Optimized response to electricity time-of-use tariff of a compressed natural gas fuelling station. (15th July 2018)

• Record Type: Journal Article
• Authors: Kagiri, Charles; Wanjiru, Evan M.; Zhang, Lijun; Xia, Xiaohua
• Is Part Of: Applied energy. Volume 222(2018)
• Page Start: 244
• Page End: 256
• Publication Date: 2018-07-15
• Subjects: Compressed natural gas -- Fast-fill -- Demand response -- Optimization; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2018.04.017
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A model for optimization of compressor scheduling based on demand is presented. 59.3% cost reduction for a studied gas station fuelling 143 vehicles over a high demand season. 25% cost reduction a studied gas station fuelling 146 vehicles over a low demand season. Compressor switching frequency is minimized by different strategies. Abstract: Compressed natural gas propulsion of vehicles has been shown to have advantages over petrol and diesel propulsion due to lower carbon dioxide emissions as well as the increased durability of vehicle engines. The growth of compressed natural gas as an alternative fuel to petrol and diesel can be accelerated by implementing strategies that result in the economical operation of the distribution infrastructure. Economic scheduling of power consumption is a useful strategy for reducing the cost of energy for both industrial and domestic consumers who operate in time-of-use based electricity pricing environments. In this paper, an optimal energy management strategy is proposed for the operation of a compressed natural gas fuelling station. The compressor energy consumption, being the main component of the total operating cost of the fuelling station, presents a cost saving opportunity through which optimal scheduling of operation can be used to lower cost of operation of the station. The developed model shows potential average savings of 59.3% in daily electricity costs while maximizing compressor life through minimization of compressor cycling.