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Energy Management in Microgrids with Plug-in Electric Vehicles, Distributed Energy Resources and Smart Home Appliances
handle: 11693/23536 , 11693/50867
Smart Grid is transforming the way energy is being generated and distributed today, leading to the development of environment-friendly, economic and efficient technologies such as plug-in electric vehicles (PEVs), distributed energy resources and smart appliances at homes. Among these technologies, PEVs pose both a risk by increasing the peak load as well as an opportunity for the existing energy management systems by discharging electricity with the help of Vehicle-to-grid (V2G) technology. These complications, together with the PEV battery degradation, compound the challenge in the management of existing energy systems. In this context, microgrids are proposed as an aggregation unit to smartly manage the energy exchange of these different state-of-the-art technologies. In this chapter, we consider a microgrid with a high level of PEV penetration into the transportation system, widespread utilization of smart appliances at homes, distributed energy generation and community-level electricity storage units. We propose a mixed integer linear programming energy management optimization model to schedule the charging and discharging times of PEVs, electricity storage units, and running times of smart appliances. Our findings show that simultaneous charging and discharging of PEV batteries and electricity storage units do not occur in model solutions due to system energy losses.
- Bilkent University Turkey
690, Optimization, Smart appliances, Energy management, Smart grid, DER, Microgrids
690, Optimization, Smart appliances, Energy management, Smart grid, DER, Microgrids
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).3 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
