What is it about?
This work addresses a catch-22 in power systems: absorbing more renewable energy (RE) can disrupt their stable and cost-effective operation, yet not using all available RE results in wastage. So, our study puts forth a model (termed many-objective probabilistic optimal power flow or MOPOPF) designed to ensure that power systems can absorb as much RE as possible with minimal disruption and without wasting it. We aim to minimize any curtailments (or intentional reductions) of RE while maintaining the secure and economical functionality of power systems. We've developed a unique optimizer, enhanced with ensemble learning, which helps in finding the best solutions to this multi-objective problem. The case studies conducted validate the effectiveness of our proposed model and optimizing tool when applied to both theoretical and real power systems.
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Why is it important?
With the global march towards net-zero carbon emissions, the integration and efficient utilization of renewable energy in power systems are vital. Yet, the challenge is ensuring that the generous absorption of RE doesn’t destabilize the power systems or inflate costs. Our research explores the tension between maximizing RE usage, maintaining system stability, and ensuring economic viability. The MOPOPF model and the newly developed optimizer (ELGSOMP) are critical as they illuminate a pathway that allows for the amplification of RE in power systems while keeping them stable and cost-effective. This is not merely a technical stride but also a crucial step towards sustainable energy management, aligning with global green energy goals, and enabling power systems to significantly contribute to reducing the carbon footprint without neglecting their operational integrity and economic feasibility.
Perspectives
Navigating through the dilemma of enhancing RE absorption without jeopardizing the stable and economical operation of power systems was a journey filled with intricate challenges and enlightening discoveries. The development of the MOPOPF model was a journey into blending the objectives of RE maximization and operational safety in power systems, forging a pathway where sustainability and operational excellence coexist. This pursuit extended beyond the technical realm, embedding itself into a broader canvas where sustainable practices, operational excellence, and economic prudence harmonize, sculpting a future where our power systems are not just robust and economically viable, but also significantly greener and sustainable. This journey threads through the delicate balance of maximizing the boon of RE without spiraling into operational chaos, paving a way where every ray of sunlight and every gust of wind is judiciously harnessed to light up our future sustainably.
Professor/PhD Supervisor/SMIEEE Yang Li
Northeast Electric Power University
Read the Original
This page is a summary of: Renewable Energy Absorption Oriented Many-Objective Probabilistic Optimal Power Flow, IEEE Transactions on Network Science and Engineering, January 2023, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/tnse.2023.3290147.
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