Abstract
The increasing adoption of gas-fired power plants directly strengthens the coupling between electric power and natural gas systems. Current industrial practice in optimal power flow for electric power systems has not taken the security constraints of gas systems into consideration, resulting in an overly-optimistic solution. Meanwhile, the operation of electric power and natural gas systems is coupled over multiple periods because of the ramp rate limits of power generators and the slow dynamical characteristics of gas systems. Based on these motivations, we propose a multi-period integrated natural gas and electric power system probabilistic optimal power flow (M-GEPOPF) model, which includes dynamic gas flow models. To address the uncertainties originating from wind power and load forecasting, a probabilistic optimal power flow (POPF) calculation based on a three-point estimate method (3PEM) is adopted. Moreover, power-to-gas (PtG) units are employed to avoid wind power curtailment and enable flexible bi-directional energy flows between the coupled energy systems. An integrated IEEE RTS 24-bus electric power system and the Belgian 20-node natural gas system are employed as a test case to verify the applicability of the proposed M-GEPOPF model, and to demonstrate the potential economic benefits of PtG units.
Highlights
With the longstanding large-scale exploitation and utilization of fossil fuels, the world is facing the formidable challenges of energy resource depletion and heavy pollution emissions
2) To address wind power uncertainty, POPF based on a three-point estimation method (3PEM) is introduced, which, in conjunction with the M-GEOPF model, yields a multi-period gas and electric system probabilistic optimal power flow (M-GEPOPF) model
This paper proposed an M-GEPOPF model incorporating PtG units
Summary
With the longstanding large-scale exploitation and utilization of fossil fuels, the world is facing the formidable challenges of energy resource depletion and heavy pollution emissions. The performance of the obtained solution was found to depend largely on the selected scenario In this regard, probabilistic optimal power flow (POPF) is a powerful tool for accommodating uncertainties that can yield the statistics of output variables according to the distributions of input variables [18, 19]. Based on the above discussion, the primary contributions of the present work are as follows: 1) A M-GEOPF model incorporating PtG units is formulated based on precise nonlinear power and gas flow models, where the dynamical characteristics of the gas network are modeled. 2) To address wind power uncertainty, POPF based on a three-point estimation method (3PEM) is introduced, which, in conjunction with the M-GEOPF model, yields a multi-period gas and electric system probabilistic optimal power flow (M-GEPOPF) model.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
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 call
