Sathyajith Mathew

Analysis of wind regimes for energy estimation

Supplementing our energy base with clean and renewable sources of energy has become imperative due to the present days energy crisis and growing environmental consciousness. Wind is one of the potential renewable energy sources, which can be harnessed in a commercial scale for various end-uses. A precise knowledge of wind regime characteristics is a pre-requisite for the efficient planning and implementation of any wind energy project. In the present study, a method for characterizing wind regimes, bringing out their energy potential, is discussed. A Rayleigh distribution was adopted for defining the distribution of wind velocity in terms of its probability density and cumulative distribution functions. Expressions to compute the energy density, energy available in the wind spectra in a time period and the energy received by turbine have been developed. A method to identify the most frequent wind speed and velocity that carries maximum amount of energy with it, is also discussed. The analysis of wind energy potential of a eight sites in Kerala, India, adopting this procedure is presented. The performance of three wind turbines differing in their working velocity band, at these sites are compared. The effect of cut-in and cut-out wind speeds on wind turbine performance are also analyzed.

Modelling the integrated output of wind-driven roto-dynamic pumps

Roto-dynamic pumps offer better match with wind rotors for low lift-high discharge water pumping applications. Tremendous potential for such systems does exist in many developing countries like India. In the present study, a mathematical model is proposed for estimating the performance of wind-driven roto-dynamic pumps at various operating conditions. In contrast with the earlier attempts in this direction, an integrated approach incorporating the characteristics of the rotor, pump and the wind regime is envisaged for formulating the model. The model is validated using the field performance data from a 5 m, five-bladed experimental rotor coupled with a low speed centrifugal pump. Performance of the system at fluctuating conditions of wind regimes is estimated and compared with that of a system with reciprocating pump. Wind driven roto-dynamic pumps are found to offer distinctly better performance than the conventional system with reciprocating pumps. Effects of the specific speed and specific diameter of the pump on the gear ratio and optimum pump size are also discussed. A low specific speed roto-dynamic pump with reasonable specific diameter is found to be suitable for coupling with wind rotors for water pumping application.

A NOVEL LOW REYNOLDS NUMBER AIRFOIL DESIGN FOR SMALL HORIZONTAL AXIS WIND TURBINES

In order to improve the performance of small horizontal axis wind turbines at low wind speed, this study designs a novel airfoil section with an optimum transition ramp through multipoint inverse design method. A viscous analysis code is used to close the design loop. Further, Shear stress transport-transition model in ANSYS-Fluent is employed with modified constants to analyze the flow and aerodynamic performance of the airfoil at Reynolds numbers 60 000, 100 000, 200 000, 300 000 and 500 000. Next we consider the designing of a 2m rotor from the new airfoil section using an evolutionary algorithm for optimization. The power coefficient and self starting of a small 2m wind turbine is improved significantly with the chosen generator resistive torque of 0.5Nm, the new airfoil section and the optimization technique for finding the optimal values of the parameters.

Analysis of Wind Regimes and Performance of Wind Turbines

With the present day’s energy crisis and growing environmental consciousness, the global perspective in energy conversion and consumption is shifting towards sustainable resources and technologies. This resulted in an appreciable increase in the renewable energy installations in different part of the world. For example, Wind power could register an annual growth rate over 25% for the past 7 years, making it the fastest growing energy source in the world. The global wind power capacity has crossed well above 160 GW today and several Multi-Megawatt projects-both on shore and offshore-are in the pipeline. Hence, wind energy is going to be the major player in realizing our dream of meeting at least 20% of the global energy demand by new-renewables by 2020.

The Wind-driven Regenerative Water-pump

Roto-dynamic pumps can offer attractive performance when coupled mechanically to wind rotors in shallow lift water pumping applications. However, the gearing ratio required in the transmission for such systems restricts their commercial acceptability. This problem can be reduced by selecting a pump with a very low specific speed, so that, for a particular flow and lift, the shaft need not rotate so fast. Therefore, a regenerative pump was designed and developed for wind powered water pumping applications. A semi-empirical approach was adopted for the design. Performance of the pump was evaluated under variable operating conditions. Power-speed characteristics of the pump at different pumping heads were established and superimposed on those of a suitable wind rotor, to identify the points of operation of the integrated rotor-pump system. With optimum gearing, the peak efficiency points of the rotor and the pump could be reasonably matched over a wide range of conditions. Operating speeds of the system at different wind speeds were estimated and then translated into discharge rates and overall system efficiency. The proposed wind pumping system, with the regenerative pump, performs better on shallow lifts than either wind-driven piston or centrifugal pumping systems.

