Browsing by Subject "Smart grid"

Now showing 1 - 2 of 2

Open Access
Energy management in microgrids with plug-in electric vehicles, distributed energy resources and smart home appliances
(Springer, Singapore, 2015) Arslan, Okan; Karaşan, Oya Ekin; Rajakaruna, S.; Shahnia, F.; Ghosh, A.
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.
Open Access
Multi-stage stochastic programming for demand response optimization
(Elsevier, 2020-02-19) Şahin, Munise Kübra; Çavuş, Özlem; Yaman, Hande
The increase in the energy consumption puts pressure on natural resources and environment and results in a rise in the price of energy. This motivates residents to schedule their energy consumption through demand response mechanism. We propose a multi-stage stochastic programming model to schedule different kinds of electrical appliances under uncertain weather conditions and availability of renewable energy. We incorporate appliances with chargeable and dischargeable batteries to better utilize the renewable energy sources. Our aim is to minimize the electricity cost and the residents’ dissatisfaction. We use a scenario groupwise decomposition (group subproblem) approach to compute lower and upper bounds for instances with a large number of scenarios. The results of our computational experiments show that the approach is very effective in finding high quality solutions in small computation times. We provide insights about how optimization and renewable energy combined with batteries for storage result in peak demand reduction, savings in electricity cost and more pleasant schedules for residents with different levels of price sensitivity.