CPS: Synergy: Distributed coordination of smart devices to mitigate intermittency of renewable generation for a smarter and sustainable power grid

该项目的最终目标是帮助电网变得更加可靠，即使大量电力来自太阳能和风能等间歇性的绿色能源。为了应对这种间歇性，需要廉价的能源储存。该项目不是投资电池，而是寻求通过智能决策算法操纵消费者负载的电力需求，以获得廉价的存储空间。通过上下改变负载的名义耗电量，可以使负载的行为像电池一样，从而有效地创建虚拟储能(VES)源。这种虚拟存储比电池便宜，因为它是基于软件的解决方案；几乎不需要额外的硬件。该项目的另一个方面是开发决策算法，以应对由于间歇性太阳能发电的使用日益增加而导致的配电网(向社区输送电力)面临的操作问题。实现这一愿景存在几个技术挑战：智能地操纵消费者负载和其他设备，以帮助电网可靠地运行。该项目旨在解决其中两个关键挑战。其一是在没有中央决策者的情况下，设计算法来协调大量负载的行动。分布式(而不是集中式)控制将是必要的，因为集中式方案的通信和计算负担不堪重负。同时，分布式控制算法需要以较低的通信带宽提供可靠的性能，并认识到在这种有人类参与的网络物理系统(CPS)中固有的隐私和安全问题。第二个挑战是，负荷时的需求操纵必须以这样一种方式进行，即消费者。服务质量(QoS)保持在严格的预先协商的范围内。一些技术创新为拟议的工作奠定了基础。这些创新包括(1)频率分解，将用户资源映射到电网？S需要的；(2)随机控制算法，将棘手的组合优化问题转化为易于处理的凸问题；(3)通过电网频率和电压测量的物理信号，使多智能体能够在没有显式通信的情况下进行协调。

The ultimate goal of the project is to help the electric grid become more reliable even when a large amount of electricity is generated from green, but intermittent - sources such as solar and wind. To deal with this intermittency, inexpensive source of energy storage are required. Instead of investing in batteries, this project seeks to obtain cheap storage by manipulating power demand in consumer loads through intelligent decision-making algorithms. By varying power demand up and down from what a load would nominally consume, the load can be made to behave like a battery, effectively creating a source of Virtual Energy Storage (VES). This kind of virtual storage is cheaper than batteries since it is a software-based solution; little additional hardware is needed. Another aspect of the project is to develop decision-making algorithms to cope with operational issues faced by the power distribution networks (that deliver electricity to neighborhoods) due to increasing use of intermittent solar power.There are several technical challenges in achieving this vision: of intelligently manipulating consumer loads and other devices to help the power grid operate reliably. This project aims to address two of these key challenges. One is the design of algorithms to coordinate the actions of a large number of loads without a central decision-maker. Distributed (as opposed to centralized) control will be necessary since the communication and computation burden of a centralized scheme is overwhelming. At the same time, distributed control algorithms need to deliver reliable performance with low communication bandwidth, and be cognizant of the privacy and security concerns inherent in such Cyber Physical Systems (CPS) with humans in the loop. The second challenge is that the demand manipulation at the loads has to be done in such a manner that consumers. Quality of Service (QoS) is maintained in tight, pre-negotiated bounds. A number of technical innovations undergird the proposed work. These innovations include (1) frequency decomposition to map consumer resources to grid?s needs, (2) randomized control algorithms to convert intractable combinatorial optimization problems to tractable convex problems, and (3) physical signaling through grid-frequency and voltage measurements to enable multi-agent coordination without explicit communication.