Day-ahead micro-market design for distributed energy resources

Postprint (author's final draft

Centralised and distributed optimization for aggregated flexibility services provision

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe recent deployment of distributed battery units in prosumer premises offer new opportunities for providing aggregated flexibility services to both distribution system operators and balance responsible parties. The optimization problem presented in this paper is formulated with an objective of cost minimization which includes energy and battery degradation cost to provide flexibility services. A decomposed solution approach with the alternating direction method of multipliers (ADMM) is used instead of commonly adopted centralised optimization to reduce the computational burden and time, and then reduce scalability limitations. In this work we apply a modified version of ADMM that includes two new features with respect to the original algorithm: first, the primal variables are updated concurrently, which reduces significantly the computational cost when we have a large number of involved prosumers; second, it includes a regularization term named Proximal Jacobian (PJ) that ensures the stability of the solution. A case study is presented for optimal battery operation of 100 prosumer sites with real-life data. The proposed method finds a solution which is equivalent to the centralised optimization problem and is computed between 5 and 12 times faster. Thus, aggregators or large-scale energy communities can use this scalable algorithm to provide flexibility services.Peer ReviewedPostprint (published version

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Optimization problem for meeting distribution system operator requests in local flexibility markets with distributed energy resources

The increasing penetration of distributed energy resources in the distribution grid is producing an ever-heightening interest in the use of the flexibility on offer by said distributed resources as an enhancement for the distribution grid operator. This paper proposes an optimization problem which enables satisfaction of distribution system operator requests on flexibility. This is a decision-making problem for a new aggregator type called Smart Energy Service Provider (SESP) to schedule flexible energy resources. This aggregator operates a local electricity market with high penetration of distributed energy resources. The optimization operation problem of SESP is formulated as an MILP problem and its performance has been tested by means of the simulation of test cases in a local market. The novel problem has also been validated in a microgrid laboratory with emulated loads and generation units. The performed tests produced positive results and proved the effectiveness of the proposed solution.Peer Reviewe