Abstract:
Renewable energy sources (RES) integration in power system has increased globally in recent years and renewable portfolio standards (RPS) are broadly adopted to encourage further investments in RES. However, large-scale integration of these variable energy sources poses several challenges to network planners. There is growing interest in energy storage system (ESS) due to its ability to deal with intermittency issues of RES by storing excess energy when available and delivering back during peak hours. This paper introduces a coordinated generation, transmission and storage expansion planning model, formulated as dynamic mixed integer liner programming (MILP) optimization problem. The model is used to study the economic impact of co-optimizing investments in these three asset classes subject to RPS targets up to 75%. We also analyze ESS impact on CO2 emissions from thermal sources and overall network performance. The model is implemented on a modified IEEE 24-bus system and numerical results show that up to 22.4% savings could be achieved in total cost by utilizing the existing network more optimally compared to the case when no ESS investments are considered. Moreover, the renewable curtailments are significantly reduced at high RPS by integrating ESS and network utilization is also increased.
