Research on Critical Peak Price Decision Optimization Considering Industrial Consumer’s Risk Appetite under the Carbon Neutrality Goal

Abstract

The existing research on critical peak price (CPP) decision-making ignores the difference in risk appetite between industries within the consumer population, resulting in a serious lag in the enthusiasm of some users to respond to CPP, and unsatisfactory improvement of power systems and carbon emission reduction on the supply and demand side. Firstly, the problem of consumer risk appetite was comprehensively analyzed, and the industrial consumer population was secondarily stratified according to the influencing factors and the enthusiasm of responding to CPP, namely: stubborn, active and conformist, and quantitatively verified by cluster analysis. Secondly, by combing the relevant paths of CPP decision-making, the critical-peak window determination model and CPP multi-objective optimization model were constructed, and the calculation of relevant indicators was introduced. Finally, taking 10 industrial enterprises in a city in Sichuan Province as an example, the clustering method was used to verify the stratification results, and the index analysis method was used to measure the load and carbon emission improvement of two typical enterprises after CPP optimization. The results showed that the stubborn users insist on using electricity, the improvement effect of load and carbon emission reduction was poor, and additional production costs will be caused. The conformist and active users had high sensitivity to electricity price fluctuations, good load and carbon emission reduction improvement effects, and significantly reduced electricity costs.

Grid Investment’s Impact on Transmission and Distribution Tariffs Considering Carbon Costs

“…While extensive research has been conducted by Chinese scholars on the relationship between power grid investment and transmission and distribution tariffs, there is a noticeable gap in the literature regarding the influence of power grid investment on transmission and distribution tariffs when factoring in carbon costs [8][9]. Building upon the 2020 version of the transmission and distribution tariff pricing method, this paper analyzes the impact of power grid investments on transmission and distribution tariff pricing by incorporating carbon costs throughout the cost analysis using the full life cycle theory.…”

Double-layer optimization model for integrated energy system under multiple robustness

“…To address the problem of collaborative dispatching of integrated regional energy systems taking into account the uncertainty of new energy output, Lv [ 8 ] developed a regional integrated energy system optimal dispatching model considering integrated demand response, which improves the wind power consumption capacity of the system; Yan [ 9 ] developed a three-level, two-stage regional integrated energy system robust optimization model to accommodate stochastic disruptions in natural gas and power generation and transmission systems caused by extreme weather; Qi [ 10 ] solved the uncertainties associated with variable wind and solar power diffusion and load forecasting errors in a chance constrained programming framework; Gao [ 11 ] developed an integrated power/gas/heat system optimal dispatch model; Saberi Hossein et al [ 12 ] presents a novel probabilistic model for explicitly quantifying the VESS capacity in charging and discharging modes, which can further be optimized by scheduling building loads; Liu Shuqi [ 13 ] proposed a regional integrated energy bi-level optimization model considering energy storage; Yao Zhaosheng et al [ 14 ] develops a multi-objective robust optimization framework that accounts for the benefits of multiple parties of smart charging and discharging systems and depicts a bounded uncertainty set based on partial statistical information from real data; Cesena Eduardo Alejandro Martinez and Mancarella Pierluigi [ 15 ] proposed a robust operational optimization framework for smart districts with multi-energy devices and integrated energy networks; Zhang Tao [ 16 ] established a multi-objective optimal dispatch model considering operation cost, carbon emission, and energy utilization efficiency by using the flexible characteristics of the regional integrated energy system; Yu Xiaobao [ 17 ] constructed the critical-peak window determination model and CPP multi-objective optimization model, combing the relevant paths of CPP decision-making; Qiu Zhi [ 18 ] established a bi-level model based on particle swarm optimization to cope with renewable energy uncertainty and energy price fluctuations. However, the stochastic rule approach presupposes accurate probability distribution information of the uncertainty factor, and the computation scale is huge and the random variables require complete distribution characteristics.…”

Study on Dynamic Pricing Strategy for Industrial Power Users Considering Demand Response Differences in Master–Slave Game

“…Refs. [15,16] construct a mathematical model based on timeof-use pricing that reflects the elasticity of electricity consumption by electricity consumers regarding the price of electricity demand. Ref.…”