The Exploitation Of Renewable Energy Sources Engineering Essay

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Kodjo Agbossou et al (2004) presented a work that the Hydrogen Research Institute (HRI) has designed and developed a control system with power conditioning devices to manage the energy flow throughout a RE system to assure continuous supply of energy to the load, which this work emphasis to test the developed control system for autonomous long-term operation and technical feasibility of the stand-alone RE system based on Electrolytic hydrogen (H2) [4].

S. Arul Daniel and N. AmmasaiGounden (2004) proposed an isolated hybrid scheme employing a simple three-phase square-wave inverter to integrate a photovoltaic array with a wind-driven induction generator. For the first time, a dynamic mathematical model of the hybrid scheme with variables expressed in - synchronous reference frame has been developed. The model is implemented in the power system blockset platform and a comparison has been made between transients simulated and transients obtained in an experimental prototype [5].

Amin S. H (2007) studied the data of 11 meteorological stations in Iraqi Kurdistan Region, describing the topography of Kurdistan region, the patterns of pressure, air masses and wind speed. The study analyzed the differences of the wind directions and its speed as a result of the season's changing. Using wind shear of 0.14, this thesis extrapolated the wind speed to 50m, 75m and 100m heights and the yearly power estimated on 75m height using a wind turbine specification [6].

Mohamed Shwan Husami (2007) studied the potential of renewable energy in Iraqi Kurdistan region, regarding to wind data sources the wind speed extrapolated from 2m to 10m then from 10m to 50m height. The Weibull distribution two-parameters are used to characterize wind regimes using HOMER computer model, the average monthly sunshine and the average monthly solar radiation are calculated in Kurdistan region. In order to study the impact of renewable energy in Kurdistan, a small village has been taken as a model and provided with energy from renewable resources [7].

Dong-Jing Lee and Li Wang (2008) presented small-signal stability analyzed results of an autonomous hybrid renewable energy power generation/energy storage system connected to isolated loads using time-domain simulations. A time-domain approach based on three mathematical models for three studied cases under various operating points and disturbance conditions is performed. It can be concluded from the simulation results that the proposed hybrid power generation/energy storage system feeding isolated loads can be properly operated to achieve system power-frequency balance condition [8].

Salahaddin Abdul-Qader Ahmad (2009) stadied statistical analysis of the wind speed data for 23 meteorological stations in Iraqi Kurdistan Region, which the roughness effects zo determined for all stations, the wind data extrapolated to 45m using power law formula, the mean wind speed direction and the persistence of the resultant direction are also found for most of the stations, in this research the Weibull function is used for representing wind speed frequency distribution, which its parameters (shape and scale) are found by Maximum Likelihood method. A Rayleigh function is also used as a comparison. The analysis also includes seasonal changes in wind speed values and the seasonal wind power density is estimated for all stations, also a mathematical formulation using a two parameter Weibull wind speed distribution established to estimate the wind energy generated by and ideal wind turbine and the annual actual wind energy [9].

Sándor Bartha (2009) evaluated the solar and wind energy potential from measured data realized at the Black Sea coast, then developing and modeling a small-scale PV wind energy system, which can supply with electricity a rural application sited in remote area with examining and analyzing a small-scale wind turbine used for this stand-alone application and examining and evaluating the optimal relation between renewable energy fraction and PV wind rate. [10].

Salman K Salman (2010) presented an investigation which is based on a practical project that was executed in collaboration between academia and industry. It involves design and installation of a prototype integrated renewable energy system which consists of two 15 kW wind turbines, electrolyser, and fuel cell system (FCS) and the associated control equipment [2].

Marija S. Todorović et al (2011) outlined the intrinsic harmony of the traditional village houses encompassing efficiency and balanced use of renewable materials and energy sources. Further paper reviews technical advances in integrating energy efficiency, solar and other renewable energy sources in new and existing buildings, to approach sustainable net Zero Energy Buildings, villages and cities. [11].

Regarding to wind energy studies, the following works are presented:

Suresh.H.Jangamshetti, V.Guruprasada Rau (1999) investigated site matching of wind turbine generators based on appropriate selection of statistical models and means of wind speed data. The wind speed means were computed using arithmetic mean, root mean square and cubic mean cube root. Wind Speed frequency distributions are modelled using Weibull and Rayleigh probability density functions. The analytically obtained capacity factors are validated by comparing with the actual capacity factors, it is observed that the capacity factors computed from the Weibull statistical model using cubic mean of wind speed data fairly match the actual capacity factors. Various commercially available wind turbine generators are used for site matching study [12].

James W. Taylor et al (2009) investigated the methods for predicting the probability density function of generated wind power from one to ten days ahead. A density forecasts from weather ensemble predictions generated from atmospheric models and compared to density forecasting from statistical time series models which results that the weather ensemble predictions have strong potential for wind power forecasting [13].

Ravita D. Prasad et al (2009) presented the estimate for annual wind energy yield for the Vadravadra site in Gau Island in Fiji. It also presents a method for finding the optimum wind turbine that can be installed at a site and the kind of wind turbine that should be installed at a site, where cyclone may hit the area [14].

While in the field of solar energy, some of the investigation and studies carried out by authors are as the following:

John J. Bzura (1995), from 1986 onward, New England Electric has carried out and supported a wide range of research, development and demonstration projects related to the use of solar photovoltaic (PV) energy. Described each project and summarizes performance to date [15].

