Network Expansion Planning (NEP) plays a pivotal role in the development of power systems. It involves investing in new generating units and transmission lines to meet growing load demands and ensure a reliable electricity supply. Historically, the incorporation of demand response (DR) factors in power system planning has been limited due to their complexity and evaluation challenges. However, with advancements in smart grid technologies, increased integration of renewable energy, and the emergence of flexible loads, the inclusion of DR models has become crucial for enhancing power system reliability. While numerous studies have delved into generation and transmission expansion planning (GTEP) problems, only a few have explored the integration of network payment schemes and DR within the GTEP framework. This study proposes a multi-annual generation and transmission expansion planning model that incorporates three network payment schemes and two DR techniques. The objective is to secure financing for new generating units and transmission lines while minimizing the overall system cost. The proposed models employ the mixed-integer linear programming (MILP) optimization method and are validated using a modified IEEE 24-bus system. Two key system performance metrics, namely the network congestion index and network saturation index, are employed to assess system reliability and effectiveness. These results demonstrate that the integration of network payment schemes and DR techniques into the generation and transmission expansion planning model can lead to a cost reduction of 32.1% as compared to base model, reduced power system congestion and saturation (22.1%, 2.73%) to allow more renewable energy integration and enhanced power system reliability and operational flexibility.
Impact of demand response and network payment schemes on generation and transmission expansion planning with high renewable energy penetration / Ahmad, Shehzad; Numan, Muhammad; Salam, Izhar Us; Yousif, Muhammad. - In: SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS. - ISSN 2213-1388. - 87:(2026). [10.1016/j.seta.2026.104882]
Impact of demand response and network payment schemes on generation and transmission expansion planning with high renewable energy penetration
Ahmad, Shehzad;Salam, Izhar Us;
2026
Abstract
Network Expansion Planning (NEP) plays a pivotal role in the development of power systems. It involves investing in new generating units and transmission lines to meet growing load demands and ensure a reliable electricity supply. Historically, the incorporation of demand response (DR) factors in power system planning has been limited due to their complexity and evaluation challenges. However, with advancements in smart grid technologies, increased integration of renewable energy, and the emergence of flexible loads, the inclusion of DR models has become crucial for enhancing power system reliability. While numerous studies have delved into generation and transmission expansion planning (GTEP) problems, only a few have explored the integration of network payment schemes and DR within the GTEP framework. This study proposes a multi-annual generation and transmission expansion planning model that incorporates three network payment schemes and two DR techniques. The objective is to secure financing for new generating units and transmission lines while minimizing the overall system cost. The proposed models employ the mixed-integer linear programming (MILP) optimization method and are validated using a modified IEEE 24-bus system. Two key system performance metrics, namely the network congestion index and network saturation index, are employed to assess system reliability and effectiveness. These results demonstrate that the integration of network payment schemes and DR techniques into the generation and transmission expansion planning model can lead to a cost reduction of 32.1% as compared to base model, reduced power system congestion and saturation (22.1%, 2.73%) to allow more renewable energy integration and enhanced power system reliability and operational flexibility.| File | Dimensione | Formato | |
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https://hdl.handle.net/11583/3007785
