Microgrid optimization, modelling and control

Overall, we propose to tackle these issues: Microgrid Efficiency Improvement: Besides increasing renewable energy content within the microgrid, system overall efficiency can be further enhanced by optimally dispatch resources. This means optimally dispatching load to generation units within a microgrid for fuel usage minimization. Further, if a historic load profile as well as generators' fuel consumption curves is known, we are able to find the best generators combination for fuel usage minimization. In this optimization problem, real-world constraints are put into consideration as well.;Natural Gas Engine Modelling and Control: Natural gas engines have become more and more popular because of the lower cost of natural gas and their lower environment impact. However, the applications of natural gas engine based generation units are limited, since the longer transport delay between fuel injection and torque makes the transient response unsuitable for grid frequency control.;As load is dispatched to generators that have different fuel usage curves, generators are running at dissimilar operation points. They can even be turned on and off depending on the load profile and other circumstances. To handle fast load variations, maximize renewable energy content, allow for rapid adjustment for generators operating points, and keep Microgrid frequency deviation within the allowed range in islanded mode, advanced control approaches are needed. Here robust control and L1 adaptive control are implemented and compared with classical control techniques. For controller design and validation purposes, control orientated mathematical models for internal combustion engine, storage system and renewable generation system are developed and validated.;The voltage control of a synchronized generator is realized through the closed-loop current control of the exciter. Within a microgird, internal combustion engines are used as primary movers to rotate alternator. Hence, the internal combustion engine control is mainly focused on grid frequency control by controlling the engine crank shaft speed.;Storage System Modelling and Control for Transient Performances Improvement: In the proposed setup, microgrid transient performances are further improved by adding a storage system (e.g., battery). Since the high cost of storage system, its capacity is limited. It only reacts on high frequency load fluctuation (caused by renewable energy) or load transients with constrained power delivery capability. Its state of charge and output power are monitored and controlled accordingly. The load variations with slower dynamics and bigger amplitude are taken care of by internal combustion engines in the configuration.;Through this research, the methodology of dealing with systems consisting of subsystems that have inherently distinct properties for improving overall system performances are developed. A slower system with bigger capacity is mostly cheaper in terms of per unit deliverables. A faster system with small capacity is more expensive to deliver the same amount of output. In a microgrid, the capital cost of per kW output power of internal combustion engine is much cheaper than per kW output capital cost of a battery. To improve the entire system performance without significant costs increment, we would like to separate the wheat and chaff of both systems and bring the advantages of both systems together. In microgrids, the battery system and internal combustion engine system work collectively. We maximize the usage of battery and avoiding any saturation or drain. At the same time we encourage the internal combustion engines to take the big trend of load fluctuations. The developed methodology can be applied to solve problems in various disciplinaries. (Abstract shortened by UMI.).