Abstract
With the joint optimization of the electricity–gas–heating system (EGHS) attracting more and more attention, a distributed optimized scheduling framework for EGHS based on an improved alternating direction method of multipliers (ADMM) algorithm is put forward in this paper. The framework of the proposed algorithm is a co-ordinated convex distribution framework with inner and outer layers. The outer layer is a penalty convex–concave procedure (PCCP), the inner layer is an ADMM-FE (forced equality) procedure. In this framework, the outer layer optimization uses the convex and concave procedure to turn the non-convex airflow equation into a second-order cone constraint with successive iterations, and the inner layer ADMM-FE algorithm solves the convex model to obtain a convergent solution. In the end, we compare the established algorithm with the traditional ADMM algorithm and the centralized optimization algorithm through example simulation analysis, and the results verify the effectiveness of the proposed model and optimization algorithm framework.
Highlights
With the further advancement of the industrialization reform of the energy industry, the energy internet has received increasing attention and research
Integrated energy systems (IES) that include gas units, gas to power (P2G) equipment, and combined heat and power (CHP) equipment break the barriers to exchange between different forms of energy
In the open electricity market environment, the electricity supplier, gas supplier, and heating supplier in the electric heat interconnection system generally belong to different suppliers, it is important to ensure the privacy of the information in the co-ordinated operation, so data needs to be protected [5,6]
Summary
With the further advancement of the industrialization reform of the energy industry, the energy internet has received increasing attention and research. A robust co-optimization scheduling model was proposed to study the co-ordinated optimal operation of electricity–gas systems, and the optimization problem of the model was solved by the alternating direction method of multipliers [8]. A day-ahead scheduling optimization model of the electricity–gas–heating system (EGHS), considering heating system and most are lacking consideration of network dynamic characteristics. The dynamic characteristics of the network in order to tap the potential of complementary advantages this paper builds a day-ahead scheduling optimization model of the electricity–gas–heating system between energy (EGHS),different considering theflows. A convex relaxationmethods approach proposed achieve other hand, in the existing research, the optimization of was the IES system to mostly the co-ordinated operation of electricity naturalrelaxation gas systems [10].
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