Minwon Park and In-Keun Yu (2004) proposed a novel real-time simulation method for PV generation systems under real weather conditions using a real-time digital simulator (RTDS). - curves of a real PV panel are tested using electric load device, and a hypothetical network of the tested PV panel is created on the RTDS by arranging electrical components from the customized component model libraries. The real weather conditions, insolation, and temperature of the PV panel, are interfaced through the analog input ports of the RTDS for real-time simulation. The outcomes of the simulation demonstrate the effectiveness of the proposed simulation technique, and also show that cost-effective verification of availability and stability of PV generation systems is possible using the built-in simulator [16].

Eyad S. Hrayshat (2009) assessed the viability of solar photovoltaic as an electricity generation source for Jordan, Long-term monthly average daily global solar radiation and sunshine duration data for 24 locations were studied and analyzed, and formed an input to the RetScreen Software for evaluation and analysis of the proposed plant's electricity production and economic feasibility [17].

Abd El-Shafy A. Nafeh (2009) presented a study on a stand-alone photovoltaic (PV) system to provide the required electricity for a single residential household in Sinai Peninsula of Egypt. The complete design of the suggested system is carried out, such that the site radiation data and the electrical load data of a typical household in the considered site are taken into account during the design steps. Also, the life cycle cost (LCC) analysis is conducted to assess the economic viability of the system. The results of the study encouraged the use of the PV systems to electrify the remote sites of Egypt [18].

In addition to the energy analyzing the authors had made investigations for capacity sizing as the following works:

Riad Chedid, Saifur Rahman (1997) proposed analysis employs linear programming techniques to minimize the average production cost of electricity while meeting the load requirements in a reliable manner, and takes environmental factors into consideration both in the design and operation phases. Such a power system is mainly composed of solar, wind and battery sets; and depending on the application, either diesel engines or a grid option are considered for back-up purposes [19].

W.D. Kellogg et al (1998) presented the results of investigations on the application of wind, photovoltaic (PV), and hybrid wind/PV power generating systems for utilization as stand- alone systems. A simple numerical algorithm has been developed for generation unit sizing. It has been used to determine the optimum generation capacity and storage needed for a stand-alone, wind, PV, and hybrid wind/PV system for an experimental site in a remote area with a typical residential load. Generation and storage units for each system are properly sized in order to meet the annual load and minimize the total annual cost to the customer. In addition, an economic analysis has been performed for the above three scenarios and is used to justify the use of renewable energy versus constructing a line extension from the nearest existing power line to supply the load with conventional power. Annual average hourly values for load, wind speed, and insolation have been used [20].

Juhari Ab. Razak et al (2007) discussed the optimization of the hybrid system in context of minimizing the excess energy and cost of energy. The hybrid of pico hydro, solar, wind and generator and battery as back-up is the basis of assessment. The system configuration of the hybrid is derived based on a theoretical domestic load at a remote location and local solar radiation, wind and water flow rate data. Three demand loads are used in the simulation using HOMER to find the optimum combination and sizing of components. Another set of demand loads is used to investigate the effect of reducing the demand load against the dominant power provider of the system. The results show that the cost of energy can be reduced to about 50% if the demand load is increased to the maximum capacity. Reducing the load to the capacity of the dominant power provider will reduce the cost of energy by 90% [21].

Troy Knutson and P.E (2011) studied many factors that affect the economics of small grid connected renewable energy generation system of 50kW and below. They range from determining a site, maintenance, project life and financing, using a financial calculator that was created by Microsoft Excel [22].

Moreover to the works relative to load forecasting by artificial neural network (ANN) the authors had been presented the following:

Tetsuya Kakkonda et al (2003) proposed an electric load forecasting method by neural networks considering various load types, which consists of two forecasting steps, Loads of all load types of specific three time zones are forecasted and the daily load curve for next day [23].

Ref N Cross and C. T. Gaunt (2003) described the methods used to determine hourly activity load curves for use in energy models. Conditional demand analysis (CDA) curves have been derived from surveys conducted in, and the logging of, 15 rural villages. Appliance curves developed using the CDA curves and penetration levels; these can be combined and used to develop the total activity curves (e.g. cooking). These activity curves can then be used to specify the demand for the relevant energy consuming activities for a rural village [24].

Paras Mandal et al (2005) presented an approach for short-term electricity price and load forecasting using neural network model, in which load and price curves are forecasted by using the information of the days being similar to that of the forecast day [25].

S. Fan, K. Methaprayoon, and W. J. Lee (2007) proposed an ANN-based multi-region load forecasting system, which a detailed investigation to the regional weather and electricity demand characteristics is made, and quantify the load diversity within the system. The load diversity factor for the twenty four regions is calculated using daily to monthly peak load [26].

A. A. Rasool et al (2009) proposed an approach for Short Term Load Forecasting (STLF) which combines Wavelet Transform (WT) and Artificial Neural Network (ANN). It is well known that the electrical load at any time can be considered as a linear combination of different frequencies. The daily load curves are decomposed into approximation part associated with low frequency and some detail parts associated with high frequency by means of (WT). Feed Forward Neural Networks are trained by low frequencies and corresponding average temperature or maximum and minimum temperature to predict the approximation part for the next seven days [27].

Shu Fan et al (2009) proposed a short-term load forecasting methodology, which combines forecasting and ensemble learning techniques, combining forecasting using adaptive coefficients is used to produce more accurate temperature prediction by sharing the strength of different meteorological predictions. Then, to improve the forecasting accuracy and generalization performance, ensemble learning technique has been applied for the training and forecasting of ANN, where several sub-ANNs are generated and integrated based on bagging [28].

Ju Yi-feng and Wu Shu-wen (2010), Genetic Algorithm - Support vector regression (GA-SVR) predicting model is developed to predict village electrical load [29].