CN-121097842-B - Optimal control method and system for carbon emission of electric power system

CN121097842BCN 121097842 BCN121097842 BCN 121097842BCN-121097842-B

Abstract

The invention provides an optimization control method and system for carbon emission of an electric power system, which relate to the technical field of carbon emission optimization control, and the method comprises the steps of collecting real-time load, power grid carbon emission factors and time-of-use electricity price, automatically dividing electricity utilization periods by adopting a clustering algorithm, modeling dynamic changes of the carbon emission factors in time-of-use periods, optimizing energy storage charging and discharging paths by using the principles of discharging in peak periods, smoothing and charging in valley periods, and incorporating energy loss and the health state of an energy storage unit in the charging and discharging process into carbon emission accounting; meanwhile, a multi-objective collaborative optimization model is built, and balance optimization of total carbon emission and electricity consumption cost is achieved, so that time sequence characteristics of actual production load and power grid carbon emission factors are accurately matched, accuracy of carbon emission collection and scheduling optimization level are improved, and carbon emission and energy consumption cost in a production period is effectively reduced.

Inventors

LI YUANXIA
WANG PENG
LIU BIN
CHEN JIANDONG
DUAN YAQIONG

Assignees

国网甘肃省电力公司临夏供电公司

Dates

Publication Date: 20260505
Application Date: 20251027

Claims (8)

