Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets

The paradigm of the regional integrated energy system (RIES) with internal energy sharing, consisting of mul-tiple geographically adjacent and interconnected multi-energy microgrids (MEMGs), is considered a strategic effort to empower low-carbon energy systems. However, various operational uncertainties and electricity market transaction rules pose challenges to fulfilling the functionalities and economic promises of RIES. This paper presents a collaborative energy management strategy for RIES based on the market rules, which is formulated as a three-phase structure (i.e., day-ahead bidding, real-time dispatch and revenue allocation) and integrates multiple time scales to support electricity settlement and fine-grained energy dispatch. The day-ahead bidding model is developed based on the hybrid stochastic and chance-constrained programming that can comprehen-sively address multiple uncertainties introduced by the electricity market, distributed renewable generation and multi-energy loads to decide the optimal bidding electricity. The actual operation decisions can be determined in the rolling model predictive control based real-time dispatch phase in coordination with the day-ahead bidding electricity. The revenue from energy sharing is fairly allocated to each MEMG based on Nash bargaining theory to stabilize the incentive for MEMGs to engage in collaboration. The effectiveness of the proposed solution is extensively assessed through numerical simulations in the Guangdong electricity market.

Automated summary

This paper presents a collaborative energy management strategy for the regional integrated energy system (RIES) to address operational uncertainties and electricity market transaction rules.