Optimal Heat Storage Sizing for District Heating Networks to Maximize Electricity Revenue from Combined Heat and Power Units

Abstract

Integrating heat storages in district heating networks (DHNs) supports managing dynamic characteristics such as heat-demand variations and changing energy prices, and the intermittency of renewable sources. A common application are DHNs with combined heat and power (CHP) units, where a storage allows shifting heat extraction to periods with favorable electricity prices. Although the benefits of heat storage in DHNs are well established, determining the optimal storage size remains challenging due to the diversity of DHNs in terms of heat sources, production and consumption patterns, network heat losses, and fuel costs. This paper presents a scalable, automated methodology for optimizing short-term heat storage in DHNs using mathematical optimization. The nonlinear, physics-based approach models the DHN, heat producers, and storages simultaneously to minimize total economic cost through optimal storage sizing, explicitly considering time-varying heat-production costs, heat demands, and heat losses. The methodology is demonstrated on a 3rd-generation CHP-DHN in Belgium with 30 consumers, exceeding the scale of previous physics-based storage-sizing studies. For this system, optimal storage integration reduces the 20-year cost by 730 k EUR (16.5%), from 4.41 M EUR to 3.68 M EUR. The reduction results from a 1.07 M EUR decrease in heat-production cost achieved by shifting heat extraction to periods of low electricity prices, while the storage investment amounts to 323 k EUR. A comparison to a commonly used simplified storage sizing method, which fails to identify the optimal storage size, demonstrates the advantage of the proposed holistic, physics-based optimization approach in ensuring feasible designs, accurate cost assessments, and optimal storage sizing.