SBIR Phase I: A Smartphone Incentive System to Align Electricity Demand with Intermittent Supply

这个小型企业创新研究计划(SBIR)第一阶段项目将解决电力公用事业公司在增加越来越多的间歇性可再生能源发电系统时在维护电网稳定性方面面临的挑战。太阳能和风能是可变的，因此使平衡能源生产和消耗的过程变得复杂。这个项目的目标是展示基于软件的解决方案的可行性，以帮助实现这种平衡，减少对昂贵的能源存储的需求。这项服务将通过智能手机向消费者提供实时激励，以响应请求减少或增加用电量。另一个目标是证明机器学习算法可以帮助服务基于环境、位置和个人因素估计消费者响应率。该项目将包括对居民用电用户的初步试验，他们将被发送响应模拟条件的请求；一些用户将能够通过智能手机调整负载。从试验中收集的用电量和其他数据将用于训练和测试机器学习估计器，并评估验证消费者是否如承诺的表现的方法。该项目更广泛的影响/商业潜力将是提高公用事业公司在电网中增加可再生能源发电的能力，同时最大限度地减少对昂贵补偿解决方案的需求，如燃气轮机调峰厂或储能。它还将降低高峰电力需求，进一步减少对调峰电厂的需求，从而降低公用事业公司和消费者的成本。最终结果将是减少对化石燃料发电的依赖，提高国家的能源安全，减少温室气体排放。第二个影响将是改善客户的教育和对他们的能源消耗的参与度。因此，消费者可能更有可能购买和安装节能家电和家居装修，进一步降低能源消耗。加强对这种关系的技术理解，特别是考虑到智能手机和相关应用的激增，将提高创造激励措施促进电网友好型能源消耗的能力。

This Small Business Innovation Research Program (SBIR) Phase I project will address challenges that electric utilities face in maintaining stability of their grids as more and more intermittent renewable energy generating systems are added to them. Solar and wind are variable and thus complicate the process of balancing energy generation with consumption. The objective of this project is to show the viability of a software-based solution to assist with this balance, reducing the need for expensive energy storage. This service will provide real-time incentives to consumers via their smart phones to reduce or increase electricity usage in response to a request. Another objective is to demonstrate that machine-learning algorithms can help the service estimate consumer response rate based upon environmental, locational, and personal factors. The project will include a preliminary trial with residential electricity consumers where they will be sent requests in response to simulated conditions; some will be able to adjust loads from their smart phones. Electricity usage and other data gathered from the trial will be used to train and test the machine-learning estimators and to evaluate methods that validate whether the consumer performed as promised. The broader impact/commercial potential of this project will be to increase utilities' ability to add renewable electricity generation to their grids while minimizing the need for expensive compensating solutions like gas turbine peaking plants or energy storage. It will also lower peak electricity demand, further reducing the need for peaking plants and therefore reducing costs for utilities and consumers. The end result will be less reliance on fossil fuel for electricity generation, improving the nation's energy security and reducing greenhouse gas emissions. A second impact will be to improve customers' education and engagement with their energy consumption. As a result, consumers may be more likely to purchase and install energy-efficient appliances and home improvements, further reducing energy consumption. An increased technical understanding of that relationship, particularly given the proliferation of smartphones and related applications, will improve the ability to create incentives to foster grid friendly energy consumption.