Model-Based Approach for Optimizing Operational Flexibility of Integrated Multi-Energy Industrial Clusters

Abstract

Achieving carbon-neutral energy systems in industrial clusters necessitates fundamental restructuring of existing energy systems. This transition is accompanied by several significant challenges. In pursuit of carbon neutrality, there is an increasing demand for industrial electrification, as well as a rising demand for green electricity and sustainable energy carriers, such as hydrogen and ammonia. The integration of variable renewable energy sources (VRES) is critical to address the growing demand for clean energy and enable the critical shift away from fossil fuel dependence. However, the intermittent nature of VRES, in combination with grid congestion issues, poses a challenge to the reliability of energy supply, a crucial element in fostering an attractive investment climate. Moreover, the development of new energy infrastructure is constrained by several factors, including limited access to new grid connections, investment uncertainty, and spatial limitations. Conventional energy planning and operation approaches, which treat energy sectors in isolation, are unable to address these complex, system-wide challenges. These approaches limit the ability to optimize across various energy sectors and fail to harness the potential synergies between energy carriers. Conversely, a more flexible and integrated approach provided by multi-energy systems (MESs) has been shown to effectively mitigate VRES intermittency, alleviate grid congestion through alternative energy pathways, and enhance cross-sector synergies and infrastructure utilization. However, the realization of these benefits necessitates a deeper understanding of the operation and organization of such systems.

To provide these insights, this research develops a model-based optimization approach for the cost-effective operation of MESs. The modeled system represents a synthetic, future-oriented energy system for an industrial cluster, drawing inspiration from the Maasvlakte area in the Port of Rotterdam. The research introduces a new operation strategy to support the transition towards a carbon neutrality, addressing key barriers currently limiting the decarbonization of industrial clusters.

A detailed conceptual model for the synthetic MES was developed to reflect the existing infrastructure of the Maasvlakte area, planned projects, and potential future developments. This conceptual model was translated into an operational optimization model implemented in Python using the PyPSA toolbox. The MES integrates five energy carriers—electricity, natural gas, hydrogen, ammonia, and heat—within a unified model through the energy hub approach that facilitates sector coupling, conversion, and storage within multi-energy carrier networks. The electricity system is modeled with physic-based power flow constraints to capture technical feasibility in the power system, and the non-electrical carrier networks are modeled using the energy hub approach. The entire system is optimized through a single-objective cost minimization, with mixed-integer linear programming, using hourly resolution over a one-year horizon. To test the system's performance under varying renewable energy supply, three weather-dependent scenarios were formulated and optimized, reflecting variability in wind and solar conditions and its implications for system operation.

Based on the system’s optimal performance across all scenarios, this research proposes a new operation strategy that enables flexible and cost-effective operation of a multi-energy industrial cluster, representing a paradigm shift from conventional approaches. Instead of relying on static, price-driven, and siloed sectoral operation, the proposed strategy emphasizes cross-sector economic optimization, dynamic dispatch response to system states, enhanced system flexibility through integrated conversion and storage technologies, and continuous energy supply to industrial consumers.

Key outcomes include the development of an operation strategy that minimizes costs while ensuring energy supply to industrial consumers and technical feasibility, the identification of ammonia as key flexibility provider, and actionable insights into flexibility management, the role of conversion technologies, and infrastructure planning. The results have important implications for decarbonization pathway of industrial clusters, offering a cost-effective and actionable approach to integrated energy system operation.