1. The optimal control method for the carbon emission of the electric power system is characterized by comprising the following specific steps of: S1, collecting power load of a power system, real-time carbon emission factors of a power grid and time-sharing electricity price, and dividing the power utilization period of the power system into a peak period, a flat peak period and a valley period based on the power load; S2, respectively generating fluctuation curves of carbon emission factors changing with time in different time periods based on the real-time carbon emission factors of the power grid and the power utilization period of the power system; S3, setting an energy storage charging and discharging strategy of 'charging in a flat period and in a valley period and discharging in a peak period' for the power system, jointly calibrating the flat period and the valley period as charging periods, dividing the charging periods into a plurality of groups of subintervals, and distributing charging power with the carbon emission of the minimum charging period as a target to realize the optimization of a charging path; S4, constructing an equivalent carbon emission model under the participation of charge and discharge, correcting the equivalent carbon emission model according to the loss of the electric power system, and calculating the total carbon emission and the total electricity cost in a production period; The equivalent carbon emission model under the participation of energy storage is expressed as: In the middle of Indicating the total amount of carbon emissions that has not been corrected, 、 Respectively represent The power load and the charge-discharge power of the power system at the moment, The time of this is indicative of the charging, The time of this is indicative of the discharge, Representing the total time of one production cycle, Represents the average carbon emission factor of the charging period, Representation of The discharge power at the moment of time is, Representation of The carbon emission factor at the moment of time, A functional expression representing the carbon emission factor during peak hours; In the middle of Represent the first The carbon emission factor at the start of the subinterval, Represent the first Starting time of subinterval, subscript An index representing a subinterval; The loss of the power system comprises power loss and equipment loss, the charge and discharge power is corrected based on the power loss, and the corrected charge and discharge power is expressed as: In the middle of Indicating the charge-discharge power after the correction, Representation of The charging power at the moment of time is, 、 Respectively representing charging efficiency and discharging efficiency; Substituting the corrected charge and discharge power into an equivalent carbon emission model to replace the original charge and discharge power, so as to finish the primary correction of the equivalent carbon emission model; the equipment loss is the health state of an energy storage unit in the power system; the health state is quantified by monitoring the capacity change of the energy storage unit in real time, and the expression is as follows: In the middle of 、 Respectively represent the energy storage units in State of health at time and real-time capacity, Representing the maximum capacity of the energy storage unit; The implicit carbon emission coefficient during charge and discharge is constructed based on the health state of the energy storage unit, and the expression is as follows: In the middle of Representation of The implicit carbon emission coefficient at the moment, 、 Respectively representing a preset reference value and a preset regulating factor of the implicit carbon emission coefficient; and then the recessive carbon emission coefficient is introduced into the equivalent carbon emission model to finish the final correction of the equivalent carbon emission model, and the expression of the corrected equivalent carbon emission model is as follows: In the middle of Indicating the total amount of carbon emissions after the correction is completed, Representing the total carbon emission after the initial correction; And S5, constructing a multi-objective collaborative optimization function, weighting the total carbon emission and the total electricity cost, dynamically optimizing the charge and discharge power of the power system through an optimization algorithm, and realizing collaborative minimization of the carbon emission and the total electricity cost of the factory.
2. The method for optimizing and controlling carbon emission of an electric power system according to claim 1, wherein the electric power system is a load end of an electric network; Logic for generating a fluctuation curve of carbon emission factors over time at different time periods is: When the electricity utilization period of the power system is divided, a clustering statistical algorithm is adopted, the electricity utilization loads are automatically grouped according to the load level and the duration, so that the time division of peak, flat peak and valley periods is formed, and the time division is calibrated as follows in sequence 、、 ; Respectively carrying out statistics and fitting on fluctuation curves of carbon emission factors changing along with time in peak period, flat peak period and low valley period, and respectively generating functional expressions of the carbon emission factors in each period: In the middle of 、 And respectively representing the functional expression of the carbon emission factor in the flat peak period and the low valley period.
3. The method for optimizing control of carbon emission of an electric power system according to claim 1, wherein the electric power system comprises an energy storage unit for charging and discharging, and the specific logic of the energy storage charging and discharging strategy is as follows: when the electricity utilization period of the electric power system is in a peak period and a valley period, charging power is distributed by taking carbon emission of a minimum charging period as a target, and the energy storage unit of the electric power system is charged from a power grid; And when the electricity utilization period of the power system is a peak period, discharging electricity from the energy storage unit to the power system so as to reduce the load of the power grid.
4. The method for optimizing control of carbon emission in an electric power system according to claim 1, wherein the logic for optimizing the charging path is: Evenly dividing the charging period into the following steps according to the preset time slices A subinterval, and acquiring a carbon emission factor of the starting moment of each subinterval; Taking the charging power at the starting moment of each subinterval as a decision variable, taking the carbon emission in the minimized charging period as an optimization target, taking the energy balance and the charging power as constraints, and carrying out optimization adjustment on the charging power in each subinterval; And generating a charging power distribution sequence based on a linear programming solving algorithm, preferentially distributing the charging power to the interval with the lowest carbon emission factor, and if the residual exists, increasing the charging power to the next low-carbon interval until the charging target is met.
5. The method for optimizing control of carbon emissions in an electrical power system according to claim 4, wherein the expression of the objective function when carbon emissions during the minimized charging period are used as the optimization target is: In the middle of Represent the first The charging power at the start of each subinterval, Representing the duration of the subinterval; When the total energy of charging in the charging period is greater than or equal to the target energy, the charging target is considered to be satisfied, and the corresponding energy balance constraint expression is: In the middle of Representing a target energy; The expression of the charging power constraint is: In the middle of Indicating the maximum charge power allowed.
6. The method for optimizing control of carbon emission in an electric power system according to claim 5, wherein the total electricity consumption cost is calculated by: In the middle of Representation of Time-of-use electricity prices at time.
7. The method for optimizing control of carbon emission in an electric power system according to claim 6, wherein the expression of the multi-objective collaborative optimization function is: In the middle of A function score representing the multi-objective co-optimization function, 、 The two are respectively represented by weight coefficients, and the sizes of the two are determined according to the optimization requirement; function score by objective collaborative optimization function Minimization is an optimization objective by which a synergistic minimization of carbon emissions and total cost of electricity is achieved, wherein the optimization algorithms include, but are not limited to, dynamic planning, linear planning, and genetic algorithms.
8. The optimizing control system for the carbon emission of the electric power system is characterized in that the optimizing control system is used for executing the optimizing control method according to any one of claims 1 to 7, and specifically comprises the following steps: the data acquisition module is used for acquiring the power load of the power system, the real-time carbon emission factor of the power grid and the time-sharing electricity price; The data analysis module is used for dividing the electricity utilization period of the power system into a peak period, a flat peak period and a valley period; the data fitting module is used for generating a fluctuation curve of the carbon emission factor changing along with time in different time periods and fitting out a function expression of the carbon emission factor in each time period; the power detection module is used for detecting the charge and discharge power and the health state of the energy storage unit in real time; the model construction module is used for constructing an equivalent carbon emission model under the participation of charge and discharge and correcting the equivalent carbon emission model according to the loss of the power system; and the power optimization module is used for constructing a multi-objective collaborative optimization function, weighting the total carbon emission amount and the total electricity consumption cost, and dynamically optimizing the charge and discharge power of the energy storage unit in the power system through an optimization algorithm.

