为解决综合能源生产单元(integrated energy production unit,IEPU)中燃煤机组碳捕集过程的高能耗问题,同时应对新能源不确定性对运行调度带来的挑战,该文提出一种考虑太阳能辅助碳捕集技术的IEPU随机低碳调度策略,旨在实现IEPU的多能协同与低碳运行.首先,对含太阳能辅助碳捕集热电联产单元(combined heat and power based on solar-assisted carbon capture,CHP-SACC)的能量流动与运行机理进行分析,并构建其运行模型;其次,考虑风电不确定性带来的影响,提出一种基于条件最小二乘生成对抗网络(conditional-least squares generative adversarial networks,C-LSGANs)的可再生能源场景生成方法来提高场景的生成质量;然后,考虑异质能流耦合约束、多元设备运行约束以及能量平衡约束等,以最大化系统运行收益期望为目标构建IEPU随机低碳调度模型;最后,在算例仿真中设置不同的运行策略验证所提低碳转型方案的有效性,并分析了能源价格、设备容量等因素对系统运行收益的影响.
Stochastic Low-carbon Scheduling Strategy of Integrated Energy Production Unit Considering Solar-assisted Carbon Capture Technology
To solve the problem of high energy consumption in the carbon capture process of coal-fired units in the integrated energy production unit(IEPU),and to deal with the challenges brought by the uncertainty of new energy sources to the operation scheduling,this paper proposes a stochastic low-carbon scheduling strategy for IEPU considering solar-assisted carbon capture technology,aiming to achieve multi-energy coordination and low-carbon operation of IEPU.First,the energy flow and operation mechanism of combined heat and power integrated units based on solar-assisted carbon capture(CHP-SACC)are analyzed,and its operation model is also constructed.Second,a renewable energy scenario generation method based on conditional-least squares generative adversarial networks(C-LSGANs)is proposed to improve the quality of scenario generation considering the impact of wind power uncertainty.Then,considering different energy flow coupling constraints,multi-device operation constraints and energy balance constraints,the IEPU stochastic low-carbon scheduling model is constructed to maximize the system operation revenue expectation.Finally,the effectiveness of the proposed low-carbon transition scheme is verified by setting different operation strategies in the case simulation,and the impact of energy price,equipment capacity and other factors on the system operation benefit is analyzed.
integrated energy production unitgenerating adversarial networkswind power uncertaintyrandom low-carbon scheduling
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