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An assessment of the load modifying potential of model predictive controlled dynamic facades within the California context

机译:在加利福尼亚范围内评估模型预测受控动态立面的荷载改变潜力

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摘要

California is making major strides towards meeting its greenhouse gas emission reduction goals with the transformation of its electrical grid to accommodate renewable generation, aggressive promotion of building energy efficiency, and increased emphasis on moving toward electrification of end uses (e.g., residential heating, etc.). As a result of this activity, the State is faced with significant challenges of systemwide resource adequacy, power quality and grid reliability that could be addressed in part with demand responsive (DR) load modifying strategies using controllable building technologies. Dynamic facades have the ability to potentially shift and shed loads at critical times of the day in combination with daylighting and HVAC controls. This study explores the technical potential of dynamic facades to support net load shape objectives. A model predictive controller (MPC) was designed based on reduced order thermal (Modelica) and window (Radiance) models. Using an automated workflow (involving JModelica.org and MPCPy), these models were converted and differentiated to formulate a non-linear optimization problem. A gradient-based, non-linear programming problem solver (IPOPT) was used to derive an optimal control strategy, then a post-optimization step was used to convert the solution to a discrete state for facade actuation. Continuous state modulation of the facade was also modeled. The performance of the MPC controller with and without activation of thermal mass was evaluated in a south-facing perimeter office zone with a three-zone electrochromic window for a clear sunny week during summer and winter periods in Oakland and Burbank, California. MPC strategies reduced total energy cost by 9-28% and critical coincident peak demand was reduced by up to 0.58 W/ft(2)-floor or 19-43% in the 4.6 m (15 ft) deep south zone on sunny summer days in Oakland compared to state-of-the-art heuristic control. Similar savings were achieved for the hotter, Burbank climate in Southern California. This outcome supports the argument that MPC control of dynamic facades can provide significant electricity cost reductions and net load management capabilities of benefit to both the building owner and evolving electrical grid. (C) 2020 The Authors. Published by Elsevier B.V.
机译:加利福尼亚州正在努力实现其温室气体减排目标,包括改造电网以适应可再生能源发电,积极提高建筑能效以及更加重视最终用途电气化(例如住宅供暖等)。 )。这项活动的结果是,纽约州面临着全系统资源充足性,电能质量和电网可靠性的重大挑战,这些挑战可以部分通过使用可控建筑技术的需求响应(DR)负载调整策略来解决。动态立面结合采光和HVAC控制功能,可以在一天中的关键时刻潜在地转移和减轻负荷。这项研究探讨了动态立面支持净荷载形状目标的技术潜力。基于降阶热模型(Modelica)和窗口模型(Radiance)设计了模型预测控制器(MPC)。使用自动工作流程(涉及JModelica.org和MPCPy),对这些模型进行了转换和区分,从而提出了非线性优化问题。使用基于梯度的非线性规划问题求解器(IPOPT)来得出最佳控制策略,然后使用后优化步骤将解决方案转换为离散状态以进行外墙驱动。还对立面的连续状态调制进行了建模。在夏季和冬季,在加利福尼亚州奥克兰和伯班克,在晴朗的晴天,在带有三区电致变色窗的朝南外围办公室区域中,评估了有无激活热质量的MPC控制器的性能。 MPC策略将总能源成本降低了9-28%,并且关键的同时高峰需求在4.6 m(15英尺)深的南部地区,在阳光明媚的夏日减少了0.58 W / ft(2)-地板或19-43%。与最先进的启发式控制相比在南加利福尼亚州更炎热的伯班克气候中也获得了类似的节省。这一结果支持这样的论点,即动态立面的MPC控制可以显着降低电力成本和净负荷管理功能,这既有益于建筑物所有者,也有益于不断发展的电网。 (C)2020作者。由Elsevier B.V.发布

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