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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 of 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 of 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. We also study the benefits of using energy storage when we rate control solar. To do so, we present a decentralized algorithm to charge and discharge batteries for each smart solar. Our evaluation on a city-scale dataset shows that our approach enables 2.6× 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 30× faster convergence. Finally, we demonstrate energy storage can help netmeter more solar energy while ensuring fairness and grid constraints are met.
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Enforcing fair grid energy access for controllable distributed solar capacity
The rapid expansion of intermittent grid-tied solar capacity is making the job of balancing electricity's real-time supply and demand increasingly challenging. To address the problem, recent work proposes mechanisms for actively controlling solar power output to the grid by enabling software to cap it as a fraction of its time-varying maximum output. Utilities can use these mechanisms to dynamically share the grid's solar capacity by controlling the solar output at each site. However, while enforcing an equal fraction of each solar site's time-varying maximum output results in "fair" short-term contributions of solar power, it does not result in "fair" long-term contributions of solar energy. This discrepancy arises from fundamental differences in enforcing "fair" access to the grid to contribute solar energy, compared to analogous fair-sharing in networks and processors. In this paper, we present a centralized and distributed algorithm to enable control of distributed solar capacity that enforces fair grid energy access. We implement our algorithm and evaluate it on synthetic data and real data across 18 solar sites. We show that traditional rate allocation, which enforces equal rates, results in solar sites contributing up to 18.9% less energy than an algorithm that enforces fair grid energy access over a single month.
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- PAR ID:
- 10062536
- Date Published:
- Journal Name:
- ACM International Conference on Systems for Energy-Efficient Built Environments
- Page Range / eLocation ID:
- 1 to 10
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3137133.3137147
