Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach

This study aims to develop a comprehensive decision model for sustainable design of biomass based renewable energy supply chains and district heating systems (DHS) with thermal energy storages. The model integrates the strategic decisions such as location and capacity selection for energy plants, DHS, thermal storages and biomass storages with tactical decisions related to biomass production, supply and transportation planning, inventory management and energy production. The main purpose is to find the optimum configuration of the supply chain and DHS to meet the heat demand of a particular locality. The model combines cost and service level objectives and accounts for biomass supply, material flow, capacity, demand and technical constraints. The problem is formulated as a fuzzy Mixed Integer Linear Programming (MILP) model that comprises multiple biomass types and system uncertainties. To explore the viability of the proposed model, computational experiments are performed on a real-world case. Sensitivity analyses are conducted to examine the impacts of cost and capacity limit of thermal energy storage, as well as heat demand, on the objective functions and thermal storage capacity. The results reveal that the proposed model can effectively be used in practice to assist the decision makers in planning energy production systems in a sustainable and effective manner.