Dynamic deployment of energy symbiosis networks integrated with organic Rankine cycle systems

The amount of greenhouse gas (GHG) emissions from the energy sector is significant. Energy symbiosis (ES) is an innovative solution that helps reduce those emissions and lessens their role in worsening climate change. ES can enable the uptake of renewable energy sources at the industrial level, reduce reliance on fossil fuel, and help conserve materials. Organic Rankine Cycle (ORC) systems are ideal ES solutions for recovering wasted heat as they are compatible with different heat sources and offer high flexibility and compatibility. This study uses parametric optimization and performance analysis to examine the dynamic development of symbiotic networks with ORC facilities. The multi-objective mixed integer linear programming (MILP) model developed here maximizes energy recovery amounts in the network and minimizes the costs of establishing the required infrastructure. The MILP model can determine, for each period, the number of financial resources, the active connections between nodes (facilities), the amount of energy flowing through symbiosis, the opening/closing times of ORC facilities, and the ORC locations and capacities. The model has been tested in a case study using two scenarios: dynamic development of ES excluding and involving the ORC. The results show that integrating the ORC increases energy recovery by 18% while reducing the total network cost by about 7%.