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Aggregating Large-Scale Generalized Energy Storages to Participate in Energy Market and Regulation Market

Yao Yao, Peichao Zhang, Sijie Chen

TL;DR

This work introduces generalized energy storage (GES) to unify heterogeneous flexible loads under a degree-of-satisfaction (DoS) state and a unified dynamic model. It proposes a market-based, real-time coordination framework that uses DoS-equality and demand curves to allocate aggregate power across devices operating in continuous or discrete modes, enabling participation in both energy and regulation markets. A low-dimensional aggregate model for a GES cluster is derived, enabling tractable optimization for multi-market flexibility allocation. Simulations show significant cost reductions for an aggregator and high tracking accuracy, with robustness limited by ideal communication assumptions in the study.

Abstract

This paper proposes a concept of generalized energy storage (GES) to facilitate the integration of large-scale heterogeneous flexible resources with electric/thermal energy storage capacity to participate in multiple markets. First, a generalized state variable referred to as degree of satisfaction (DoS) is defined, and dynamic models with a unified form are derived for different types of GESs. Second, a real-time market-based coordination framework is proposed to facilitate control, and ensure user privacy and device security. Demand curves of different GESs are then developed based on DoS to express their demand urgencies as well as flexibilities. Furthermore, a low-dimensional aggregate dynamic model of a GES cluster is derived thanks to the DoS-equality control feature provided by the design of demand curve. At last, an optimization model for a large-scale GESs to participate in both the energy market and regulation market is established based on the aggregate model. Simulations results demonstrate that the optimization algorithm could effectively reduce the total cost of an aggregator. Additionally, the proposed coordination method has high tracking accuracy and could well satisfy users' diversified power demand.

Aggregating Large-Scale Generalized Energy Storages to Participate in Energy Market and Regulation Market

TL;DR

This work introduces generalized energy storage (GES) to unify heterogeneous flexible loads under a degree-of-satisfaction (DoS) state and a unified dynamic model. It proposes a market-based, real-time coordination framework that uses DoS-equality and demand curves to allocate aggregate power across devices operating in continuous or discrete modes, enabling participation in both energy and regulation markets. A low-dimensional aggregate model for a GES cluster is derived, enabling tractable optimization for multi-market flexibility allocation. Simulations show significant cost reductions for an aggregator and high tracking accuracy, with robustness limited by ideal communication assumptions in the study.

Abstract

This paper proposes a concept of generalized energy storage (GES) to facilitate the integration of large-scale heterogeneous flexible resources with electric/thermal energy storage capacity to participate in multiple markets. First, a generalized state variable referred to as degree of satisfaction (DoS) is defined, and dynamic models with a unified form are derived for different types of GESs. Second, a real-time market-based coordination framework is proposed to facilitate control, and ensure user privacy and device security. Demand curves of different GESs are then developed based on DoS to express their demand urgencies as well as flexibilities. Furthermore, a low-dimensional aggregate dynamic model of a GES cluster is derived thanks to the DoS-equality control feature provided by the design of demand curve. At last, an optimization model for a large-scale GESs to participate in both the energy market and regulation market is established based on the aggregate model. Simulations results demonstrate that the optimization algorithm could effectively reduce the total cost of an aggregator. Additionally, the proposed coordination method has high tracking accuracy and could well satisfy users' diversified power demand.

Paper Structure

This paper contains 29 sections, 39 equations, 18 figures, 2 tables.

Figures (18)

  • Figure S1: DoS of different GESs.
  • Figure S2: Demand curve of a CP-GES.
  • Figure S3: Demand curve of DP-GES.
  • Figure S4: $S$ and $S'$ of a DP-GES at different $\lambda^*$.
  • Figure S5: Participation in energy and regulation market.
  • ...and 13 more figures