Economic Evaluation of Energy Efficiency Labelling in Domestic Appliances: the Spanish Market

30 p.

History of Oystering in the United States and Canada, Featuring the Eight Greatest Oyster Estuaries

Oyster landings in the United States and Canada have been based mainly on three species, the native eastern oyster, Crassostrea virginica, native Olympia oyster, Ostreola conchaphila, and introduced Pacific oyster, C. gigas. Landings reached their peak of around 27 million bushels/year in the late 1800's and early 1900's when eastern oysters were a common food throughout the east coast and Midwest. Thousands of people were involved in harvesting them with tongs and dredges and in shucking, canning, packing, and transporting them. Since about 1906, when the United States passed some pure food laws, production has declined. The causes have been lack of demand, siltation of beds, removal of cultch for oyster larvae while harvesting oysters, pollution of market beds, and oyster diseases. Production currently is about 5.6 million bushels/year.

Stress on the ward: evidence of safety tipping points in hospitals

Do hospitals experience safety tipping points as utilization increases, and if so, what are the implications for hospital operations management? We argue that safety tipping points occur when managerial escalation policies are exhausted and workload variability buffers are depleted. Front-line clinical staff is forced to ration resources and, at the same time, becomes more error prone as a result of elevated stress hormone levels. We confirm the existence of safety tipping points for in-hospital mortality using the discharge records of 82,280 patients across six high-mortality-risk conditions from 256 clinical departments of 83 German hospitals. Focusing on survival during the first seven days following admission, we estimate a mortality tipping point at an occupancy level of 92.5%. Among the 17% of patients in our sample who experienced occupancy above the tipping point during the first seven days of their hospital stay, high occupancy accounted for one in seven deaths. The existence of a safety tipping point has important implications for hospital management. First, flexible capacity expansion is more cost-effective for safety improvement than rigid capacity, because it will only be used when occupancy reaches the tipping point. In the context of our sample, flexible staffing saves more than 40% of the cost of a fully staffed capacity expansion, while achieving the same reduction in mortality. Second, reducing the variability of demand by pooling capacity in hospital clusters can greatly increase safety in a hospital system, because it reduces the likelihood that a patient will experience occupancy levels beyond the tipping point. Pooling the capacity of nearby hospitals in our sample reduces the number of deaths due to high occupancy by 34%.

User experience of mobile cloud applications - current state and future directions

The increasing penetration rate of feature rich mobile devices such as smartphones and tablets in the global population has resulted in a large number of applications and services being created or modified to support mobile devices. Mobile cloud computing is a proposed paradigm to address the resource scarcity of mobile devices in the face of demand for more computing intensive tasks. Several approaches have been proposed to confront the challenges of mobile cloud computing, but none has used the user experience as the primary focus point. In this paper we evaluate these approaches in respect of the user experience, propose what future research directions in this area require to provide for this crucial aspect, and introduce our own solution.

Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.

Planning, Devolution and the Territorialisation of Wind Energy in the UK

The decarbonisation of energy systems draw a new set of stakeholders into debates over energy generation, engage a complex set of social, political, economic and environmental processes and impact at a wide range of geographical scales, including local landscape changes, national energy markets and regional infrastructure investment. This paper focusses on a particular geographic scale, that of the regions/nations of the UK (Scotland, Wales, Northern Ireland), who have been operating under devolved arrangements since the late 1990s, coinciding with the mass deployment of wind energy. The devolved administrations of the UK possess an asymmetrical set of competencies over energy policy, yet also host the majority of the UK wind resource. This context provides a useful way to consider the different ways in which geographies of "territory" are reflected in energy governance, such through techno-rational assessments of demand or infrastructure investment, but also through new spatially-defined institutions that seek to develop their own energy future, using limited regulatory competencies. By focussing on the way the devolved administrations have used their responsibilities for planning over the last decade this paper will assess the way in which the spatial politics of wind energy is giving rise to renewed forms of territorialisation of natural resources. In so doing, we aim to contribute to clarifying the questions raised by Hodson and Marvin (2013) on whether low carbon futures will reinforce or challenge dominant ways of organising relationships between the nation-state, regions, energy systems and the environment.

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

The predominant fear in capital markets is that of a price spike. Commodity markets differ in that there is a fear of both upward and down jumps, this results in implied volatility curves displaying distinct shapes when compared to equity markets. The use of a novel functional data analysis (FDA) approach, provides a framework to produce and interpret functional objects that characterise the underlying dynamics of oil future options. We use the FDA framework to examine implied volatility, jump risk, and pricing dynamics within crude oil markets. Examining a WTI crude oil sample for the 2007–2013 period, which includes the global financial crisis and the Arab Spring, strong evidence is found of converse jump dynamics during periods of demand and supply side weakness. This is used as a basis for an FDA-derived Merton (1976) jump diffusion optimised delta hedging strategy, which exhibits superior portfolio management results over traditional methods.

Managing the variability of supply in the European power system with high wind energy penetration

The power system of the future will have a hierarchical structure created by layers of system control from via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the concept of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called ‘back-up generation’ needed to support an 80% renewable energy portfolio in Europe by 2050.

Impact of energy-using product policies

Energy-using products (EuPs), such as domestic appliances, audio-visual and ICT equipment contribute significantly to CO2 emissions, both in the domestic and non-domestic sectors. Policies that encourage the use of more energy efficient products can therefore generate significant reductions in overall energy consumption and hence, CO2 emissions. To the extent that these policies cause an increase the average production cost of EuPs, they may impose economic costs on producers, or on consumers, or on both. In this theoretical paper, an adaptation of a simple vertical product differentiation model – in which products are characterised in terms of their quality and their energy consumption – is used to analyse the impact of the different EuP polices on product innovation and to assess the resultant economic impacts on producers and consumers. It is shown that whereas the imposition of a binding product standard for energy efficiency unambiguously reduces aggregate profit and increases the average market price in the absence of any learning effects, the introduction or strengthening of demand-side measures (such as energy labelling) may reduce, or increase, aggregate profit. Even in the case where the overall impact is unambiguously negative, the effects of product innovation and learning can be in either direction.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Impact of a price-maker pumped storage hydro unit on the integration of wind energy in power systems

The increasing integration of larger amounts of wind energy into power systems raises important operational issues, such as the balance between power generation and demand. The pumped storage hydro (PSH) units are one possible solution to mitigate this problem, once they can store the excess of energy in the periods of higher generation and lower demand. However, the behaviour of a PSH unit may differ considerably from the expected in terms of wind power integration when it operates in a liberalized electricity market under a price-maker context. In this regard, this paper models and computes the optimal PSH weekly scheduling in a price-taker and price-maker scenarios, either when the PSH unit operates in standalone and integrated in a portfolio of other generation assets. Results show that the price-maker standalone PSH will integrate less wind power in comparison with the price-taker situation. Moreover, when the PSH unit is integrated in a portfolio with a base load power plant, the role of the price elasticity of demand may completely change the operational profile of the PSH unit. (C) 2014 Elsevier Ltd. All rights reserved.

Distributed, Agent-Based Intelligent System for Demand Response Program Simulation in Smart Grids

A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.