A Multi-Stage Security Constrained Coordinated Expansion Planning of Transmission System and Energy Hubs

This paper presents a security constrained coordinated decision-making process for optimal long-term and short-term scheduling of the transmission system (TS) and energy hubs (EHs). Energy users (EUs) across the transmission system (TS) minimize their energy costs by investing in the EHs. A three-level approach using the diagonalization algorithm is employed to evaluate the benefits of cooperation between the transmission system operator (TSO) and energy users (EUs). The proposed framework is modeled using both static and multi-stage optimization approaches to minimize the total costs of the planning, operation, emission, and expected energy not served (EENS) simultaneously for the TSO and EUs at the first and second levels, respectively. The TSO expansion planning is optimized at the first level to meet the TS capacity requirements. At the second level, the EUs at different nodes invest in the EHs based on the calculated locational marginal prices (LMPs). Once the expansion planning of the EUs is optimized, the net electrical demands at the TS nodes are updated. Then, the electrical market is cleared by the independent system operator (ISO) at the third level to update the LMPs. Finally, the strategical expansion planning of the TSO is updated at the first level.The security of the TS and EHs is modeled considering the possibility of failure occurrence in the TS lines and energy sources in the EHs. The output power of the renewable energy resources (RESs), multi-carrier load demands, district market prices, operation cost of the thermal units, and equipment availability have uncertain nature. These uncertainties are applied to the proposed framework by a stochastic optimization framework. For evaluating the performance of the proposed model, it is implemented on the modified IEEE 30 bus and 118 bus test systems, considering a common model of the EH, consisting of photovoltaic panels (PVs), wind turbines (WTs), combined heat and power generation (CHP) units boilers, and absorption chillers. Numerical results indicate that the proposed method significantly reduces EENS and overall system costs under both static and multi-stage approaches, demonstrating its effectiveness.