3D layout optimization for large wind farms

This paper proposes a novel 3D micro-siting approach for optimal placement of wind turbines in the continuous space of a wind farm. Along with X and Y positions, hub height and rotor radius of each turbine is optimized to maximize the yield of the farm. Such 3D siting not only reduces the land requirement, but also extracts more power from the same site. Proposed 3D siting problem is formulated as a constrained optimization problem and solved by a particle swarm optimization (PSO) algorithm.

Exploring the Feasibility of Solar Photo-Voltaic Power Plants in Brunei Darussalam:

Aiming for a sustainable and secure energy future, policies are being formulated in Brunei Darussalam for supplementing the national energy base with renewable resources and technologies. Some preliminary studies in this direction indicated that solar energy could be a potential energy option for the country. Technical feasibility and economic viability of such grid integrated solar PV power plants, under the Bruneian environment, are investigated in this study. The prevailing energy scenario is analyzed and future trends in electricity consumption are predicted based on the time series energy use data. The forecast indicates that the annual electricity consumption may reach up to 4.32 Billion kWh by the year 2020. The possibility of exploiting the available solar energy resource for meeting this growing electricity demand is investigated. Five years solar radiation data from Maura district were collected and analyzed under the study. The solar energy resource is characterized in terms of monthly averaged total daily global, beam and diffused radiations and hourly variations in solar intensity. Availability of solar energy in the region is also statistically modeled using Beta distribution. Performance of a solar photovoltaic power plant under these levels of insolation was simulated using the RETScreen model. With a total panel area of 10,619 m2such a plant is expected to show a capacity factor of 18.1 per-cent and generate 1899.2 MWh electricity annually. This clearly indicates the technical feasibility of grid integrated solar power plants in Brunei Darussalam. Under the economic analysis, the unit cost of electricity generation was estimated to be BND 0.30/kWh. A detailed cost benefit analysis, over the life cycle of such power projects, is also presented.

Estimating the wake losses in large wind farms: A machine learning approach

Estimating the wake losses in a wind farm is critical in the short term forecast of wind power, following the Numerical Weather Prediction (NWP) approach. Understanding the intensity of the wakes and the nature of its propagation within the wind farm still remains a challenge to scientist, engineers and utility operators. In this paper, five different machine learning methods are used to estimate the power deficit experienced by wind turbines due to the wake losses. Production data from the Horns Rev offshore wind farm, Denmark, have been used for the study. The methods used are linear regression, linear regression with feature engineering, nonlinear regression, Artificial Neural Networks (ANN) and Support Vector Regression (SVR). Power developed by individual turbines located at different positions within the farm were computed based on the above methods and compared with the actual power measurements. With the respective Variance Normalized Root Mean Square Error (VNRMSE) of 0.21 and 0.22, models based on ANN and SVR could estimate the wind farm wake effects at an acceptable accuracy level. The study shows that suitable machine learning methods can effectively be used in estimating the power deficits due to wake effects experienced in large wind farms.

Algorithms for upgrading the resolution of aggregate energy meter data

Metering of the energy supplied to consumers is an important component of operations for utility providers. Several schemes have been employed for this purpose, including traditional postpaid and prepaid metering, and more advanced smart metering technology. Analysis of the data generated by these meters has the potential to provide insights into consumer characteristics and power consumption patterns, including consumer segmentation and anomaly detection. We describe the different types of power purchase and consumption data, as well as the analytics algorithms that can be applied to them. Most applications developed for energy meter data require high resolution information of the type provided by smart meters, thus leaving aggregate prepaid or postpaid meter schemes at a disadvantage. In this paper, we present analytics-based methodologies to upgrade aggregate prepaid and postpaid meter data resolution, which will allow smart meter analytics to be applied without expensive infrastructure upgrades.

Energy-Efficiency Potential of Behavioral Initiatives: An Experimental Case Study from Brunei

In several warm-climate countries, loads from air-conditioners constitute more than half of the energy consumed by residential buildings. Therefore improving the end-use efficiency of AC electricity consumption can yield significant benefits in terms of minimizing demand and energy subsidies, mitigating impacts of climate change, improving grid stability, and reducing the need for new investments in generation and transmission assets. In this work, we estimate savings that can be achieved through behavioral energy efficiency initiatives for residential households in a country with tropical climate. With the help of a pilot instrumentation covering different types of homes, we quantify the achievable savings from running ACs at higher set point temperature without sacrificing comfort and turning them off when not in use. Our analysis results indicate that simple behavioral adjustments can in fact deliver aggregate savings of about 19% as compared to business-as-usual energy consumption without much discomfort to residents.