Wind-thermal systems operation optimization considering emission problem

This paper proposes a hybrid computational framework based on Sequential Quadratic Programming (SQP) and Particle Swarm Optimization (PSO) to address the Combined Unit Commitment and Emission (CUCE) problem. By considering a model which includes both thermal generators and wind farms, the proposed hybrid computational framework can minimize the scheduling cost and greenhouse gases emission cost. The viability of the proposed hybrid technique is demonstrated using a set of numerical case studies. Moreover, comparisons are performed with other optimization algorithms. The simulation results show that our hybrid method is better in terms of the speed and accuracy. The main contribution of this paper is the development of a emission unit commitment model integrating with wind energy and combining the SQP and PSO methods to achieve faster and better performance optimization

Urban heat island and wind flow characteristics of a tropical city

 Urban Heat Island (UHI) has become a growing concern to the quality of densely built urban environments, particularly in tropical cities. Wind speed has widely been reported to have decreased the intensity of heat island effect in urban areas. The cooling effect of the wind helps to mitigate the adverse effects of heat island on the micro climate and human thermal comfort. This paper investigates the existence of heat island in Muar, one of the fast growing cities in southern part of Malaysia and its possible causes, and then examines the effects of different urban geometry on the wind flow. The results of this study indicate that the chaotic development in Muar has caused reduced ventilation in urban canyons. The heat island intensity in the city center was recorded as 4. °C during the day and 3.2. °C during the night. Investigation of various urban geometry modifications showed that step up configuration was the most effective geometry as it can distribute the wind evenly allowing the wind to reach even the leeward side of each building. © 2014 Elsevier Ltd.

An optimized mean variance estimation method for uncertainty quantification of wind power forecasts

A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems. © 2014 Elsevier Ltd. All rights reserved.

A novel fuzzy multi-objective framework to construct optimal prediction intervals for wind power forecast

The forecasting behavior of the high volatile and unpredictable wind power energy has always been a challenging issue in the power engineering area. In this regard, this paper proposes a new multi-objective framework based on fuzzy idea to construct optimal prediction intervals (Pis) to forecast wind power generation more sufficiently. The proposed method makes it possible to satisfy both the PI coverage probability (PICP) and PI normalized average width (PINAW), simultaneously. In order to model the stochastic and nonlinear behavior of the wind power samples, the idea of lower upper bound estimation (LUBE) method is used here. Regarding the optimization tool, an improved version of particle swam optimization (PSO) is proposed. In order to see the feasibility and satisfying performance of the proposed method, the practical data of a wind farm in Australia is used as the case study.

Demo abstract: wind measurements for water quality studies in urban reservoirs

Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

Giving solidity to pure wind: temporising as transformation

Jared Diamond asked the acclaimed evolutionary biologist Ernst Mayr (1904-2005) why Aristotle didn’t come up with the theory of evolution. Mayr’s answer was ‘Frage stellen’ which Diamond translates as ‘a way of asking questions [sic]’ (Byrne 2013). The idea that a particular way-of-asking might generate a particular way-of-knowing and, indeed, a particular branch-of-knowledge, is utterly intriguing, especially when we frame the practice of creative writing in those terms: as a way of asking questions.Drusilla Modjeska unpacks the concept of ‘temporising’ in her article ‘Writing Poppy’ (Modjeska 2002: 75). This discussion invites us to consider the generative capabilities of the temporising space – as an imaginative space for writers, as an alternate way of asking questions … of seeing, being, knowing. In narrative, the questions that underpin the work do not necessarily appear in the surface-content of the text. In this way, the story is a metaphorical representation of the questions that lie beneath. As Aristotle suggests, metaphor relies on ‘an intuitive perception of the similarity [to homoion theorein] in dissimilars’ (Ricoeur 1977: 23). In narrative we contemplate a question, or an idea, within the context of a metaphorical other. This is a form of temporising: of ‘slip[ping] into other time frames’ as a means of ‘retreat[ing] and consider[ing]’ (Modjeska 2002: 75, 76). In narrative time, we consider one thing through an alternate temporal lens. We prevaricate in otherness.Fiction-making represents a very particular way of asking questions. With reference to the process of writing the short story – ‘Everything that matters is silvery white’ – it is clear that ‘making’ narrative is a way of asking questions that is assisted by the transformative temporising space.

