Journal Article

Reliability-constrained transmission expansion planning based on simultaneous forecasting method of loads and renewable generations

Oboudi, Mohammad Hossein, Hamidpour, Hamidreza, Zadehbagheri, Mahmoud, Safaee, Sheila, Pirouzi, Sasan

2025

Overview

Due to increased energy consumption in upcoming years, the power system needs to be expanded to meet suitable technical conditions. The primary requirement is to gain accurate information about consumption growth in the planning horizon, which can be obtained via forecast studies. Since renewable sources can grow beside the demand, the accurate prediction should consider simultaneous changes in supply and demand in the future. In this paper, a reliability-constrained transmission expansion planning (RCTEP) is proposed. It simultaneously is based on the load forecasting and renewable sources production, named the net power demand forecasting technique (NPDFT). NPDFT consists of a time series-based logistic method, which forecasts loads at planning years. RES generation forecasting forecasts the following year’s generation by an estimated coefficient. RCTEP minimizes the summation of the planning, operation, and reliability cost so that it is limited to the AC optimal power flow equations, planning constraints, and reliability limitations for N – 1 contingency. Then, the stochastic programming based on the Monte Carlo Simulation and the simultaneous backward approach models the uncertainties of the load, RES power, and availability of network equipment. This problem is solved by the hybrid algorithm of grey wolf optimization and training and learning optimization algorithm to achieve the securable optimal solution with a low standard deviation. Generally, this paper contributes to predicting the net power demand, simultaneous modeling of operation, reliability, and economic indices, besides using hybrid algorithms to solve the defined problem. Finally, this strategy is implemented on the 3-bus, 30-bus, and 118-bus transmission networks in MATLAB software. The numerical results confirm the capabilities of the proposed method in improving network operation and reliability indices. Higher reliability can be found for the network by defining a desirable penalty price. Also, operation indices, such as voltage profile and power loss, increase more than 10% under these conditions.

• Publisher: Springer Berlin Heidelberg,Springer Nature B.V
• Subject: Algorithms / Alternative energy sources / Constraints / Contingency / Economics and Management / Electric power systems / Electrical Engineering / Electrical loads / Electrical Machines and Networks / Electricity / Energy consumption / Energy Policy / Engineering / Flow equations / Forecasting / Forecasting techniques / Genetic algorithms / Machine learning / Monte Carlo simulation / Network reliability / Optimization / Original Paper / Planning / Power Electronics / Power flow / Stochastic programming / Supply & demand / Taxonomy / Wind power