CN-121984032-A - Jackal optimized driving regional energy system double-layer low-carbon planning method, system, equipment and medium

CN121984032ACN 121984032 ACN121984032 ACN 121984032ACN-121984032-A

Abstract

The invention discloses a jackal optimization driving regional energy system double-layer low-carbon planning method, a jackal optimization driving regional energy system double-layer low-carbon planning system, jackal optimization driving regional energy system double-layer low-carbon planning equipment and a jackal optimization driving medium, and belongs to the technical field of low-carbon planning and operation optimization of regional comprehensive energy systems. The invention realizes the minimization of comprehensive cost in whole life cycle, improves the synergy of flexible load and energy balance, integrates and optimizes carbon emission and economic cost, and dynamically adapts capacity allocation and operation scheduling.

Inventors

WANG BIN
WANG WEI
LUO NING
ZHU YONGQING
WANG YUXIANG
YIN JIA
LIN CHAO
CHEN JULONG
ZHANG YU
MOU XUEPENG
YANG SHIPING
LUO CHEN
WANG CE
HU BIN
TANG XUEYONG

Assignees

贵州电网有限责任公司

Dates

Publication Date: 20260505
Application Date: 20251128

Claims (10)

1. The jackal optimizing and driving regional energy system double-layer low-carbon planning method is characterized by comprising the following steps of, Constructing an objective function of the energy system, and comprehensively covering all links of the energy system; Setting constraint conditions, and planning the capacity of an upper energy system through jackal optimization algorithm; and under the condition of considering flexible load and energy balance constraint, carrying out optimal scheduling of the power of the equipment.
2. The jackal energy system double-layer low-carbon planning method of optimal driving area energy system as claimed in claim 1, wherein the objective function of constructing the energy system comprises, Acquiring the capacity, the electric energy storage capacity and the thermal energy storage capacity of an upper thermal power coal-fired unit; Constructing an objective function with minimum comprehensive cost; The comprehensive cost covers all links of energy production, transmission, storage and carbon emission.
3. The method for double-layer low-carbon planning of the jackal energy system optimally driven by the method of claim 2, wherein the objective function of constructing the energy system comprises, Calculating operation and maintenance cost through operation and maintenance cost of renewable energy equipment; calculating fuel cost through natural gas consumption cost of the gas turbine and the gas boiler; And calculating the interaction cost of the power grid through the electricity purchasing cost and the electricity selling benefits.
4. The jackfruit optimized driving regional energy system double-layer low-carbon planning method of claim 3, wherein the comprehensive covering energy system whole link comprises, Calculating energy storage cost through electric energy storage and thermal energy storage charging and discharging energy loss cost; Calculating the demand response compensation cost through user compensation including load translation, transfer and reduction; calculating a carbon trade cost by segment pricing based on the carbon emissions; the construction cost is obtained.
5. The method for double-layer low-carbon planning of the jackal energy system optimally driven by the jackal energy system of claim 4, wherein the set constraint conditions comprise an electric energy storage constraint and a thermal power output constraint; The electric energy storage constraint comprises capacity constraint, state update and mutual exclusion of charge and discharge; the capacity constraint is: the state update is: The mutual exclusion of charge and discharge is as follows: Wherein, the In order to store the remaining capacity of the energy, And Respectively the minimum value and the maximum value of the residual capacity of the stored energy, In order to be self-damaged, In order to achieve the efficiency of the charge, In order for the discharge efficiency to be high, In order for the charging power to be high, For the power of the discharge it is, For a state of charge, 1 or 0,1 represents charge; in a discharge state, 1 or 0,1 represents discharge; the thermal power output constraint comprises a maximum output limit and a climbing constraint; The maximum force limit is: The climbing constraint is as follows: Wherein, the Is the maximum output of the thermal power coal-fired unit, The climbing rate of the thermal power coal-fired unit is achieved.
6. The method for bi-layer low-carbon planning of the jackal energy system optimally driven by claim 5, wherein the set constraint conditions further comprise a power balance constraint and a heat balance constraint; The power balance constraint is an electric balance constraint Wherein, the In order to interchange the power with the grid, As a basic electric load, delta P (t) is a demand response adjustment electric load quantity comprising translation, transfer and reduction; The thermal equilibrium constraint is: Wherein, the The power is charged for the thermal energy storage, For the thermal energy storage discharge power, As a basis for the thermal load of the heat, The amount of heat load is adjusted for demand response.
7. The jackal energy system double-layer low-carbon planning method for optimizing the driving area energy system according to claim 6, wherein the jackal optimization algorithm comprises optimizing the capacities, the electric energy storage capacities and the thermal energy storage capacities of the thermal power coal-fired unit based on the jackal optimization algorithm; Initializing search parameters, namely setting the number of search individuals, the maximum iteration times and variable dimensions, and defining upper and lower boundaries of variables; initializing and evaluating fitness of each individual, namely transmitting the current upper limit value to a lower layer optimization model as hard constraint by using a maximum capacity scheme of electric energy storage and thermal energy storage of each individual as a thermal power generating unit, and taking the total running cost of a system returned by the lower layer as a fitness value of the current individual; Executing a jackal optimization algorithm behavior mechanism, and updating a search position based on search behaviors, surrounding behaviors and attack behaviors; If the convergence condition is met or the maximum algebra is reached, outputting an optimal upper limit of output, otherwise, re-executing the jackal optimization algorithm behavior mechanism to continue iteration, wherein the current result is used as the upper limit constraint of thermal power output in the lower-layer optimization model to limit the carbon discharge; Under the upper constraint, the system running cost is minimized by using a solver, the upper optimal thermal power coal-fired unit, the electric energy storage and the thermal energy storage optimization result are input, the residual prediction data are input at the same time, and an objective function is constructed: and setting constraint conditions, solving by using a gurobi solver, and transmitting the optimal cost obtained by the solver to the upper layer optimization as a fitness value.
8. The jackal-optimized-driving regional energy system double-layer low-carbon planning system is applied to the jackal-optimized-driving regional energy system double-layer low-carbon planning method according to any one of claims 1-7, and is characterized by comprising a target construction module and a planning module; the target construction module is used for constructing a target function of the energy system and comprehensively covering all links of the energy system; The system comprises a planning module, a power supply module and a power supply module, wherein the planning module is used for setting constraint conditions, planning the capacity of an upper energy system through a jackal optimization algorithm, and carrying out optimal scheduling of equipment power under the condition of considering flexible load and energy balance constraint.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the jackal optimized drive regional energy system double-layer low-carbon planning method of any one of claims 1 to 7.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, carries out the steps of the jackal energy system double-layer low-carbon planning method of the optimized drive of any one of claims 1 to 7.

