| The combined cooling,heating,and power(CCHP)system coupled with renewable energy has been widely used in energy supply of buildings due to its high energy-utilization efficiency,low pollutant emission,and the ability to achieve energy cascade utilization.This system is capable of alleviating the energy shortage caused by the depletion of traditional energy resource and meeting the growing energy demand of buildings.How to use intelligent decision-making technology to generate the optimal collaborative operation scheme and significantly improve the economic,energy efficiency,and environmental performance of this system has important research value.However,the existing CCHP system that incorporates renewable energy source lacks the rationality in its configuration and operation due to its numerous components and inherent stochastic fluctuation characteristics of renewable energy.Especially under the context of climate change,the drastic change in meteorological elements such as temperature and radiation lead to the difficulty in maintaining energy supply-demand balance.In addition,subjected to the complex operation mechanism and multiple influencing factors of the CCHP system coupled with renewable energy,there are many uncertainties in the optimization design of its configuration and operation pattern.This brings many difficulties to the design and implementation of system’s energy supply strategy,affecting user’s energy consumption experience.As in-depth understanding of the research problem and continuous development of theoretical method,in this thesis,the evolution of research objectives was considered as the clue,an innovative dynamic and interactive integrated model of the CCHP system under climate change and multiple uncertainties was established through the improvement of research method and the deepening of research conclusion.This model incorporates user-side load forecasting,supply-side output calculation,system-side uncertainty identification,and operation-side collaborative optimization into a unified framework.It firstly realizes the combination and practical application of regional climate simulation(PRECIS),user load prediction(TRNSYS and DeST),equipment output evaluation(mechanism modeling),uncertainty identification(interval,stochastic and fuzzy),and collaborative optimization of CCHP system(LINGO software),which provides the theoretical support and practical basis for enhancing the robustness and integrity of the energy supply pattern.The main research content of this thesis includes:(i)Because traditional operation optimization model of hybrid renewable energy and CCHP system neglects the influence on the user demand caused by fluctuations in meteorological factors such as temperature and humidity under climate change,leading to the inflexible operating strategies without the ability to cope with climate change,therefore the research on the operation optimization of a solar CCHP system considering the impact of climate change on the demand side was conducted.Taking a five-star hotel in Shanghai as an example,the regional climate model PRECIS(Providing Regional Climate for Impacts Studies)was firstly used to predict temperature and radiation in the region over the next 80 years;then,the predicted results were innovatively incorporated into the DeST software to accurately identify the fluctuation of user demand caused by climate change;next,the predicted user demand was incorporated into the traditional operation optimization model of coupled solar CCHP system;finally,the energy-provision strategy adapted to the climate change was generated.The demand forecasting results demonstrated that,under the same RCP scenario,the cooling demand on the user side would increase year by year;conversely,the heating demand would decrease.In addition,the variation magnitude of two types of energy demand under the RCP8.5 scenario is greater than that under the RCP4.5 scenario.Compared with traditional operating optimization model without the consideration of climate change,this proposed model can effectively alleviate the energy supply shortage caused by extreme high temperature in summer under climate change and avoid the excessive energy supply in the warm winter.It improves the economic performance of the system while providing more stable energy supply service.(ii)In order to solve the limitation of the optimization model developed in research content(i),which only analyzed the correlation between multiple meteorological factors and the cooling,heating,and electricity demands of targeted hotel and neglected the deviation between the actual output of core equipments and their rated power under extreme weather condition,resulting in the high risk of supply-demand imbalance and lower robustness of supply strategies,in this thesis,the study on the energy supply optimization with the synergistic influence of climate change on both the demand and supply sides was accomplished.Taking a hospital in Shanghai as a case study,the regional climate simulation software PRECIS was firstly utilized to predict the temperature and humidity in target area for the next 80 years.Secondly,hospital’s energy consumption simulation model was established by aid of demand prediction software TRNSYS,which incorporates typical annual temperature and radiation prediction results under climate change for different time interval(recent,2025,mid-term 2050,mid-to-long term 2075,and long-term 2098)into the demand prediction process in order to accurately evaluate the fluctuating trend in user energy demand under climate change.Thirdly,as a core equipment of the CCHP system,the mechanism simulation model of the gas turbine was formulated,which quantitatively reflected the adverse effect of extreme high temperature caused by climate change on the electricity generation and the heating value of waste heat exhaust gas.Finally,the operation optimization model of the CCHP system with user’s demand prediction and equipment’s output calculation was established,leading to an optimal energy supply plan that was adaptable to climate change and providing effective technical support for the energy efficiency improvement and cost saving in the future.(iii)Due to the fact that the operation optimization model of CCHP system developed in research content(ii)only focuses on the maximum demand value of user side and minimum output value of supply side,such that generation process of optimal energy-supply strategy for future typical years is failing to comprehensively consider the influence exerted by historical weather condition,future climate change characteristics and other uncertainties(such as policy influence and human operation),leading to poor coherence of generated operation plan and increase of supply-demand imbalance risk.In this article,a five-star hotel in Beijing was selected as an example for exploring the coordinated impact of climate change and uncertainty on the demand and supply sides.The various software tools(including PRECIS and DeST)and mechanism simulation methods were firstly exploited to predict meteorological elements,users’ demand and equipment output.Secondly,both mentioned above predicted values and the historical values of user demand and equipment output were used to identify and represent critical uncertain parameters based on appropriate uncertainty-analysis methods(including interval,random and fuzzy),which replaced the deterministic variables of traditional operation optimization model of solar CCHP system.Next,the uncertain operation optimization model for the solar CCHP system was established,which coupled with regional climate simulation,user-side demand prediction,and supply-side equipment simulation under climate change.Finally,the uncertainty optimization algorithm was used to solve this model,leading to the optimal energy supply scheme with the capabilities of adapting to climate change and tackling the uncertainties.To sum up,a unified model framework that integrates regional climate simulation,user-side demand forecasting method,supply-side mechanism simulation method,uncertainty identification method,and operation-side optimization method was established.This model comprehensively considered the interaction relationships among various levels of energy supply system and proposed an operation mode that maximizes the economic benefits,promotes efficient energy utilization,and maintains supply-demand balance.This combine approach effectively solved a series of problems,including irrational energy demand prediction due to the overlook of the influence caused by climate change and the over dependence on the empirical coefficient,oversimplified output calculation of critical equipment,the uncertainty identification depending on the subjective judgment,as well as potential imbalance of energy supply and demand.It provides the valuable insight for decision-makers to choose optimal operation pattern for CCHP system while ensuring more stable energy supply service. |
PDF Full Text Request