Combining wind farms with concentrating solar plants to provide stable renewable power

We evaluate the extent to which a combination of wind power and concentrating solar power (CSP) may lead to stable and even baseload power by taking advantage of: 1) spatiotemporal balancing of solar and wind energy resources and 2) storage capabilities of CSP plants. A case study is conducted for the region of Andalusia in Spain. To this end, spatiotemporal variability of modeled CSP and wind capacity factors in a 3-km spatial resolution grid were analyzed based on principal component analysis (PCA) and canonical correlation analysis (CCA). Results reveal that renewable baseload power can be obtained in the study region by locating wind farms and CSP plants using balancing patterns derived from CCA and PCA. In addition, the power fluctuation reduction attained from these patterns was substantially higher than those obtained by interconnecting randomly-located wind farms and CSP plants across the study region. Results were particularly meaningful for the winter season. Upon considering storage capability of the CSP plants, results proved better. The main difference was a higher firm capacity value associated with spring and summer seasons. For the other seasons, the contribution of thermal storage capabilities of the CSP plants to stable power proved less relevant.     

Trivariate maximum entropy distribution of significant wave height,wind speed and relative direction

A trivariate maximum entropy distribution of significant wave height, wind speed and the relative direction is proposed here. In this joint distribution, all the marginal variables follow modified maximum entropy distributions, and they are combined by a correlation coefficient matrix based on the Nataf transformation. The methods of single extreme factors and of conditional probability are presented for the joint design of trivariate random variables. The corresponding sampling data about significant wave heights, wind speeds and the relative directions from a location in the North Atlantic is applied for statistical analysis, and the results show that the trivariate maximum entropy distribution is sufficiently good to fit the data, and method of conditional probability can reduce the design values efficiently.     

Investigation of the performance of a staggered configuration of tidal turbines using CFD

This paper investigates the influence of wake interaction and blockage on the performance of individual turbines in a staggered configuration in a tidal stream farm using the CFD based Immersed Body Force turbine modelling method. The inflow condition to each turbine is unknown in advance making it difficult to apply the correct loading to individual devices. In such cases, it is necessary to establish an appropriate range of operating points by varying the loading or body forces in order to understand the influence of wake interaction and blockage on the performance of the individual devices. The performance of the downstream turbines was heavily affected by the wake interaction from the upstream turbines, though there were accelerated regions within the farm which could be potentially used to increase the overall power extraction from the farm. Laterally closely packed turbines can improve the performance of those turbines due to the blockage effect, but this could also affect the performance of downstream turbines. Thus balancing both the effect of blockage and wake interaction continues to be a huge challenge for optimising the performance of devices in a tidal stream farm.     

Regarding the influence of the Van der Hoven spectrum on wind energy applications in the meteorological mesoscale and microscale

We demonstrate the use of high frequency data (HFD) to reproduce the power spectrum shown by Van der Hoven in 1957. His work represents the basis of wind energy standards such as averaging and variability in the frequency domain. Our results unveil discrepancies with Van der Hoven's approach, which can be related to constraints in the computing capabilities in the 1950's. We show a major eddy-energy peak at a period of 2 days and a smaller eddy-energy peak contribution at frequencies higher than the region known as the spectrum gap. The variance calculated by the area under the curve indicated that the spectral energy is mainly due to the Power Spectral Density (PSD) values located in the microscale region. We calculated the economic value of this energy based on the turbulence kinetic energy of the wind data set. We also conclude that, given the results of the present study, HFD analysis in the frequency domain uncover eddy energy peaks that determine energy fluctuations in the short and long terms. This information is lost every time data are erased from current monitoring systems.     

Local models-based regression trees for very short-term wind speed prediction

This paper evaluates the performance of different types of Regression Trees (RTs) in a real problem of very short-term wind speed prediction from measuring data in wind farms. RT is a solidly established methodology that, contrary to other soft-computing approaches, has been under-explored in problems of wind speed prediction in wind farms. In this paper we comparatively evaluate eight different types of RTs algorithms, and we show that they are able obtain excellent results in real problems of very short-term wind speed prediction, improving existing classical and soft-computing approaches such as multi-linear regression approaches, different types of neural networks and support vector regression algorithms in this problem. We also show that RTs have a very small computation time, that allows the retraining of the algorithms whenever new wind speed data are collected from the measuring towers.     

