that the effective on-site management of sub-contracted labor has a significant impact on the degree of success of an urban development project. The two core barriers to sub-contracted labor productivity are; 1) ineffective supervision of sub-contracted labor, and 2) lack of skilled sub-contracted labor. The implication of this research is that on-site project management play an integral role in the level of productivity achieved by sub-contracted labor in urban development projects. Therefore, on-site management situated in urban, confined construction sites, are encouraged to take heed of the findings herein and address the barriers documented. The value of this research is obtained through consideration of the critical factors; construction management professionals can mitigate such barriers, in order to optimise subcontracted labor productivity on-site.

Hierarchical Demand Response for Peak Reduction using Dantzig‐Wolfe Decomposition

Demand Response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralised agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus it is desirable to use a scalable decentralised algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for Peak Minimisation (PM) based on Dantzig-Wolfe Decomposition (DWD). In addition, a Time Weighted Maximisation option is included in the cost function which improves the Quality of Service for devices seeking to receive their desired energy sooner rather than later. The paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

Demand response to improved walking infrastructure: A study into the economics of walking and health behaviour change

Walking is the most common form of moderate‐intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 minutes of at least moderate‐intensity physical activity per week. We model walking in an individual’s local neighbourhood as a ‘weak complement’ to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood
characteristics, substitutes, and individual’s characteristics, including their opportunity cost of time.  Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood.  Using a sample of 1,209 respondents surveyed over a 12 month period (Feb 2010‐Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people’s perception of access to shops and facilities  would lead to an increase in walking of about 36 minutes/person/week, valued at £13.65/person/week. When focusing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to
achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens.

Demand-side characterisation of the smart city for energy modelling.

This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

A Scheme Design of Cloud + End Technology in Demand Side Management

Demand Side Management (DSM) plays an important role in Smart Grid. It has large scale access points, massive users, heterogeneous infrastructure and dispersive participants. Moreover, cloud computing which is a service model is characterized by resource on-demand, high reliability and large scale integration and so on and the game theory is a useful tool to the dynamic economic phenomena. In this study, a scheme design of cloud + end technology is proposed to solve technical and economic problems of the DSM. The architecture of cloud + end is designed to solve technical problems in the DSM. In particular, a construct model of cloud + end is presented to solve economic problems in the DSM based on game theories. The proposed method is tested on a DSM cloud + end public service system construction in a city of southern China. The results demonstrate the feasibility of these integrated solutions which can provide a reference for the popularization and application of the DSM in china.