Integrating heat pumps into large-scale electricity-to-heat industrial processes has proven highly successful in enhancing the utilisation of renewable energy and contributing to carbon emission reductions. However, most studies focus on overall system performance, overlooking the detailed thermal behaviour of the heat pump itself. This limits the adaptability of heat pumps in dynamic industrial settings. This work proposes an equation-oriented framework that enables flexible integration of thermodynamically detailed heat pump models into industrial heat recovery systems. A superstructure-based optimisation model is developed to minimise energy costs and enhance efficiency, considering process constraints, network layout, and heat pump performance. The model dynamically optimises heat pump operation and placement to enhance waste heat recovery and overall system integration. Moreover, the approach supports the integration of low-grade utilities to further improve the energy efficiency. The proposed framework is validated through an industrial-scale case study of a crude oil distillation process. Life cycle assessment is conducted to quantify potential environmental and economic benefits. Results show that integrating heat pumps into the system recovered 50.52 % of low-pressure steam, reducing the total operating cost and annual cost by 12.88 % and 12.42 %. Additionally, total net carbon emissions decreased by 28.70 %. Lower electricity prices increase heat pump use and economic benefits but also amplify rebound effects. Furthermore, although high-temperature heat pumps operating above 150 °C tend to increase capital expenditures, they unlock greater energy efficiency, thereby accelerating the industrial decarbonisation process.

Transitioning heat exchanger network (HEN) synthesis designs to industrial application involves operational, environmental, and cost considerations, posing computational challenges. This study proposes a systematic optimization approach integrating multi-objective, multi-period optimization HEN synthesis with waste heat recovery and multiple utilities. The proposed methodology incorporates a novel two-step unit reduction strategy to overcome the increase of model combinational complexities arisen from the multi-period features, thereby facilitating the solving of large-scale problems. Meanwhile, environmental impacts are concerned by using the technique for order preference by similarity to ideal solution approach. A new optimization route, Enhanced Pinch-assisted Multi-Objective Optimization is proposed to obtain the final decision in this multi-objective problem time-efficiently. The case study includes a 15 streams problem, and a real industrial-scale crude oil distillation preheat system. The results showed that assigning carbon compensation to the waste heat recovery option can significantly reduce carbon emissions and change energy distribution.

The Solar Combined Cooling, Heating, and Power (S-CCHP) system, distinct from traditional centralised generation, provides clean energy solutions by installing user-side renewable energy capture facilities like solar panels to address the energy crisis and mitigate global warming. Previous research on the design of S-CCHP for buildings has often emphasised self-sufficiency, with less focus on the role of these systems as energy suppliers on the market. However, it is feasible to install scaled-up solar facilities that generate enough power to export to the grid, reducing grid pressure and enhancing the renewable energy mix. This study analyses the optimal design deployment for electricity within the S-CCHP system, based on the Renewable Energy System for Residential Building Heating and Electricity Production (RESHeat) system installed in Limanowa. It aims to optimise owner energy deployment by strategically integrating electricity generation, hybrid storage, and the electricity market to maximise owner benefits. A Life Cycle Assessment is also conducted to explore greenhouse gas emissions across scenarios with different storage facilities and reuse rates. Results show that the optimal deployment of 264 PV panels, each with a rated power of 440 W, generates 105 MWh annually, resulting in the surplus of 90.18 MWh with a selling price of 115 EUR/MWh. Vanadium redox flow batteries offer the highest revenue (4922.01 EUR) with the lowest storage costs, while lithium-ion batteries have the lowest carbon emissions (1.22 t CO2 eq/y). Sensitivity analysis and revenue break-even analysis are further conducted to assess the robustness and financial viability.