Advanced Distributed Decision-making framework for Smart grid aggregators

今天，配电网络正处于从需求驱动型向积极的资产驱动型实体转变的时代，体现在分散式发电机组措施的扩大、对电力市场的全面反思以及终端用户对需求响应（DR）计划的日益参与。为此，配电网络将从自上而下的结构演变为自下而上的结构，客户在配电系统中的角色将从被动转变为主动参与。新的能源市场参与者，如网络微电网、主动建筑聚合器和负载聚合器，可以通过其本地发电、存储和需求灵活性来支持配电网运营商。在集成器内运行这样的玩家集群可能是利用分布式能源（DER）的最佳方式，为批发电力系统提供低成本可靠性产品，即为传输系统提供辅助服务。能源市场对聚合或需求响应聚合器很感兴趣，因为这种结构可以实施强大的经济激励措施，吸引许多参与者。在这种转型中，运营商通过适当协调可用资源和需求侧管理机制，持续保持电网的平衡至关重要。尽管有这些优势，但在容纳大量参与者（微电网、负载、DERs等）方面存在一些挑战。一些主要的挑战是：1)集中优化方法的难治性；2)行为的异质性及其利益的分歧；(3)被聚合器调用时，负载和分布式能源可用性的不确定性；(4)不同客户之间需求响应奖励的公平性。在这个发现项目中，我们的目标是克服与许多需求响应参与者的协调相关的一些挑战，特别是那些与减轻维度诅咒有关的挑战，允许在聚合水平上对冲不确定性。我的研究计划的长期目标是开发先进和高性能的工具来模拟和分布优化各种能源市场参与者在配电网。特别是，我们的目标是通过适当的方法捕获适当的可再生能源和负荷不确定性，实现能源交易机制和参与者之间DR奖励分配的公平性。提出的发现计划将有助于分布式能源的发展，智能电网中聚合器的增长。该提案将为一项长期计划奠定基础，确保：1)加拿大hqp成为智能电网系统算法设计领域的世界领导者；2)在新的大型项目中发挥重要作用，如由Hydro-Quebec、Schneider等合作伙伴共同资助的nserc联盟。

Today, electricity distribution networks are in the era of transforming from a demand-driven to an active asset driven entity, portrayed by expanding measures of decentralized generation units, complete rethinking of the electricity market and an increasing participation of end-users in demand response (DR) programs. To this end, distribution networks will be evolving from a top-down structure into a bottom-up structure and the role of customers in distribution systems will shift from passive to an active participation. New energy market players such as networked microgrids, active building aggregators and load aggregators can support the distribution network operator through their local generation, storage and demand flexibility. The operation of such clusters of players within the aggregator is possibly the best way to utilize distributed energy resources (DER), to supply low cost reliability products to the wholesale electricity system i.e., providing ancillary services to the transmission system. Aggregation or demand response aggregators are interesting to the energy market as such structure could implement powerful economic motivators to attract many participants. With such transformation, it is vital for the operators to continuously preserve the balance in the electricity grid through appropriate coordination of available resources and demand side management mechanisms. Despite these advantages, there exist several challenges associated with accommodating large number of participants (microgrids, loads, DERs, etc.). Some of the main challenges are: 1) intractability of centralised optimization approaches; 2) the heterogeneity of actions and their diverging interests; 3) the uncertainty in the availability of loads and distributed energy resources when called upon the aggregator and 4) the fairness in the rewards from demand response among various customers. In this discovery program, we aim to overcome some of the challenges associated with coordination of many demand response players, especially those related to mitigating the curse of dimensionality allowing to hedge against uncertainty at aggregation level.  The long-term objective of my research program aims to develop advanced and high-performance tools to model and distributively optimize various energy market players in the distribution network. Particularly, we aim to capture properly renewable energy sources and load uncertainties via appropriate methods, achieve fairness in energy trading mechanisms and in DR rewards distribution among players. The proposed Discovery program will contribute to the development of distributed energy resources, the growth of aggregators in smart grids. The proposal will set the foundations for a long-term program ensuring that: 1) Canadian HQPs become world leaders in the field of algorithms design in smart grids systems and 2) Significant leverage for new larger projects such NSERC-Alliance co-financed by partners like Hydro-Quebec, Schneider.