94 resultados para Scenarios for generation and demand


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The electricity industries of New Zealand (NZ) and the Australian state of Queensland have undergone substantial structural and regulatory reform with the common intent to improve economic efficiency. Deregulation and privatisation have been key elements of the reform but have been approached differently by each jurisdiction. This study traces the link between structural and regulatory regimes and asset valuation, profits and, ultimately, pricing. The study finds that key drivers in recent price increases are the government-owned generation and retail sector in NZ and the government-owned distribution sector in Queensland. It is concluded that, contrary to the rationale for the imposition of regulatory controls in a nonmarket environment, the regulatory regimes appear to have contributed to higher rather than lower pricing structures.

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Researchers in the field of occupational stress and well-being are increasingly interested in the role of emotion regulation in the work context. Emotion regulation has also been widely investigated in the area of lifespan developmental psychology, with findings indicating that the ability to modify one's emotions represents a domain in which age-related growth is possible. In this chapter, we integrate the literatures on aging, emotion regulation, and occupational stress and well-being. To this end, we review key theories and empirical findings in each of these areas, summarize existing research on age, emotion regulation, and stress and well-being at work, and develop a conceptual model on how aging affects emotion regulation and the stress process in work settings to guide future research. According to the model, age will affect: (1) what kinds of affective work events are encountered and how often; (2) the appraisal of and initial emotional response to affective work events (emotion generation), and; (3) the management of emotions and coping with affective work events (emotion regulation). The model has implications for researchers and practitioners who want to understand and facilitate successful emotion regulation and stress reduction in the workplace among different age groups.

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This paper investigates the long- and short-run relationships between energy consumption and economic growth in Australia using the bound testing and the ARDL approach. The analytical framework utilized in this paper includes both production and demand side models and a unified model comprising both production and demand side variables. The energy-GDP relationships are investigated at aggregate as well as several disaggregated energy categories, such as coal, oil, gas and electricity. The possibilities of one or more structural break(s) in the data series are examined by applying the recent advances in techniques. We find that the results of the cointegration tests could be affected by the structural break(s) in the data. It is, therefore, crucial to incorporate the information on structural break(s) in the subsequent modelling and inferences. Moreover, neither the production side nor the demand side framework alone can provide sufficient information to draw an ultimate conclusion on the cointegration and causal direction between energy and output. When alternative frameworks and structural break(s) in time series are explored properly, strong evidence of a bidirectional relationship between energy and output can be observed. The finding is true at both the aggregate and the disaggregate levels of energy consumption.

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The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.