Asia Power Week 2017

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Hybrid Microgrid Solutions for Asia – Economic Optimization Based Selection of Microgrid Topology and Control Architecture (Room Nile 1)

Growing electrification needs and concerns about carbon emission tends to stimulate the demand for distributed energy generation development across the regions in Asia. Developing economic yet innovative energy solutions suited for the Asian climatic conditions become very essential with the increased role of non-dispatchable and distributed renewable energy sources. Such solutions are collectively called hybrid microgrid comprising of controllable load and distributed energy generation with renewable energy penetration and energy storage integration. The architecture and component selection for a hybrid microgrid is highly dependent on geographic location, available natural resources for renewable penetration, criticality of load, and most importantly the economic aspects of the fuel and other energy resources. This paper aims at to identify and categorize the considerations of choosing hybrid microgrid topology and control architecture based on the geographic locations and types of customer requirements. Reciprocating Engines based Gensets (REG) are usually considered as distributed generation capacity in a hybrid microgrid because of the maturity and reliability of the available technology. This paper would compare different architectures of REG based hybrid microgrid and appropriate energy management strategy based on different geographic locations in Asia. Along with respective dispatch/ control strategies, the architectural selection of a reliable and resilient hybrid microgrid depends on economic consideration of using reciprocating engines based Gensets, renewable energy resource, energy storage to meet customer electrical and thermal load profile. The locations and load data for the study would come from Rolls-Royce MTU-Onsite’s understanding of the customer requirements. A comprehensive analysis will be reported in the final paper based on the economic model and optimization results obtained using microgrid design and planning tools.