Sowing the wind

'Sowing the wind' is a chapter from the novel manuscript 'The Earth does not get fat'

Sensor placement and measurement of wind for water quality studies in urban reservoirs

We study the water quality in an urban district, where the surface wind distribution is an essential input but undergoes high spatial and temporal variations due to the impact of surrounding buildings. In this work, we develop an optimal sensor placement scheme to measure the wind distribution over a large urban reservoir using a limited number of wind sensors. Unlike existing solutions that assume Gaussian process of target phenomena, this study measures the wind that inherently exhibits strong non-Gaussian yearly distribution. By leveraging the local monsoon characteristics of wind, we segment a year into different monsoon seasons that follow a unique distribution respectively. We also use computational fluid dynamics to learn the spatial correlation of wind. The output of sensor placement is a set of the most informative locations to deploy the wind sensors, based on the readings of which we can accurately predict the wind over the entire reservoir in real time. Ten wind sensors are deployed. The in-field measurement results of more than 3 months suggest that the proposed sensor placement and spatial prediction scheme provides accurate wind measurement that outperforms the state-of-the-art Gaussian model based on interpolation-based approaches.

Migrating swans profit from favourable changes in wind conditions at low altitude

Because energy reserves limit flight range, wind assistance may be of crucial importance for migratory birds. We tracked eight Bewick's swans Cygnus columbianus bewickii, using 95-g satellite transmitters with altimeters and activity sensors, during their spring migration from Denmark to northern Russia in 1996. During the 82 occasions where a swan's location was recorded in flight, average flight altitude was 165 m a.s.1. with a maximum of 759 m a.s.1., despite winds often being more favourable at higher altitudes. We also counted Bewick's swans departing from the Gulf of Finland and subsequently passing an observatory in the next major stop-over area 800 km further north in the White Sea, northern Russia, during the springs of 1994, 1995 and 1996. A comparison of these counts with wind data provided evidence for Bewick's swans using favourable changes in wind conditions to embark on migration. Changes in the numbers of birds arriving in the White Sea correlated best with favourable changes in winds in the Gulf of Finland 1 day earlier. Again, migratory volume showed a correlation with winds at low altitudes only, despite wind conditions for the swans being more favourable at high altitudes. We conclude that the relatively large Bewick's swan tends to gear its migration to wind conditions at low altitude only. We argue that Bewick's swans do not climb to high altitudes because of mechanical and physiological limitations with respect to the generation of power for flight and to avoid rapid dehydration.

Skipping swans: fuelling rates and wind conditions determine differential use of migratory stopover sites of Bewick's Swans Cygnus bewickii

Some migratory birds refuel at stopover sites that they by-pass on the return trip. In theory, this skipping behaviour is only expected in time-selected migrants when the overflown site is of a lower quality than the departure site. We provide empirical evidence that quality differences in stopover sites are the cause for skipping in Bewick's Swans Cygnus bewickii tracked by satellite telemetry. Two and five complete tracks were recorded in spring and autunm, respectively, showing that the White Sea was visited for c. 2 weeks in spring, but by-passed (or visited for a few days at the most) in autumn. Skipping of the White Sea in autumn was predicted by a dynamic programming model which was based on calculated gain rates during stopover in the Pechora Delta and the White Sea. This prediction was not sensitive to plausible variations in gain rates. Relative to the Pechora Delta the White Sea is a poor site because a large tidal amplitude precludes foraging on the beds of the submerged macrophyte Fennel Pondweed Potamogeton pectinatus during high tide. The dynamic programming model predicted a fast autunm migration. However, the phenology of autunm arrival dates of Bewick's Swans on the wintering grounds revealed that only in three out of ten years a significant number of birds was able to reach the wintering grounds without refuelling. In the other years, unfavourable wind conditions along the Russian/Baltic part of the route prevented such non-stop migration.

Flight costs and fuel composition of a bird migrating in a wind tunnel

We studied the energy and protein balance of a Thrush Nightingale Luscinia luscinia, a small long-distance migrant, during repeated 12-hr long flights in a wind tunnel and during subsequent two-day fueling periods. From the energy budgets we estimated the power requirements for migratory flight in this 26 g bird at 1.91 Watts. This is low compared to flight cost estimates in birds of similar mass and with similar wing shape. This suggests that power requirements for migratory flight are lower than the power requirements for nonmigratory flight. From excreta production during flight, and nitrogen and energy balance during subsequent fueling, the dry protein proportion of stores was estimated to be around 10%. A net catabolism of protein during migratory flight along with that of fat may reflect a physiologically inevitable process, a means of providing extra water to counteract dehydration, a production of uric acid for anti-oxidative purposes, and adaptive changes in the size of flight muscles and digestive organs in the exercising animal.