A Novel Multi-Timescale Optimal Scheduling Model for a Power–Gas Mutual Transformation Virtual Power Plant with Power-to-Gas Conversion and Comprehensive Demand Response

Shuo Yin, Yang He, Zhiheng Li, Senmao Li, Peng Wang and Ziyi Chen ()
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Shuo Yin: State Grid Henan Electric Power Company Economic and Technological Research Institute, Zhengzhou 450052, China
Yang He: Henan Power Exchange Center, Zhengzhou 450003, China
Zhiheng Li: Henan Power Exchange Center, Zhengzhou 450003, China
Senmao Li: Henan Power Exchange Center, Zhengzhou 450003, China
Peng Wang: School of Electrical and Electronic Engineering, North China Electric Power University, Changping, Beijing 102206, China
Ziyi Chen: School of Electrical and Electronic Engineering, North China Electric Power University, Changping, Beijing 102206, China

Energies, 2024, vol. 17, issue 15, 1-19

Abstract: To optimize energy structure and efficiently utilize renewable energy sources, it is necessary to establish a new electrical power–gas mutual transformation virtual power plant that has low-carbon benefits. To promote the economic and low-carbon operation of a virtual power plant and reduce uncertainty regarding the use of new energy, a multi-timescale (day-ahead to intraday) optimal scheduling model is proposed. First, a basic model of a new interconnected power–gas virtual power plant (power-to-gas demand response virtual power plant, PD-VPP) was established with P2G and comprehensive demand response as the main body. Second, in response to the high volatility of new energy, a day-ahead to intraday multi-timescale collaborative operation optimization model is proposed. In the day-ahead optimization period, the next day’s internal electricity price is formulated, and the price-based demand response load is regulated in advance so as to ensure profit maximization for the virtual power plant. Based on the results of day-ahead modeling, intraday optimization was performed on the output of each distributed unit, considering the cost of the carbon emission reductions to achieve low-carbon economic dispatch with minimal operating costs. Finally, several operation scenarios are established for a simulation case analysis. The validity of the proposed model was verified via comparison.

Keywords: virtual power plant; power-to-gas transformation; demand response; multi-timescale (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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