A new multi-objective multi-energy optimization model in the urban-industrial symbiosis network using LARG supply chain approach

Abstract

Urban-industrial symbiosis represents a novel approach within the circular economy, promoting synergy in resource development and management between adjacent urban and industrial areas. A particular form, energy-based symbiosis, emphasizes the integrated supply of energy across these areas. This paper presents a new model for multi-energy optimization within an urban-industrial symbiosis energy network. The model enables the integrated supply of electrical, heating, cooling, and hydrogen to both industrial and residential sectors. To achieve this, we formulated an optimization problem focused on determining optimal equipment capacities and energy flow. A key innovation is the integration of LARG supply chain paradigms into the energy network modeling: lean (i.e., cost minimization), agile (i.e., shifted demand minimization), resilient (i.e., addressing uncertainties in energy demand and renewable energy generation), and green (i.e., CO₂ emissions minimization). The problem was modeled using multi-objective approach, and numerical simulations were conducted on an urban-industrial symbiosis area, accounting for seasonal and daily demand variations. The results illustrate the optimal distribution of energy flow throughout the day and across seasons. The objective function values highlight the inherent trade-offs between the LARG paradigms. The chosen solution for the multi-objective problem effectively balances these objectives, achieving a 55 % reduction in shifted demand and a 22 % reduction in CO₂ emissions, with only a 5 % increase in costs. The findings also emphasize the importance of fostering synergies between optimization strategies for industrial symbiosis networks and energy policy-making, to simultaneously enhance energy security and environmental sustainability.