Abstract-The market for battery powered and plug-in hybrid electric vehicles is currently limited, but this is expected to grow rapidly with the increased concern about the environment and advances in technology. Due to their high energy capacity, mass deployment of electrical vehicles will have significant impact on power networks. This impact will dictate the design of the electric vehicle interface devices and the way future power networks will be designed and controlled. This paper presents the results of an analysis of the impact of electric vehicles on existing power distribution networks. Evaluation of supply/demand matching and potential violations of statutory voltage limits, power quality and imbalance are presented.

(2012) Generic maximum power point tracking controller for small-scale wind turbines. Renewable Energy, 44. pp. 72-79.

No abstract

Thermochemical processes, which include pyrolysis, torrefaction, gasification, combustion, and hydrothermal conversions, are perceived to be more efficient in converting waste biomass to energy and value-added products than biochemical processes. From the chemical point of view, thermochemical processes are highly complex and sensitive to numerous physicochemical properties, thus making reactor and process modeling more challenging. Nevertheless, the successful commercialization of these processes is contingent upon optimized reactor and process designs, which can be effectively achieved via modeling and simulation. Models of various scales with numerous simplifying assumptions have been developed for specific applications of thermochemical conversion of waste biomass. However, there is a research gap that needs to be explored to elaborate the scale of applicability, limitations, accuracy, validity, and special features of each model. This review study investigates all above mentioned important aspects and features of the existing models for all established industrial thermochemical conversion processes with emphasis on waste biomass, thus addressing the research gap mentioned above and presenting commercial-scale applicability in terms of reactor designing, process control and optimization, and potential ways to upgrade existing models for higher accuracy.

In order to obtain maximum power output of a Wind Energy Conversion System (WECS), the rotor speed needs to be optimised for a particular wind speed. However, due to inherent inertia, the rotor of a WECS cannot react instantaneously according to wind speed variations. As a consequence, the performance of the system and consequently the wind energy conversion capability of the rotor are negatively affected. This study considers the use of a time series Adaptive Linear Prediction (ALP) technique as a means to improve the performance and conversion efficiency of wind turbines. The ALP technique is introduced as a real time control reference to improve optimal control of wind turbines. In this study, a wind turbine emulator is developed to evaluate the performance of the predictive control strategy. In this regard, the ALP reference control method was applied as a means to control the torque/speed of the emulator. The results show that the employment of a predictive technique increases energy yield by almost 5%.