| Summary: | Electric power sector around the world is facing challenges with rapidly increasing penetration of variable renewable energy as well as environmental and economic pressure to lower the carbon
footprint of electricity production. Energy storage systems receive a lot of attention as they present attractive solutions to improve grid reliability, provide grid flexibility, and lower the environmental impacts. To that end, energy storage systems are expected to be key instruments in complex power system operations. In this paper, we present a quantitative stochastic model to examine the interactions of customer demand, power grid, and an energy storage unit that is shared by a group of users such as multi-dwelling units and campuses. The stochastic model is based on a two-dimensional continuous-time Markov chain and steady-state probability distributions are solved by numerical methods. The goal is to present a general architecture which advances modeling efforts for smart power grid systems. It is noteworthy that the ESS is discharged during peak hours to reduce peak consumption, and it is charged during off-peak hours to store cheap energy. In order to ensure grid reliability, system serving capacity is limited to
available resources and a small percentage of customer demand is rejected which serves as the performance metric of the model. Energy storage sizing is performed under various rejection probabilities and system resources. The results reveal that obtaining the right size of energy storage system is highly related to customer’s electricity consumption patterns. Finally, an economic profit model which relates financial principals with stochastic system parameters and enables system operator to choose the best operating range for the system.
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