Measuring the Long-Term Uncertainty Effect Reduction on Transmission Expansion Planning

Transmission expansion planning (TEP) is known as long-term study, which is related to the generation expansion pattern, i.e. where and how many new generation facilities will be constructed. Recently, some researchers have paid special attention to network reliability and maintainability in TEP design. As such, the uncertainty of generation expansion planning (GEP) can alter the results of TEP. Therefore, the robustness of TEP to the uncertainty of GEP should be investigated in TEP process. This paper aims to define the robustness of TEP to the long-term uncertainties mathematically. To do so, a simple TEP problem is first proposed and then the uncertainty of GEP is applied to the problem by developing a novel uncertainty-oriented TEP objective function as multi-objective optimization. Two objectives of this model are the conventional TEP costs and minimum changes. Then, the model is implemented on the IEEE 24-bus reliability test system (IEEE RTS) for two main items in order to assess the applicability of the proposed method. Furthermore, the effect of the method on undoing the uncertainty of generation mixture is investigated at the plan horizon in TEP. As TEP planning is NP-hard, genetic algorithm (GA) is utilized along with fminc optimization function in MATLAB, where the lower levels are resolved using the quadprog function in MATLAB. Afterwards, Pareto front of the solutions is analyzed to choose the most possible and economical solution between them. It can be concluded that the uncertain generation expansion would result in drastic economic losses both in the operation stage and in investment cost waste. Eventually, the obtained results confirm the applicability of the proposed model and solution method.