Distributed Rate Control for Smart Solar Arrays

Distributed Rate Control for Smart Solar Arrays
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智能太阳能电池阵列的分布式速率控制

DOI:
10.1145/3077839.3077840
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发表时间:
2017
期刊:
Proceedings of the Eighth International Conference on Future Energy Systems
影响因子:
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通讯作者:
Prashant J. Shenoy
Prashant J. Shenoy
中科院分区:
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文献类型:
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作者:
Stephen Lee;Srinivasan Iyengar;David E. Irwin;Prashant J. Shenoy

文献摘要

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技术的不断进步导致成本下降,世界各地安装的太阳能容量总量急剧增加。增加太阳能渗透率的一个缺点是,由于太阳能发电的间歇性,电网中可能出现供需不匹配。虽然储能可以用来掩盖这些问题,但我们认为,还需要明确控制每个太阳能电池阵列的太阳能发电速率,以实现高渗透率,同时处理供需不匹配。为了解决这个问题,我们提出了智能太阳能电池阵列的概念,它可以根据比例公平的概念主动调节太阳能输出。我们提出了一种基于拉格朗日优化的分散式算法,使每个智能太阳能电池阵列能够对其可以注入电网的太阳能功率的公平份额做出本地决策,然后提出一种感知广播响应协议,将我们的分散式算法实现到智能太阳能电池阵列中。我们对城市规模数据集的评估表明,我们的方法使太阳能渗透率提高了2.6倍,同时使智能阵列的输出减少了12.4%。通过采用自适应梯度方法,我们的分散算法的收敛速度快3到30倍。最后,我们实现了我们的分布式算法的树莓派类处理器上,以证明其可行性与有限的处理能力并网太阳能逆变器。
Continued advances in technology have led to falling costs and a dramatic increase in the aggregate amount of solar capacity installed across the world. A drawback on increased solar penetration is the potential for supply-demand mismatches in the grid due to the intermittent nature of solar generation. While energy storage can be used to mask such problems, we argue that there is also a need to explicitly control the rate of solar generation of each solar array in order to achieve high penetration while also handling supply-demand mismatches. To address this issue, we present the notion of smart solar arrays that can actively modulate their solar output based on the notion proportional fairness. We present a decentralized algorithm based on Lagrangian optimization that enables each smart solar array to make local decisions on its fair share of solar power it can inject into the grid, and then present a sense-broadcast-respond protocol to implement our decentralized algorithm into smart solar arrays. Our evaluation on a city-scale dataset shows that our approach enables 2.6x more solar penetration, while causing smart arrays to reduce their output by as little as 12.4%. By employing an adaptive gradient approach, our decentralized algorithm has 3 to 30x faster convergence. Finally, we implement our distributed algorithm on a Raspberry Pi-class processor to demonstrate its feasibility on grid-tied solar inverters with limited processing capability.