AMPS: Collaborative Research: Stochastic Modeling of the Power Grid

该项目将为现代电网中经济利益相关者之间的相互作用建立数学模型。虽然电力市场正在变得分散，但在市场条件和法规波动的情况下，了解潜在的市场力量仍然不足。为决策者提供更高质量的信息和建模辅助对于实现电网效率和增强稳定性至关重要。这对于避免困扰电网经济政策制定的意外后果，以及制定有效的法规，激励利益相关者的行为与社会目标（如气候变化适应和新技术投资）保持一致，也是至关重要的。该项目将构建严格的随机模型和相关的数值算法，以定量评估和分析如何引导电网的“智能”进化。该研究将解决(i)长期电网发展，特别是对可再生能源发电的投资和不同生产部门之间的竞争；（二）可再生能源深度渗透、微电网、电网稳定性新要求下的电价及相关金融合同行为。该项目融合了应用数学、博弈论和控制，并将随机学的范围扩展到一个关键的应用领域。该项目将促进数学科学博士水平的跨学科培训，并将加强数学家、运筹学研究人员、工程师和统计学家之间的思想交流。

This project will develop mathematical models for the interactions between the economic stake-holders in the modern power grid. While the electricity market is becoming decentralized, understanding the underlying market forces in the presence of fluctuating market conditions and regulations remains inadequate. Providing higher quality information and modeling aids to decision makers is crucial in the drive to achieve grid efficiency and enhanced stability. It is also central to avoiding unintended consequences that have plagued economic policy-making for the grid and for making effective regulations that incentivize aligning stakeholder behavior with societal goals, such as climate change adaptation and investment in new technologies.The project will construct rigorous stochastic models and related numerical algorithms for quantitative assessment and analysis of how to guide the grid in its "smart" evolution. The research will address (i) long-term grid evolution, in particular investment in renewable generation and competition between different producer sectors; (ii) behavior of electricity prices and related financial contracts in the new era of deep renewable penetration, micro-grids, and new requirements on grid stability. The project blends together applied mathematics, game theory, and control, and extends the reach of stochastics to a key application area. The project will contribute to inter-disciplinary training in mathematical sciences at the PhD level and will enhance the exchange of ideas between mathematicians, operations researchers, engineers, and statisticians.