A proposed model for determing bidding zones in the electricity market using location marginal prices and clustering algorithms

Currently, electricity demand in Vietnam is rising rapidly due to industrialization, modernization, and population growth, creating risks of shortages, especially in the dry season when hydropower declines. To ensure supply, coal and oil generation is often dispatched, increasing costs and pollution. Renewable energy is expanding but faces issues of price volatility and supply reliability. A zonal electricity market design is therefore seen as a promising solution to optimize pricing, attract investment, and promote clean energy development, contributing to carbon reduction. This paper proposes a two-step zonal market model: first, node indices are computed under different scenarios using DC Optimal Power Flow (DC-OPF); second, nodes are grouped into bidding zones via Spectral Clustering. The model is tested on a 118-bus system with solar and rainy-day datasets to identify efficient and practical zonal configurations.