A new approach based on off-design R-curve and thermal load duration curve for the design and optimization of bioresources driven cogeneration Rankine cycle: Application on industrial site in Nova Scotia, Canada

Abstract

Decarbonization objectives in industrial processes impose major changes for industrial energy supply. The combination of decarbonization of heat and electric load can be achieved by cogeneration plant driven by clean energy resources. Despite of new innovative cogeneration cycle being investigated, Rankine cycle cogeneration plant driven by biomass or biofuels stills the most attractive solution in low solar irradiance countries. The aim of this study is to establish a new original method combining a steady state and dynamic approach to solve and link optimal conceptual design problem and operation strategies of the plant. This approach is applied also to evaluate the worthiness of adopting a thermal energy storage solution. Breakdown of electricity and thermal cost of cogeneration plant is established for the first time for the sake of mapping energy prices of different decarbonization solutions. A thermodynamic and economic model to predict the performances of the cogeneration plant at design and off-design conditions was developed.Three off-design operation strategies are identified: the first engenders steam throttling, the second induces part-load operation of the condensing turbine, and the third requires an auxiliary boiler to meet peak thermal demand. A new R-curve named off-design R-curve is developed to predict cycle performances during these operations, and then combined with the thermal load duration curve to predict energy consumption. Subsequently, an optimization procedure combining the R-curve tool and cost break-down of electricity and thermal energy is carried out. The energy prices and the annualized capital cost R-curves are summed up to optimize the design of power to heat ratio.A case study in an industrial site in Nova Scotia (Canada) is considered. The method proves its simplicity and effectiveness in the conceptual design of the plant, as well as predicting different costs of energy and the optimization of the R ratio. Case study results show that biomass energy cost saving rises with power production to achieve its maximum at Rd equal to 1.23, while biofuel energy cost saving decreases with Rd and was achieved only when Rd is lower than 0.7. Combining the annualized cost with the energy cost reveal that the optimal Rd is at 1.07 for biomass and 0.21 for biofuel, respectively. Moreover, with the introduction of the off-design R curve, it was found that the cogeneration efficiency drops down to 18 % (from 0.52 to 0.34 at Rd equal to 1.23) and the power production down to 60 % when the process load is double the average load. Hence, more accurate energy cost-saving values and optimal on-site power production are achieved. Energy cost saving drops by 7 %, which lowers the value of Rd where biofuel cost saving is achieved to 0.3, while the optimal value stays the same for biomass. Besides, the maximum potential of thermal energy storage in energy saving is accounted. The saving in the case study is low at 5–6 %, but generally it is dependent on the frequency at which the thermal load occurs. The method developed proves its effectiveness in solving conceptual design problems, and can used to rigorously evaluate new innovative configurations of cogeneration plants. Challenges and future works to improve this method are also addressed.