Advanced Distributed Decision-making framework for Smart grid aggregators

如今，配电网正处于从需求驱动向积极资产驱动实体转变的时代，表现为分散式发电机组的措施不断扩大，对电力市场的全面反思以及最终用户越来越多地参与需求响应（DR）计划。为此，分销网络将从自上而下的结构演变为自下而上的结构，客户在分销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，如联网微电网，有源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络运营商。聚合器内的这种参与者集群的操作可能是利用分布式能源（DER）的最佳方式，以向批发电力系统供应低成本可靠性产品，即，为传输系统提供辅助服务。聚合或需求响应聚合器对能源市场很感兴趣，因为这种结构可以实现强大的经济激励，吸引许多参与者。随着这种转变，运营商必须通过适当协调可用资源和需求侧管理机制来持续保持电网的平衡。尽管有这些优点，但存在与容纳大量参与者（微电网、负载、DER等）相关联的若干挑战。一些主要挑战是：1）集中式优化方法的棘手性; 2）动作的异质性及其不同的利益; 3）当调用聚合器时负载和分布式能源的可用性的不确定性;以及4）来自各种客户之间的需求响应的回报的公平性。在这个发现计划中，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灾难有关的挑战，从而可以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建模和分布式优化配电网络中的各种能源市场参与者。特别是，我们的目标是通过适当的方法适当地捕获可再生能源和负载的不确定性，实现能源交易机制和参与者之间DR奖励分配的公平性。拟议的发现计划将有助于分布式能源的发展，智能电网聚合器的增长。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）对新的大型项目具有重要影响力，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.