Over the last decade, India has started to concentrate earnestly on renewable energy. The Indian government, as well as different state governments, are adopting policy instruments such as feed in tariff, captive consumption, renewable purchase obligation and generation based incentive etc. aimed at renewable energy development. This paper evaluates the effectiveness of state level incentives for the development of wind energy in India. Fixed effect panel data modelling technique of econometric analysis is used to analyse the data of 26 Indian states in 11 years. The results show that feed in tariff and captive consumption are the significant predictors of wind energy development. However, renewable purchase obligation does not affect wind energy significantly.
In most isolated sites situated in south Algeria, the diesel generators are the major source of electrical energy. Indeed, the power supply of these remote regions still poses order problems (technical, economical and ecological). The electricity produced with the help of diesel generators is very expensive and responsible for CO2 emission. These isolated sites have significant wind energy potential. Hence, the use of twinning wind-diesel is widely recommended, especially to reduce operating deficits. The objective of this paper is to study the global modeling of a hybrid system which compounds wind turbine generator, diesel generator and storage system. This model is based on the control strategy to optimize the functioning of the hybrid system and to consolidate the gains to provide proper management of energy sources (wind, diesel, battery) depending on the load curve of the proposed site. The management is controlled by a controller which ensures the opening/closing of different power switches according to meteorological conditions (wind speed, air mass, temperature, etc).
The purpose of this paper is to improve the control performance of the variable speed, constant frequency doubly-fed induction generator in the wind turbine generation system by using fuzzy logic controllers. The control of the rotor-side converter is realized by stator flux oriented control, whereas the control of the grid-side converter is performed by a control strategy based on grid voltage orientation to maintain the DC-link voltage stability. An intelligent fuzzy inference system is proposed as an alternative of the conventional proportional and integral (PI) controller to overcome any disturbance, such as fast wind speed variation, short grid voltage fault, parameter variations and so on. Five fuzzy logic controllers are used in the rotor side converter (RSC) for maximum power point tracking (MPPT) algorithm, active and reactive power control loops, and another two fuzzy logic controllers for direct and quadratic rotor currents components control loops. The performances have been tested on 1.5 MW doubly-fed induction generator (DFIG) in a Matlab/Simulink software environment.
This paper addresses the attuned use of multi-converter flexible alternative current transmission systems (M-FACTS) devices and demand response (DR) to perform congestion management (CM) in the deregulated environment. The strong control capability of the M-FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare (SW) and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem (MOP) based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution (NTVE) based multi-objective particle swarm optimization (MOPSO) style is formed. Fuzzy decision-making (FDM) and technique for order preference by similarity to ideal solution (TOPSIS) approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution (MOPSO-NTVE). In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR & unified power flow controller (UPFC) and the DR & M-FACTS are presented.
Harvesting the energy from ocean waves is one of the greatest attractions for energy engineers and scientists. Till date, plenty of methods have been adopted to harvest the energy from the ocean waves. However, due to technological and economical complexity, it is intricate to involve the majority of these energy harvesters in the real ocean environment. Effective utilization and sustainability of any wave energy harvester depend upon its adaptability in the irregular seasonal waves, situation capability in maximum energy extraction and finally fulfilling the economic barriers. In this paper, the front end energy conversions are reviewed in detail which is positioned in the first stage of the wave energy converter among other stages such as power take off (PTO) and electrical energy conversion. If the recent development of these front end energy conversion is well known then developing wave energy converter with economic and commercial viability is possible. The aim of this review is to provide information on front end energy conversion of a point absorber and emphasize the strategies and calamity to be considered in designing such kinds of devices to improve the energy harvesting competence. This will be useful to the engineers for speeding up the development of a matured point absorbing type wave energy converter.
