Abstract
In the researching background of integrated energy system, a single electricity-gas-heating system (EGHS) can be regarded as an active producer. In order to solve the joint optimization of integrated energy systems under the condition of incomplete information, this paper proposes a distributed optimal scheduling framework of EGHS. First, establish a coupling model of the interconnected EGHS, and perform strict second-order cone convexity of the complex natural gas flow model. Next, use the bus splitting method to realize the decoupling between different regions of the interconnected system, and employ the alternating direction multiplier method (ADMM) to solve the model. Then, construct two-region energy system (78-node grid +40-node gas grid +40-node heat grid) and three-region energy system (117-node grid +60 node gas grid +60-node heat grid) as simulation examples to verify the effectiveness of the distributed optimization framework. In the end, the algorithm solution process, the effectiveness of scheduling results, and the comparison of optimization results under different interconnection methods are analyzed in detail.
Highlights
With the further advancement of the reform of energy industrialization, the energy internet has received increasing attention and researches [1]–[4]
The continuous development of gas-fired power generation, power-to-gas (P2G) technology and combined heat-power (CHP) technology has transformed the construction of the integrated electricity-gas-heat energy system (EGHS) from theory to reality [8], [9]
CASE STUDIES In this paper, two regions and three regions are used as simulation examples respectively to verify the validity of the proposed distributed optimal scheduling framework for interconnected electricity-gas-heating system (EGHS)
Summary
With the further advancement of the reform of energy industrialization, the energy internet has received increasing attention and researches [1]–[4]. Most researches on the optimal dispatch of integrated energy systems focus on internally regional optimization, that is, the coordination and complementation of electric energy, natural gas energy and thermal energy in a single zone [10]–[13]. Reference [10] proposes an improved sequential energy flow analysis method to solve the optimal energy flow of electrical interconnection system. The optimization of the stochastic day-ahead scheduling of electric power systems with natural gas transmission constraints. The ADMM algorithm is an important method for solving separable convex optimization problems It has the advantages of wide adaptability and fast convergence speed, which is more in line with the requirements of distributed computing in integrated energy systems. The research focus of this paper is to construct interconnected EGHS distributed scheduling framework. P2g, node and gas storage tank, node and CHP, node and gas unit and node and pipeline; fg,t , fP2G,t , fCHP,t , fGT,t , fD,t are gas source output vector, P2G gas injection vector, CHP gas injection vector, gas flow injection vector and gas load vector
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
