Work

Multistage power generation planning approach for new power systems with high renewable energy integration considering flexibility constraints

Year: 2025

Type: article

Abstract: • Static modeling alone cannot meet new power system planning demands. • High-penetration renewables degrade traditional planning efficacy. • Multistage scenario-tree modeling maintains economic reliability. • Flexibility-constrained planning enhances low-carbon adaptability. • Scenario-tree with flexibility constraints achieves optimal planning. Under the “dual-carbon” goals, the integration of high-proportion renewable energy has amplified operational uncertainties in new power systems, posing novel challenges to the economic planning of generation system expansion. However, existing power planning methodologies suffer from static modeling defects, incomplete constraint systems, and oversimplified cost structures, rendering them inadequate to support the low-carbon transition of emerging power systems. This necessitates a comprehensive consideration of system variability and flexibility to establish a multi-stage generation planning model. Addressing these limitations, this paper develops a fundamental multi-stage planning framework based on scenario tree structures, further incorporating carbon emissions and penalty costs for curtailed renewable energy. A flexibility-constrained multi-stage generation planning model is formulated, which resolves nonlinearity through auxiliary variable linearization and Benders decomposition algorithm. Case studies demonstrate that the proposed model achieves a 47.3% reduction in total 10-year planning costs for a typical regional system, comprising 39.5% operational cost savings and 46.3% carbon emission cost reduction, while elevating renewable energy accommodation rate to 80%. The model fulfills economic-environmental requirements and ensures system reliability.

Source: International Journal of Electrical Power & Energy Systems

DOI: 10.1016/j.ijepes.2025.110818

Authors: Danyang Li, Hongpeng Liu, Jingwei Zhang, Xu Han, Shuxin Zhang

Institutions: Northeast Electric Power University, State Grid Jilin Electric Power (China)

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Climate action, Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,920