article · Energies
An improved optimisation framework combines a primal-dual interior point method with a generation scaling factor to manage transmission congestion and calculate electricity prices in wind-integrated power systems. By adjusting generator outputs based on transmission line flow sensitivities, the approach mitigates congestion early, maintains power flow feasibility, and computes locational marginal prices accurately. The technique was tested on the standard IEEE 30-bus test system and a real 114-bus Algerian transmission grid. In both cases, the framework reduced generation costs and transmission losses while increasing social profit across single-sided and double-sided market designs. Testing varying levels of wind penetration revealed that strategic wind farm placement enhances congestion mitigation and lowers locational marginal prices at critical nodes. Overall, the methodology supports competitive electricity market operations and facilitates larger-scale renewable energy integration.
Integrating variable wind power into electrical grids can overload transmission lines and complicate wholesale power pricing. By mitigating grid congestion and accurately calculating local power prices, this framework helps electricity market operators integrate more renewable generation without compromising system stability. It provides a computational mechanism to lower consumer and producer costs while transitioning toward cleaner energy supplies.
This framework could be adopted by transmission system operators, power exchange administrators, and utility planners managing deregulated electricity markets with high renewable shares. It serves as an algorithmic decision-support tool for congestion management and market dispatch. Validated through numerical simulations on standard test systems and an actual 114-bus Algerian transmission network, the approach represents applied research tested in simulated network models, requiring integration into industrial market-clearing software before commercial deployment.
AI-generated from the published abstract. Always read the original work before citing.
This study presents a new improved primal–dual interior point method associated with a generation scaling factor (PDIPM–GSF) for congestion-aware optimal power flow (OPF) in power systems with renewable integration in a deregulated electricity market. The proposed framework combines the robustness of the primal–dual interior point method with an adaptive generation scaling strategy that adjusts generator outputs according to transmission line flow sensitivities, enabling early congestion mitigation, improved power flow feasibility, and accurate determination of locational marginal prices (LMPs). The proposed approach is evaluated on the IEEE 30-bus test system and a real 114-bus Algerian power network. The results demonstrate that the proposed framework can reduce generation costs and improve social profit under both single-sided and double-sided market operation through enhanced coordination between generation, demand, and congestion management. The impact of integrating wind energy is analyzed under different levels of wind energy penetration in the first IEEE 30-bus test system, showing that the integration of wind energy can not only improve social welfare and save generation costs but also lower transmission losses. Additionally, the results show that the placement of wind farms can improve the performance of the proposed PDIPM–GSF framework in terms of congestion management and reduction in LMPs at important nodes. For the 114-bus Algerian transmission network, renewable energy integration further demonstrates the capability of the proposed framework to reduce transmission losses and generation costs while improving overall market performance. These results demonstrate that the proposed PDIPM–GSF framework provides an effective smart optimization approach for renewable-integrated power systems by improving congestion management, facilitating large-scale WE integration, enhancing market efficiency, and ensuring reliable LMP computation. The proposed method, therefore, represents a practical and efficient solution for supporting future renewable energy transition and competitive electricity market operation in Algeria and other renewable-rich power systems.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.3390/en19184247
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
