The Potential of Distributed Generation using Dual-Fuel Technology in Myanmar
(Room Nile 1)
20 Sep 17
2:00 PM
-
3:30 PM
Tracks:
Track E - Integration, Storage and Distributed Generation
Following the lifting of the sanctions, Myanmar has become one of the hottest countries in South East Asia for business, economic and trade activities. In order to fulfill its growth, Myanmar needs to substantially increase its current installed generation capacity of 5,215MW. As per the Myanmar Energy Master Plan of Asian Development Bank (ADB), the demand forecast is expected to grow to close to 14,500MW in 2030. Due to the current domestic gas shortage till 2020, alternative liquid fuel sources should be considered in the short and middle term future for power generation in order not to slow down the economic and industrial development of Myanmar. This is line with Japan International Cooperation Agency (JICA) recommendation in its National Electricity Master Plan reports where JICA mentioned that liquid fuel firing could be considered for power generation. Firstly, this paper will study the current Myanmar’s power system, explains the merits of Distributed Generation and how DG could help Myanmar to address its urgent needs for power. It would recommend a few locations where decentralized power plant could be built. Secondly, this paper will study the various possible liquid fuels available for DG in Myanmar. This paper will explain why HFO is the most economic viable fuel to address the short and middle term fuel crisis until pipeline gas or LNG is available and that the initial operation on HFO will also respect Emissions Guidelines of Myanmar. This paper will present 2 case studies of power plants using dual-fuel medium speed internal combustion engines capable of running on HFO initially and switching to natural gas for a 30MW captive power plant for an industrial zone and a 100MW power plant to be connected to the national grid. The 2 case studies will be presented using the cost of generated electricity. Finally, the paper will present a sensitivity analysis which can be used to compare the various unknowns in the DG Value Chain.