Agricultural residues can be utilized by developing countries as a feedstock for producing various bioenergy products to be able to meet local demand. Such initiatives may help reduce the dependence of a country on fossil fuel imports and, at the same time, maximize a vast amount of untapped biomass resources. The production of biofuels and biochemicals can be made possible by developing and implementing integrated biorefineries (IBR). An IBR consists of integrated process units that convert biomass into multiple bioenergy products. The design and synthesis of IBRs is a challenging task due to the number of possible pathways in producing a particular product while considering the type of feedstock and equipment. The P-graph (process graph) method is an excellent tool in process network synthesis (PNS) problems, and is an approach based on graph theory and efficient combinatorial algorithms. Its effectiveness in determining an optimal structure for solution recommendations is evident in a number of systems. In this work, a P-graph based approach was used to optimally synthesize an IBR using locally available agricultural waste as input. Optimal and sub-optimal solutions were generated by maximizing hourly profit. A sensitivity analysis on the effect of the price of key products on the optimal solution was conducted. The model was able to solve the problem given a feedstock supply and product demand constraint. Two case studies, a rice- and a corn-based IBR, were used to demonstrate the applicability of the proposed method. From the results, the rice- and corn-based IBRs generated a profit of 376.88 USD/h and 7746.93 USD/h. The difference in profit is mainly driven by the supply of biomass and prices of key products. This work will provide a reference in creating IBR using local feedstock, thereby valorizing agricultural residues. This may enable increased revenues for farmers from the sale of biomass.