This work presents a new adaptive scheme for energy management in an independent microgrid. The proposed energy management system has been developed to manage the utilization of power among the hybrid resources and energy storage system in order to supply the load requirement based on multi-agent system (MAS) concept and predicted renewable powers and load powers. Auto regressive moving average models have been developed for predicting the wind speed, atmospheric temperature, irradiation, and connected loads. The structure proposed in this paper includes renewable sources as primary source and storage system as secondary source. A wind generator and solar PV array system together acts as primary source, which supplies power to the local load most of the time in this energy management strategy. When they fail to meet the load demand, the secondary source present in the system will assist the primary source and help to attain the goal of satisfying load demand without interruption. If the primary source and secondary source together are not able to meet the load demand then load shedding will be executed according to the priority set. Thus the developed MAS algorithm co-ordinates the hybrid system components and achieves energy management among renewable energy sources, storage units, and load under varying environmental conditions and varying loads. STATCOM based compensation has been implemented to balance the reactive power demand and to mitigate the voltage fluctuations and harmonics on the AC bus. The proposed microgrid has been simulated with MAS concept in Matlab/Simulink environment. The results presented in this paper show cases the effectiveness of the proposed energy management controller.
Magnetic resonance imaging is a noninvasive technique that has been developed for its excellent depiction of soft tissue contrasts. Instruments capable of ultra-high field strengths, ≥7 Tesla, were recently engineered and have resulted in higher signal-to-noise and higher resolution images. This paper presents various subsystems of the MR imaging systems like the magnet subsystem, gradient subsystem, and also various issues which arise due to the magnet. Further, it also portrays finer details about the RF coils and transceiver and also various limitations of the RF coils and transceiver. Moreover, the concept behind the data processing system and the challenges related to it were also depicted. Finally, the various artifacts associated with the MR imaging were clearly pointed out. It also presents a brief overview about all the challenges related to MR imaging systems.
Many parts of remote locations in the world are not electrified even in this Advanced Technology Era. To provide electricity in such remote places renewable hybrid energy systems are very much suitable. In this paper PV/Wind/Battery Hybrid Power System (HPS) is considered to provide an economical and sustainable power to a remote load. HPS can supply the maximum power to the load at a particular operating point which is generally called as Maximum Power Point (MPP). Fuzzy Logic based MPPT (FLMPPT) control method has been implemented for both Solar and Wind Power Systems. FLMPPT control technique is implemented to generate the optimal reference voltage for the first stage of DC-DC Boost converter in both the PV and Wind energy system. The HPS is tested with variable solar irradiation, temperature, and wind speed. The FLMPPT method is compared with P&O MPPT method. The proposed method provides a good maximum power operation of the hybrid system at all operating conditions. In order to combine both sources, the DC bus voltage is made constant by employing PI Controllers for the second stage of DC-DC Buck-Boost converter in both Solar and Wind Power Systems. Battery Bank is used to store excess power from Renewable Energy Sources (RES) and to provide continuous power to load when the RES power is less than load power. A SPWM inverter is designed to convert DC power into AC to supply three phase load. An LC filter is also used at the output of inverter to get sinusoidal current from the PWM inverter. The entire system was modeled and simulated in Matlab/Simulink Environment. The results presented show the validation of the HPS design.
This paper presents the optimal sizing of PV/Wind/Fuel Cell/Battery Hybrid Energy System for energizing a Small Scale Industrial Application or a village domestic load of 200 kW. HOMER software is used for simulation of the complete system. The solar radiation data and wind speed data used in this paper are for the place of Coimbatore, Tamil Nadu, India which is located 11.0183° N longitude and 76.9725° E latitude. The optimized sizes of components of Hybrid Power System (HPS) are found based on Levelised Cost of Energy (LCE) and total Net Present Cost (NPC). The results are presented and compared for five different combinations of HPS components. Suggestions are also presented to choose the low cost system which produces energy at low LCE.
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