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A novel multi-market optimization problem for commercial heating, ventilation, and air-conditioning systems providing ancillary services using multi-zone inverse comprehensive room transfer functions

机译:商业化供暖,通风和空调系统的新型多市场优化问题,它使用多区域逆综合房间传递函数提供辅助服务

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摘要

Electricity grids increasingly include demand response in not only the energy market, but also grid-stabilizing ancillary services markets. Commercial buildings can provide demand response through use of their heating, ventilating, and air-conditioning systems to access the buildings' thermal storage capacity. Within a model predictive control framework, commercial buildings can optimize demand response while respecting thermal comfort and system limits. In this article, a novel multi-market optimization problem that minimizes total operating costs, including energy costs, and separate revenues from regulation and reserve markets, is proposed. The 24-hour multi-zone and multi-market optimization problem is solved using a multi-zone inverse comprehensive room transfer function model of an 18-zone office building and accompanying variable air volume heating, ventilating, and air-conditioning system model. Optimal energy use, ancillary service provision, energy cost, and ancillary service revenues are reported for eight scenarios, which highlight the impact of ancillary service provision on optimal energy use and the effect of thermal mass on demand response provision. This work improves the operating capabilities of an individual building using model predictive control and can also be used to better understand demand-side resource potential for energy and ancillary services from a grid-planning perspective.
机译:电网不仅在能源市场中而且在稳定电网的辅助服务市场中都包括需求响应。商业建筑物可以通过使用其供暖,通风和空调系统来提供建筑物的蓄热能力,从而满足需求。在模型预测控制框架内,商业建筑可以在满足热舒适性和系统限制的同时优化需求响应。在本文中,提出了一种新颖的多市场优化问题,该问题可将包括能源成本在内的总运营成本降至最低,并从监管和储备市场中分离收益。使用一个18区办公楼的多区逆综合房间转移函数模型以及相应的可变风量供暖,通风和空调系统模型,可以解决24小时多区和多市场优化问题。报告了八个方案的最佳能源使用,辅助服务提供,能源成本和辅助服务收入,这些情况突出了辅助服务提供对最佳能源使用的影响以及热质量对需求响应提供的影响。这项工作使用模型预测控制提高了单个建筑物的运行能力,还可以用于从网格规划的角度更好地了解能源和辅助服务的需求侧资源潜力。

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