Multi-objective Flexible Planning of Transmission Network Considering Generation and Load Uncertainties

The rapid growth of wind and solar generation has significantly enhanced the uncertainty of power system. At present, most studies on transmission network planning considering renewable energy generation adopt DC power flow equation. But DC power flow ignores line resistance, voltage amplitude, reactive power flow and network loss, whose linear expression is not accurate enough for large power systems. Based on AC flow calculation, this paper constructs a two-layer model of multi-objective flexible planning for transmission network considering the uncertainties of renewable energy generation and load. The upper layer model is a transmission network multi-objective planning model considering the annual value cost of construction investment, annual network loss cost and operation efficiency. The non-dominant sorting genetic algorithm with elite strategy is adopted to solve the problem, and the transmission network planning results are transmitted to the lower layer. The lower layer model is a multi-scenario calibration model with the goal of minimizing the expectations of renewable energy curtailment and load shedding. The AC power flow equation is relaxed by the second-order cone so as to verify the capacity of the plan to the generation and load uncertainties. Finally, the effectiveness and feasibility of the proposed model are verified by the adjusted IEEE 39-node system.