Incentives to invest in liberalised electricity industries in the North and South. Differences in the need for suitable institutional arrangements

The issue of investment is all too often underplayed in deregulation reforms focused on market rules and de-integration measures. This presentation criticises first the optimistic approach of the theory of investment incentives through market signals when it is applied to deregulated electricity industries. The greater part of the investment in base-load and peak equipment should be made profitable by income from very high prices during peak and extreme peak periods, that raises a problem of political acceptability. The problem is then addressed in the context of the mature electricity industries in the North. Given the maturity of markets there, a number of modifications to the pure market model could be envisaged to strengthen incentives to invest, but none of them is perfect. The main way is to focus on adaptation of market rules on the supply of power at peaks and extreme peaks by considering “capacity adequacy” as a public good (with three solutions: capacity payment, reserve obligations, centralised procurement by auctioning for peak capacity). Observation of reforms suggests also the validity of some other solutions based on a limitation of the competition by allowing long-term contracts and vertical integration between production and supply. Finally the question is extended to the specific problem of developing countries characterised by irregular growth. It is argued that reforms must be designed in view of the importance of the need for investment through long-term coordination and reduction of investment risks. Indeed experiences of Latin American liberalised industries show that they have to include a number of competition-based imperfections and to allow ongoing exercise of market power in order to allow prices to rise above competition prices. The single buyer model or some variants of it appear to be good alternatives if one wishes to avoid the twists and turns of the competition paradigm. The difficulty with this model arises from the institutional conditions necessary to make it efficient and not overcostly.     

Solar energy powered Rankine cycle using supercritical CO2

A solar energy powered Rankine cycle using supercritical CO₂ for combined production of electricity and thermal energy is proposed. The proposed system consists of evacuated solar collectors, power generating turbine, high-temperature heat recovery system, low-temperature heat recovery system, and feed pump. The system utilizes evacuated solar collectors to convert CO₂ into high-temperature supercritical state, used to drive a turbine and thereby produce mechanical energy and hence electricity. The system also recovers heat (high-temperature heat and low-temperature heat), which could be used for refrigeration, air conditioning, hot water supply, etc. in domestic or commercial buildings. An experimental prototype has been designed and constructed. The prototype system has been tested under typical summer conditions in Kyoto, Japan; It was found that CO₂ is efficiently converted into high-temperature supercritical state, of while electricity and hot water can be generated. The experimental results show that the solar energy powered Rankine cycle using CO₂ works stably in a trans-critical region. The estimated power generation efficiency is 0.25 and heat recovery efficiency is 0.65. This study shows the potential of the application of the solar-powered Rankine cycle using supercritical CO₂.     

Flexibility valuation in the Brazilian power system: A real options approach

This paper presents a valuation study of operational flexibility in the complex Brazilian Power System. Thermopower plants represent operational flexibility for the national system operator provided they can be dispatched in dry periods to supply part of the load when reservoir waters are too low. Deficit costs can be avoided as a result.

We have adopted a real options approach to calculate the fair value of a financial subsidy to be paid to thermal generators for their availability to the system. A financial subsidy is mandatory for their economic feasibility and, therefore, for increased thermopower capacity in the Brazilian Power System. This is why this policy is currently being studied by Brazil's federal government.

In order to illustrate our modeling we have run the model for the southeast subsystem. We found a flexibility value of US$4.52 billion, which represents US$497/MW per year. This means that a 100 MW thermopower plant should receive US$49,700 for each year of its economic lifetime as a fair premium incentive to investments.     

基于Matlab/Simulink的火电厂热力系统模块化建模方法

本文以常规热平衡法为基础,引入模块建模的思想,阐述了模块化建模的开发过程,提出了一种火电厂热力系统模块化建模的方法。通过对热力系统分解、模块化,Matlab／Simulink为开发工具建立了火电厂常用设备的模型库,并给出实例验证了所提方法的正确性和可行性。     

Performance assessment of HCFC-22 window air conditioner retrofitted with R-407C

This paper presents the experimental performance analysis of a 1.5 TR window air-conditioner, retrofitted with R-407C, as a substitute to HCFC-22. Experimental results showed that R-407C, for the operating conditions covered in this study, had lower cooling capacity in the range 2.1–7.9% with respect to HCFC-22. The coefficient of performance for R-407C was lower in the range 7.9–13.5%. The power consumption of the unit with R-407C was higher in the range 6–7% than HCFC-22. The discharge pressures for R-407C were higher in the range 11–13% than HCFC-22.This paper also presents simulation results of heat exchangers of an HCFC-22 window air conditioner retrofitted with R-407C. The simulation has been carried out using EVAP-COND, a heat exchanger model developed by National Institute of Standards and Technology, U.S.A. The simulated evaporator capacities are within ±3% of the experimentally measured cooling capacities for both refrigerants. Simulation results for R-407C and HCFC-22 are compared. The exit temperatures of R-407C are lower by 1.9 °C to 5.2 °C in the condenser and are higher by 3.2 °C to 3.8 °C in the evaporator than HCFC-22. Evaporating pressures of R-407C are higher by 4.5–5.3% as compared to HCFC-22. The pressure drops of R-407C are lower in both the evaporator and the condenser as compared to HCFC-22. The outlet temperatures of air for HCFC-22 and R-407C in both heat exchangers are nearly the same.