919 resultados para Operational constraints


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Wind energy is predominantly a nonsynchronous generation source. Large-scale integration of wind generation with existing electricity systems, therefore, presents challenges in maintaining system frequency stability and local voltage stability. Transmission system operators have implemented system operational constraints (SOCs) in order to maintain stability with high wind generation, but imposition of these constraints results in higher operating costs. A mixed integer programming tool was used to simulate generator dispatch in order to assess the impact of various SOCs on generation costs. Interleaved day-ahead scheduling and real-time dispatch models were developed to allow accurate representation of forced outages and wind forecast errors, and were applied to the proposed Irish power system of 2020 with a wind penetration of 32%. Savings of at least 7.8% in generation costs and reductions in wind curtailment of 50% were identified when the most influential SOCs were relaxed. The results also illustrate the need to relax local SOCs together with the system-wide nonsynchronous penetration limit SOC, as savings from increasing the nonsynchronous limit beyond 70% were restricted without relaxation of local SOCs. The methodology and results allow for quantification of the costs of SOCs, allowing the optimal upgrade path for generation and transmission infrastructure to be determined.

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Wind energy installations are increasing in power systems worldwide and wind generation capacity tends to be located some distance from load centers. A conflict may arise at times of high wind generation when it becomes necessary to curtail wind energy in order to maintain conventional generators on-line for the provision of voltage control support at load centers. Using the island of Ireland as a case study and presenting commercially available reactive power support devices as possible solutions to the voltage control problems in urban areas, this paper explores the reduction in total generation costs resulting from the relaxation of the operational constraints requiring conventional generators to be kept on-line near load centers for reactive power support. The paper shows that by 2020 there will be possible savings of 87€m per annum and a reduction in wind curtailment of more than a percentage point if measures are taken to relax these constraints.

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This paper describes the optimization of conductor size and the voltage regulator location & magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.

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Dwell times at stations and inter-station run times are the two major operational parameters to maintain train schedule in railway service. Current practices on dwell-time and run-time control are that they are only optimal with respect to certain nominal traffic conditions, but not necessarily the current service demand. The advantages of dwell-time and run-time control on trains are therefore not fully considered. The application of a dynamic programming approach, with the aid of an event-based model, to devise an optimal set of dwell times and run times for trains under given operational constraints over a regional level is presented. Since train operation is interactive and of multi-attributes, dwell-time and run-time coordination among trains is a multi-dimensional problem. The computational demand on devising trains' instructions, a prime concern in real-time applications, is excessively high. To properly reduce the computational demand in the provision of appropriate dwell times and run times for trains, a DC railway line is divided into a number of regions and each region is controlled by a dwell- time and run-time controller. The performance and feasibility of the controller in formulating the dwell-time and run-time solutions for real-time applications are demonstrated through simulations.

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With the growth and development of communication technology there is an increasing need for the use of interception technologies in modern policing. Law enforcement agencies are faced with increasingly sophisticated and complex criminal networks that utilise modern communication technology as a basis for their criminal success. In particular, transnational organised crime (TOC) is a diverse and complicated arena, costing global society in excess of $3 trillion annually, a figure that continues to grow (Borger, 2007) as crime groups take advantage of disappearing borders and greater profit markets. However, whilst communication can be a critical success factor for criminal enterprise it is also a key vulnerability. It is this vulnerability that the use of CIT, such as phone taps or email interception, can exploit. As such, law enforcement agencies now need a method and framework that allows them to utilise CIT to combat these crimes efficiently and successfully. This paper provides a review of current literature with the specific purpose of considering the effectiveness of CIT in the fight against TOC and the groundwork that must be laid in order for it to be fully exploited. In doing so, it fills an important gap in current research, focusing on the practical implementation of CIT as opposed to the traditional area of privacy concerns that arise with intrusive methods of investigation. The findings support the notion that CIT is an essential intelligence gathering tool that has a strong place within the modern policing arena. It identifies that the most effective use of CIT is grounded within a proactive, intelligence‐led framework and concludes that in order for this to happen Australian authorities and law enforcement agencies must re‐evaluate and address the current legislative and operational constraints placed on the use of CIT and the culture that surrounds intelligence in policing.

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This proposition challenges the notion that clean technology firms, who form part of the emerging social innovation enterprise sector, do not have the resources to gain value from Design Led innovation practices, due to their size and operational constraints. Much has been written on the benefits of linking design and design thinking to organisational strategy and business transformation. The term Design Led in the context of this proposition is defined as the tools and approaches which enable design thinking to be embedded as a cultural transformation within a business. Being Design Led requires a company to have a vision for top line growth within their business, which is based on deep customer insights and expanded through customer and stakeholder engagements, with the outcomes being mapped to all aspects of the business to enable the vision to be achieved.

