BRIGE: A Fully Distributed Multi-Agent System Based Energy Management Solution for Microgrids

智力优势：智能技术是使现有电力系统更加智能化的经济有效的解决方案。为了提高微电网的可靠性和能源效率，降低控制系统的成本，完全分布式的控制方案是可取的。多智能体系统作为目前最流行的分布式控制解决方案之一，在电力系统运行控制中得到了广泛的应用。然而，现有的解决方案适用性有限，缺乏严格的稳定性分析。为了解决微电网的需求和现有解决方案的问题，PI？S的长期研究目标是研究基于全分布式多智能体系统的控制解决方案。在这个项目中，PI将设计三种基于稳定全局信息发现算法的全分布式优化算法。所设计的算法可以根据模型可用性、复杂度和响应时间等因素对不同的能源管理任务进行选择。基于agent的分析，提出高效的同步技术。自主活动。将为具有多种不同类型分布式能源的微电网开发具有不同细节级别的模型。开发的模型将用于评估候选解的动态性能，并克服优化算法的缺点。提出的算法可以实时解决简单问题，也可以在几秒或更快的时间内解决复杂问题。实时模拟和实验将用于调查真实世界的性能。更广泛的影响：该项目将通过引入新的理论和技术，在电力和能源研究领域开辟新的领域。计划中的工作将向电力工程师证明，先进的计算智能技术可以为复杂的工程问题带来新颖的解决方案。该项目的成功也将激励其他社会提出新的应用和挑战。该项目通过无缝集成电力系统调度和控制，有可能彻底改变电力系统运行的实践。分布式优化算法可以应用于许多其他大规模在线优化和控制问题。该项目将产生两个研究生RA职位，创建两个新的多学科课程，并通过为新墨西哥州立大学的大量少数民族学生提供优秀的实践学习机会来扩大参与。计划开展外展活动，以提高公众对智能电网的认识、理解和信心。该项目的微电网测试平台、高质量的出版物和训练有素的学生将大大提高新墨西哥州立大学进行相关研究的能力，并从政府和行业吸引新的资金。

Intellectual Merit: Intelligent techniques are cost efficient solutions to making existing power systems smarter. To improve the reliability and energy efficiency of microgrids and lower the cost of the control system, fully distributed control solutions are preferable. As one of the most popular distributed control solutions, multi-agent systems have been widely applied for power system operation and control. However, existing solutions have limited applicability and lack rigorous stability analysis. To address the needs of microgrids and the problems with existing solutions, one of the PI?s long term research goals is to study fully distributed multi-agent system based control solutions. In this project, the PI will design three types of fully distributed optimization algorithms based on a stable global information discovery algorithm. The designed algorithms can be selected for different energy management tasks based on model availability, complexity, and response time, etc. Efficient synchronization techniques will be proposed based on analysis of agents? autonomous activities. Models with different levels of details will be developed for microgrids with multiple different types of distributed energy resources. The developed models will be used to evaluate the dynamic performances of candidate solutions and overcome the disadvantages of the optimization algorithms. The proposed algorithms can solve simple problems in real time or complex problems in several seconds or faster. Real-time simulation and experimentation will be used to investigate real world performance.Broader Impacts: This project will create new fields in power and energy research by introducing new theories and technologies. The planned work will demonstrate to power engineers that advanced computational intelligence techniques can bring about novel solutions for complex engineering problems. The success of this project will also inspire other societies with new applications and challenges. The project has potential to revolutionize the practice of power system operation by seamlessly integrating power system scheduling and control. The distributed optimization algorithms can be applied to many other large-scale online optimization and control problems. The project will generate two graduate RA positions, create two new multidisciplinary courses, and broaden participation by providing excellent hands-on learning opportunities for the large population of minority students at New Mexico State University. Outreach activities are planned to improve public awareness, understanding, and confidence of the Smart Grid. The microgrid testbed, high quality publications, and trained students produced according to this project will greatly enhance the capability of New Mexico State University in doing related research and attracting new funding from governments and industries.