This paper aims to propose monthly models responsible for the theoretical evaluation of the global horizontal irradiance of a tropical region in India which is Sivagangai situated in Tamilnadu. The actual measured global horizontal irradiance hails from a 5 MW solar power plant station located at Sivagangai in Tamilnadu. The data were monitored from May 2011 to April 2013. The theoretical assessment was conducted differently by employing a programming platform called Microsoft Visual Basic 2010 Express. A graphical user interface was created using Visual Basic 2010 Express, which provided the evaluation of empirical parameters for model formulation such as daily sunshine duration (S), maximum possible sunshine hour duration (S0), extra terrestrial horizontal global irradiance (H0) and extra terrestrial direct normal irradiance (G0). The proposed regression models were validated by the significance of statistical indicators such as mean bias error, root mean square error and mean percentage error from the predicted and the actual values for the region considered. Comparison was made between the proposed monthly models and the existing normalized models for global horizontal irradiance evaluation.
In recent years, many different techniques are applied in order to draw maximum power from photovoltaic (PV) modules for changing solar irradiance and temperature conditions. Generally, the output power generation of the PV system depends on the intermittent solar insolation, cell temperature, efficiency of the PV panel and its output voltage level. Consequently, it is essential to track the generated power of the PV system and utilize the collected solar energy optimally. The aim of this paper is to simulate and control a grid-connected PV source by using an adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) controller. The data are optimized by GA and then, these optimum values are used in network training. The simulation results indicate that the ANFIS-GA controller can meet the need of load easily with less fluctuation around the maximum power point (MPP) and can increase the convergence speed to achieve the MPP rather than the conventional method. Moreover, to control both line voltage and current, a grid side P/Q controller has been applied. A dynamic modeling, control and simulation study of the PV system is performed with the Matlab/Simulink program.
Based on energy conservation equation and Darcy’s law, a model of beach well infiltration intake system applied in a seawater source heat pump system was established. The model consists of the seawater seepage and the heat transfer process. A porous medium model in a software named FLUENT was applied to simulate the seepage and the heat transfer process. This model was also validated by field experiment conducted on the seashore in Tianjin, China. The maximum relative error between simulation results and experimental results was 2.1% (less than 5%), which was acceptable in engineering application. The porosity and coefficient of thermal conductivity of the aquifer soil were determined to be 0.49 W/(m·K) and 1.46 W/(m·K), respectively in the simulation. In addition, the influencing factors of pumping water of beach well were also analyzed. The pumping water was found to increase when the distance between the beach well and the impervious boundary becomes longer, when the distance between the beach well and the supplying water source shortens, when the diameter of the beach well enlarges, and the drawdown enlarges.
The ground-water heat-pump system (GWHP) provides a high efficient way for heating and cooling while consuming a little electrical energy. Due to the lack of scientific guidance for operating control strategy, the coefficient of performance (COP) of the system and units are still very low. In this paper, the running strategy of GWHP was studied. First, the groundwater thermal transfer calculation under slow heat transfixion and transient heat transfixion was established by calculating the heat transfer simulation software Flow Heat and using correction factor. Next, heating parameters were calculated based on the building heat load and the terminal equipment characteristic equation. Then, the energy consumption calculation model for units and pumps were established, based on which the optimization method and constraints were established. Finally, a field test on a GWHP system in Beijing was conducted and the model was applied. The new system operation optimization idea for taking every part of the GWHP into account that put forward in this paper has an important guiding significance to the actual operation of underground water source heat pump.
This paper explored the feasibility and benefit of CO2 utilization as gasifying agent in the autothermal gasification process. The effects of CO2 injection on reaction temperature and producer gas composition were examined in a pilot scale downdraft gasifier by varying the CO2/C ratio from 0.6 to 1.6. O2 was injected at an equivalence ratio of approximately 0.33–0.38 for supplying heat through partial combustion. The results were also compared with those of air gasification. In general, the increase in CO2 injection resulted in the shift of combustion zone to the downstream of the gasifier. However, compared with that of air gasification, the long and distributed high temperature zones were obtained in CO2-O2 gasification with a CO2/C ratio of 0.6–1.2. The progress of the expected CO2 to CO conversion can be implied from the relatively insignificant decrease in CO fraction as the CO2/C ratio increased. The producer gas heating value of CO2-O2 gasification was consistently higher than that of air gasification. These results show the potential of CO2-O2 gasification for producing high quality producer gas in an efficient manner, and the necessity for more work to deeply imply the observation.