Microgrids (MGs) are the essential part of the modern power grids defined as the building blocks of smart grids. Renewable Energy Sources (RESs) and Battery Energy Storage Systems (BESSs) combined with Distributed Generators (DGs) form a comprehensive MG, which require the control and Energy Management System (EMS) to fulfill the load and grid requirements. As the need for BESS grows due to uncertainties of RESs, scheduling and cost management of BESSs in the MG becomes more of a concern. In this paper, BESSs have been designed for a university research center to simultaneously overcome the outage problem and shave the peak demand considering the BESS sizing and degradation; MG cost minimization, as well as MG scheduling. PV and wind are the RESs employed in this study and in combination; Li-Ion BESS has been utilized to investigate the MG performance. A two-layer optimization algorithm has been presented to optimally define the BESS size and minimize the operational cost of the MG achieving the peak shaving and valley filling objectives. The results prove the functionality and applicability of the proposed system to be implemented as a part of the experimental MG at Griffith University in order to enhance the stability and reliability of the research center and at the same time minimize the operational costs of the MG.
Measurement and monitoring of fluid flow are considered as crucial issues in industry and domestic applications especially for the water measurement. Numerous approach based on different physical principles have been proposed such as ultrasonic, electromagnetic, and differential pressure systems which each one of them requires its own particular measurement technique and algorithm to compute the necessary information such as flow speed, consumption and flow direction. However, there are some weaknesses in their measurement techniques including complexity and power consumption in their implementation. Therefore, in this paper, a measurement technique based on four sensor rotary encoder is presented. The measurement technique is simple and able to measure the speed, number of rotation and recognize the direction of the rotation. Furthermore, in the proposed measurement technique the error of the system is detectable in which debugging the system is required expensive equipment and long time for the conventional rotary encoder system. The functionality and performance of the measurement technique have been evaluated and found that the proposed technique is able to accurately measure the flow speed, the number of rotation, identify the direction of rotation and recognize the error occurred. (Abstract)
Keywords-bidirectional rotary encoder; rotary encoder measurment algorithm; fluid measument (key words)
This paper presents a battery capacity optimisation method with the aim of investment and operational cost reduction for grid-connected microgrids consisting of dispatchable generators, renewable energy resources and battery energy storage. The operating cost of grid-connected commercial Microgrids is mainly associated with the purchased energy from the grid and monthly peak demand. Hence, mitigating the peak value by the means of battery energy storage and dispatchable generators during the peak period can effectively reduce the operating cost. However, due to the high cost and short life span of the battery energy storage systems, the optimum design of energy storages is of the utmost importance to the Microgrids. This paper proposes an efficient iterative method with an inner unit commitment optimisation layer to achieve the optimised battery capacity. In order to implement the inner unit commitment optimisation, the Mixed Integer Quadratic Programming (MIQP) optimisation algorithm is applied and CPLEX solver is chosen to solve the optimisation problem. This approach is applicable and beneficial when dealing with high demands as it economically distributes the load requirement between the battery and dispatchable generators. Finally, the proposed method is applied to determine the battery capacity of the experimental Microgrid at Griffith University. The simulation results for the understudy case verified the efficiency and effectiveness of the proposed approach.
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