Advanced Distributed Decision-making framework for Smart grid aggregators

点击翻译按钮获取中文摘要

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.