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Constant changes in the global economic environment require companies to revisit traditional assumptions about how businesses create and capture value (Teece, 2010). In recent years, management practice literature has focused largely on better understanding business models and business model innovation (Amit, Zott and Massa, 2010; Johnson, Christensen and Kagermann, 2008). Much has been written on the benefits of linking design and design thinking to organisational strategies and business transformation. However, very little has been researched and reported on regarding the impact of design led approaches to triple bottom-line opportunities such as, social innovation enterprise. In the context of this paper Design Led Innovation is defined as the tools and approaches which enable design thinking to be embedded as an element of cultural transformation within a business. Being Design Led requires a company to have a vision for top line growth founded on deep customer insights and expanded through customer and stakeholder engagements. The outcomes of this are then mapped to all aspects of the business, enabling the vision to be successfully implemented and achieved. It is the latter part of this definition where we believe Design Led Innovation has the greatest value in transforming social innovation enterprise into a sustainable business venture. However, we also acknowledge that enabling these firms to think strategically about their business model is difficult given the unique operational and funding challenges that often characterize many social enterprises. The purpose of this paper, therefore, is to pose the question, do sustainable innovation enterprise innovate their business model? And if so, how? It is the authors’ opinion that such enterprises only innovate at the product or system level without a complete understanding of the business model structure, which underpins the long term viability. However, in this paper we challenge this notion and explore if such firms can overcome their size and operational constraints to become sustainable enterprises using a design led approach. This is achieved through contextualizing business model innovation, briefly defining social innovation enterprise and profiling a new and emerging industry in Australia – Clean Technology. Future research challenges and opportunities are also presented.

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Determining the condition as well as the remaining life of an insulation system is essential for the reliable operation of large oil-filled power transformers. Frequency-domain spectroscopy (FDS) is one of the diagnostic techniques used to identify the dielectric status of a transformer. Currently, this technique can only be implemented on a de-energized transformer. This paper presents an initial investigation into a novel online monitoring method based on FDS dielectric measurements for transformers. The proposed technique specifically aims to address the real operational constraints of online testing. This is achieved by designing an online testing model extending the basic “extended Debye” linear dielectric model and taking unique noise issues only experienced during online measurements into account via simulations. Approaches to signal denoising and potential problems expected to be encountered during online measurements will also be discussed. Using fixed-frequency sinusoidal excitation waveforms will result in a long measurement times. The use of alternatives such as a chirp has been investigated using simulations. The results presented in the paper predict that reliable measurements should be possible during online testing.

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This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.

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An implementable nonlinear control design approach is presented for a supersonic air-breathing ramjet engine. The primary objective is to ensure that the thrust generated by the engine tracks the commanded thrust without violating the operational constraints. An important constraint is to manage the shock wave location in the intake so that it neither gets detached nor gets too much inside the intake. Both the objectives are achieved by regulating the fuel flow to the combustion chamber and by varying the throat area of the nozzle simultaneously. The design approach accounts for the nonlinear cross-coupling effects and nullifies those. Also, an extended Kalman filter has been used to filter out the sensor and process noises as well as to make the states available for feedback. Furthermore, independent control design has been carried out for the actuators. To test the performance of the engine for a realistic flight trajectory, a representative trajectory is generated through a trajectory optimization process, which is augmented with a newly-developed finite-time state dependent Riccati equation technique for nullifying the perturbations online. Satisfactory overall performance has been obtained during both climb and cruise phases. (C) 2015 Elsevier Masson SAS. All rights reserved.

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How to regulate phytoplankton growth in water supply reservoirs has continued to occupy managers and strategists for some fifty years or so, now, and mathematical models have always featured in their design and operational constraints. In recent years, rather more sophisticated simulation models have begun to be available and these, ideally, purport to provide the manager with improved forecasting of plankton blooms, the likely species and the sort of decision support that might permit management choices to be selected with increased confidence. This account describes the adaptation and application of one such model, PROTECH (Phytoplankton RespOnses To Environmental CHange) to the problems of plankton growth in reservoirs. This article supposes no background knowledge of the main algal types; neither does it attempt to catalogue the problems that their abundance may cause in lakes and reservoirs.

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Model predictive control allows systematic handling of physical and operational constraints through the use of constrained optimisation. It has also been shown to successfully exploit plant redundancy to maintain a level of control in scenarios when faults are present. Unfortunately, the computational complexity of each individual iteration of the algorithm to solve the optimisation problem scales cubically with the number of plant inputs, so the computational demands are high for large MIMO plants. Multiplexed MPC only calculates changes in a subset of the plant inputs at each sampling instant, thus reducing the complexity of the optimisation. This paper demonstrates the application of multiplexed model predictive control to a large transport airliner in a nominal and a contingency scenario. The performance is compared to that obtained with a conventional synchronous model predictive controller, designed using an equivalent cost function. © 2012 AACC American Automatic Control Council).

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The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

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This paper presents a methodology to address reactive power compensation using Evolutionary Particle Swarm Optimization (EPSO) technique programmed in the MATLAB environment. The main objective is to find the best operation point minimizing power losses with reactive power compensation, subjected to all operational constraints, namely full AC power flow equations, active and reactive power generation constraints. The methodology has been tested with the IEEE 14 bus test system demonstrating the ability and effectiveness of the proposed approach to handle the reactive power compensation problem.

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This paper describes a framework architecture for the automated re-purposing and efficient delivery of multimedia content stored in CMSs. It deploys specifically designed templates as well as adaptation rules based on a hierarchy of profiles to accommodate user, device and network requirements invoked as constraints in the adaptation process. The user profile provides information in accordance with the opt-in principle, while the device and network profiles provide the operational constraints such as for example resolution and bandwidth limitations. The profiles hierarchy ensures that the adaptation privileges the users' preferences. As part of the adaptation, we took into account the support for users' special needs, and therefore adopted a template-based approach that could simplify the adaptation process integrating accessibility-by-design in the template.