Gas generation in interconnected power systems with high wind power penetration

Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integration of renewable energy into a historically inflexible power system. This paper examines peak and off peak benefits realised by installing a short term discharge storage unit in a system with a high penetration of wind power in 2020. A fully representative unit commitment and economic dispatch model is used to analyse two scenarios, one ‘with storage’ and one ‘without storage’. Key findings of this preliminary study show that wind curtailment can be reduced in the storage scenario, with a larger reduction in peak time ramping of gas generators is realised.

Special condition wind power forecasting based on Gaussian process and similar historical data

Due to the variability of wind power, it is imperative to accurately and timely forecast the wind generation to enhance the flexibility and reliability of the operation and control of real-time power. Special events such as ramps, spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken from both the local time and historic dataset is proposed and applied to make short-term predictions from 10 minutes to one hour ahead. A key idea is that the similar pattern data in history are properly selected and embedded in Gaussian Process model to make predictions. The results of the proposed algorithms are compared to those of standard Gaussian Process model and the persistence model. It is shown that the proposed method not only reduces magnitude error but also phase error.

Meanline Modeling of Inlet Recirculation in Automotive Turbocharger Centrifugal Compressors

This study provides a novel meanline modeling approach for centrifugal compressors. All compressors analyzed are of the automotive turbocharger variety and have typical upstream geometry with no casing treatments or preswirl vanes. Past experience dictates that inducer recirculation is prevalent toward surge in designs with high inlet shroud to outlet radius ratios; such designs are found in turbocharger compressors due to the demand for operating range. The aim of the paper is to provide further understanding of impeller inducer flow paths when operating with significant inducer recirculation. Using three-dimensional (3D) computational fluid dynamics (CFD) and a single-passage model, the flow coefficient at which the recirculating flow begins to develop and the rate at which it grows are used to assess and correlate work and angular momentum delivered to the incoming flow. All numerical modeling has been fully validated using measurements taken from hot gas stand tests for all compressor stages. The new modeling approach links the inlet recirculating flow and the pressure ratio characteristic of the compressor. Typically for a fixed rotational speed, between choke and the onset of impeller inlet recirculation the pressure ratio rises gradually at a rate dominated by the aerodynamic losses. However, in modern automotive turbocharger compressors where operating range is paramount, the pressure ratio no longer changes significantly between the onset of recirculation and surge. Instead the pressure ratio remains relatively constant for reducing mass flow rates until surge occurs. Existing meanline modeling techniques predict that the pressure ratio continues to gradually rise toward surge, which when compared to test data is not accurate. A new meanline method is presented here which tackles this issue by modeling the direct effects of the recirculation. The result is a meanline model that better represents the actual fluid flow seen in the CFD results and more accurately predicts the pressure ratio and efficiency characteristics in the region of the compressor map affected by inlet recirculation.

Caught in a 'spiral': barriers to healthy eating and dietary health promotion needs from the perspective of unemployed young people and their service providers

The number of young people in Europe who are not in education, employment or training (NEET) is increasing. Given that young people from disadvantaged backgrounds tend to have diets of poor nutritional quality, this exploratory study sought to understand barriers and facilitators to healthy eating and dietary health promotion needs of unemployed young people aged 16-20 years. Three focus group discussions were held with young people (n=14). Six individual interviews and one paired interview with service providers (n=7). Data were recorded, transcribed verbatim and thematically content analysed. Themes were then fitted to social cognitive theory (SCT). Despite understanding of the principles of healthy eating, a ‘spiral’ of interrelated social, economic and associated psychological problems was perceived to render food and health of little value and low priority for the young people. The story related by the young people and corroborated by the service providers was of a lack of personal and vicarious experience with food. External, environmental factors such as the proliferation and proximity of fast food outlets and the high perceived cost of ‘healthy’ compared to ‘junk’ food rendered the young people low in self-efficacy and perceived control to make healthier food choices. Agency was instead expressed through consumption of junk food and substance abuse. Both the young people and service providers agreed that for dietary health promotion efforts to succeed, social problems needed addressed and agency encouraged through (individual and collective) active engagement of the young people themselves.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

An approach to determine the local boundary of small disturbance voltage stability region in a cut-set power space:基于微扰的割集电压稳定域局部边界求解方法

A new approach to determine the local boundary of voltage stability region in a cut-set power space (CVSR) is presented. Power flow tracing is first used to determine the generator-load pair most sensitive to each branch in the interface. The generator-load pairs are then used to realize accurate small disturbances by controlling the branch power flow in increasing and decreasing directions to obtain new equilibrium points around the initial equilibrium point. And, continuous power flow is used starting from such new points to get the corresponding critical points around the initial critical point on the CVSR boundary. Then a hyperplane cross the initial critical point can be calculated by solving a set of linear algebraic equations. Finally, the presented method is validated by some systems, including New England 39-bus system, IEEE 118-bus system, and EPRI-1000 bus system. It can be revealed that the method is computationally more efficient and has less approximation error. It provides a useful approach for power system online voltage stability monitoring and assessment. This work is supported by National Natural Science Foundation of China (No. 50707019), Special Fund of the National Basic Research Program of China (No. 2009CB219701), Foundation for the Author of National Excellent Doctoral Dissertation of PR China (No. 200439), Tianjin Municipal Science and Technology Development Program (No. 09JCZDJC25000), National Major Project of Scientific and Technical Supporting Programs of China During the 11th Five-year Plan Period (No. 2006BAJ03A06). ©2009 State Grid Electric Power Research Institute Press.