Transactive Energy-Based Joint Optimization of Energy and Flexible Reserve for Integrated Electric-Heat Systems

Abstract

Implementing integrated electric-heat systems (IEHSs) with coupled power distribution networks and district heating networks is an essential means to solve current energy problems. However, prosumers with multiple energy forms coupled and renewable energy sources with natural uncertainties pose challenges to the operation of IEHSs. This paper proposes a joint energy and reserve dispatch model for IEHSs based on transactive energy, which is a coordinated combination of a bi-level Stackelberg game and two-stage robust optimization. The bi-level Stackelberg game is used to realize the equilibrium of interests among three transacting parties, namely, integrated energy service provider (IESP), multi-carrier prosumer (MCP), and load aggregator (LA). The two-stage robust optimization is employed to ensure the reliability of the system operation under renewable energy uncertainty. In the upper level of the Stackelberg game, the IESP perform pricing and reserve dispatch, while the MCP and LA maximize their benefits via energy management in the lower level. Linearization techniques are utilized to approximate the bi-level Stackelberg game model into a single-level mixed-integer linear programming problem. The converted single-level game model is subsequently regarded as the first stage, while the real-time feasibility check is regarded as the second stage to form a two-stage robust optimization model, which is solved by a modified C&CG algorithm. Case studies demonstrate that the proposed joint energy and reserve dispatch method effectively achieves economic and reliable operation. INDEX TERMS Integrated electric-heat system, transactive energy, joint energy and reserve dispatch, Stackelberg game, two-stage robust optimization.

A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective

“…For example, a nucleolus-based cooperative game solution is proposed in [317] that utilized the flexible loads of prosumers and considers the uncertainties of renewable energy resources to manage energy in local communities. A Stackelberg game is used to develop a joint energy and reserve dispatch model in [318] to ensure the reliability of system operation under renewable energy uncertainty. To maximize the benefit of distributed energy resources for flexible prosumers in terms of procuring revenues by trading electricity in the market, the authors in [319] and [320] explore algorithmic and non-cooperative games respectively to realize suitable transactive energy frameworks.…”

Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

“…The worst-case realization of the uncertainty of real-time electricity market prices was modeled in the second stage of an ARO in [1]. Finally, [94], [98] are the papers in this second category that use C&CG to deal with the uncertainties.…”

Transactive energy management systems: Mathematical models and formulations

“…The optimal bidding strategy of an EH considering the uncertainties from renewable energy resources, DA market price, and RT market price was modelled in [127]. The TEF for the scheduling and trading operations of coupled electric and thermal systems was discussed in [128][129][130]. Further research on the modelling of P2P energy trading among EHs can be found in [131,132].…”