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Demand-side flexibility and demand-side bidding for flexible loads in air-conditioned buildings

机译:空调建筑中柔性负荷的需求侧灵活性和需求侧竞标

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Demand-side flexibility (DSF) has been touted as a possible solution to the challenges in power system operation arising from increasing intermittent renewables penetration and the emergence of electric vehicles. In Singapore, where around 24 to 60% of electricity demand in buildings could be attributed to heating, ventilation, and air conditioning (HVAC) purposes, air-conditioned buildings represent a significant flexibility resource which could be used to provide DSF and help tackle these challenges. This study aims to investigate the DSF potential of Singapore's building stock and to explore how this potential could be realized through demand-side bidding. To this end, a building energy modeling tool with explicit modeling of the relationship between occupant comfort and HVAC load with model predictive control, CoBMo, is used. CoBMo allows optimal load scheduling to be expressed as a linear programming problem: minimizing overall electricity cost while maintaining occupant comfort. A price-based market clearing model is developed to evaluate demand side bidding implementation, for which a case study on Singapore's Downtown Core district is developed. Three scenarios with possible future utility-scale photovoltaic (PV) penetration in Singapore's electricity system are explored, alongside a sensitivity analysis and a comparison between centralized dispatch and demand-side bidding with price-quantity pairs and linear curves. Results of the analysis show that DSF potential varies between building types, depending on cooling load and occupancy schedule. When extreme price fluctuations happen in future Singapore electricity market with 10 GWp PV penetration, demand-side bidding could aid consumers to utilize their DSF potential by encouraging more effective energy use and in turn, reducing their total electricity cost.
机译:需求侧的灵活性(DSF)已被推迟作为可能的解决方案,以提高间歇性再生能源渗透率和电动汽车的出现而产生的电力系统运行中的挑战。在新加坡,建筑物的电力需求约24%至60%可归因于加热,通风和空调(HVAC)目的,空调建筑代表了一个显着的灵活性资源,可用于提供DSF并帮助解决这些资源挑战。本研究旨在调查新加坡建筑股票的DSF潜力,并探讨如何通过需求方竞标实现这种潜力。为此,使用具有明确建模的建筑能源建模工具,与模型预测控制,COBMO之间的乘员舒适和HVAC负载之间的关系。 Cobmo允许最佳负载调度表示为线性编程问题:在保持乘员舒适度的同时最大限度地降低整体电力成本。制定了基于价格的市场清算模式,以评估需求方竞标实施,为此开发了新加坡市中心核心区的案例研究。探讨了新加坡电力系统未来可能的未来实用尺度光伏(PV)渗透的三种情况,伴随着灵敏度分析,以及价格数量对和线性曲线的集中调度和需求侧竞标的比较。分析结果表明,根据冷却负荷和占用时间表,DSF电位在建筑物类型之间变化。当以10 GWP PV渗透的未来的新加坡电力市场发生极端价格波动时,需求方竞标可以帮助消费者通过鼓励更有效的能源使用,并反过来降低其总电力成本,以帮助消费者利用他们的DSF潜力。

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