Description

Optimal control method and system for carbon emission of electric power system Technical Field The invention relates to the technical field of carbon emission optimization control, in particular to an optimization control method and system for carbon emission of an electric power system. Background With large energy consumption scenes such as factories, parks and the like, higher requirements are put on low-carbon optimized scheduling of a power system. In the prior art, an energy storage scheduling strategy based on time-of-use electricity price or fixed time period is generally adopted, and dynamic changes of industrial loads, production process differences and real-time fluctuation of power grid carbon emission factors cannot be fully considered, so that carbon emission optimization effect is limited. Meanwhile, part of schemes cannot effectively combine the energy loss and the equipment health state of the whole process of the energy storage system in carbon footprint accounting and energy scheduling, so that the problems of inaccurate carbon emission collection, low emission reduction, high deficiency and the like are easily caused, and the requirements of enterprises on the aspects of carbon verification, carbon asset management, green manufacturing and the like are difficult to meet. In the prior art, publication number CN117728508A discloses an optimization control method and device for carbon emission of a power system, which comprise the steps of solving a pre-built optimization model for carbon emission of the power system to obtain an optimization result, and obtaining an optimization control scheme for carbon emission of the power system based on the optimization result, wherein the optimization result comprises at least one of power generation carbon emission of various units, start-stop carbon emission of various units, output of various units, start-up quantity of thermal power units, start-up quantity of hydroelectric units and start-up running state of the thermal power units. According to the scheme, although the power generation mode of the optimal carbon emission of the whole network and the optimal carbon emission of the thermal power generating unit can be obtained, only the system carbon emission is minimized as a single target, the power output and the start-stop carbon emission optimization of the thermal power generating unit and the like are mainly aimed at, the factors such as dynamic partition of power loads, time variability of real-time carbon emission factors, energy 'time shift' and health state of an energy storage system are not considered, and the whole-flow refined carbon reduction and economic collaborative optimization are difficult to realize. The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art. Disclosure of Invention The invention aims to provide an optimal control method and system for carbon emission of an electric power system, so as to solve the problems in the background technology. In order to achieve the above purpose, the present invention provides the following technical solutions: The optimal control method for the carbon emission of the electric power system comprises the following specific steps: S1, collecting power load of a power system, real-time carbon emission factors of a power grid and time-sharing electricity price, and dividing the power utilization period of the power system into a peak period, a flat peak period and a valley period based on the power load; S2, respectively generating fluctuation curves of carbon emission factors changing with time in different time periods based on the real-time carbon emission factors of the power grid and the power utilization period of the power system; S3, setting an energy storage charging and discharging strategy of 'charging in a flat period and in a valley period and discharging in a peak period' for the power system, jointly calibrating the flat period and the valley period as charging periods, dividing the charging periods into a plurality of groups of subintervals, and distributing charging power with the carbon emission of the minimum charging period as a target to realize the optimization of a charging path; S4, constructing an equivalent carbon emission model under the participation of charge and discharge, correcting the equivalent carbon emission model according to the loss of the electric power system, and calculating the total carbon emission and the total electricity cost in a production period; And S5, constructing a multi-objective collaborative optimization function, weighting the total carbon emission and the total electricity cost, dynamically optimizing the charge and discharge power of the power system through an optimization algorithm, and realizing collaborative mi