Description

Jackal optimized driving regional energy system double-layer low-carbon planning method, system, equipment and medium Technical Field The invention relates to the technical field of low-carbon planning and operation optimization of regional comprehensive energy systems, in particular to a jackal optimization driving regional energy system double-layer low-carbon planning method, system, equipment and medium. Background Along with the increasing severity of global energy crisis and environmental problems, a comprehensive energy system (comprising renewable energy sources such as photovoltaic, wind power and the like, traditional energy sources such as thermal power, gas turbines and the like, and equipment such as electric energy storage, thermal energy storage and the like) becomes a core carrier for realizing energy efficient utilization and low-carbon transformation. The core aim is to balance the economical efficiency and the environmental protection of the full chain of energy production, transmission, storage and consumption through the multi-energy collaborative optimization. Currently, optimal scheduling of integrated energy systems mainly relies on mathematical modeling and intelligent algorithms. Conventional approaches mostly employ a single optimization objective (e.g., consider only running cost minimization), or deal with multi-objective problems by simple weighting. Meanwhile, as the duty ratio of the flexible load (such as translatable and reducible electric/thermal load) on the user side increases, how to incorporate its adjustment potential in the scheduling to increase the flexibility of the system becomes a problem to be solved. In the aspect of optimization algorithm, the prior art mostly adopts traditional intelligent algorithms such as Particle Swarm Optimization (PSO), genetic Algorithm (GA) and the like, or simply relies on a commercial solver (such as Gurobi) to carry out mathematical programming. However, when the traditional intelligent algorithm is used for processing a complex system with high dimensionality and multiple constraints (such as energy balance and equipment output limit), the complex system is easy to be in local optimum, so that the scheduling scheme is insufficient in economy, but a method which simply depends on a solver is difficult to deal with a large-scale variable optimization problem, and efficiency bottlenecks exist in collaborative optimization of capacity configuration and operation scheduling. In addition, the gradual perfection of the carbon transaction mechanism requires that the energy system optimization must quantify the carbon emission cost, but the existing model mostly takes the carbon emission as an additional constraint, and does not form an integrated optimization framework with the economic cost, so that the decision result is difficult to consider the environmental protection and the economic targets. Disclosure of Invention The present invention has been made in view of the above-described problems. Therefore, the invention aims to realize the low-carbon and economical collaborative optimization of the regional energy system by a double-layer planning method based on a jackal optimization algorithm. In order to solve the technical problems, the invention provides the following technical proposal that the jackal optimization driving regional energy system double-layer low-carbon planning method comprises the following steps, The method comprises the steps of constructing an objective function of an energy system, comprehensively covering all links of the energy system, setting constraint conditions, planning the capacity of the upper energy system through jackal optimization algorithm, and carrying out optimal scheduling of equipment power under the condition of considering flexible load and energy balance constraint. As a preferable scheme of the jackal optimized driving regional energy system double-layer low-carbon planning method, the objective function for constructing the energy system comprises, Acquiring the capacity, the electric energy storage capacity and the thermal energy storage capacity of an upper thermal power coal-fired unit; Constructing an objective function with minimum comprehensive cost; The comprehensive cost covers all links of energy production, transmission, storage and carbon emission. As a preferable scheme of the jackal optimized driving regional energy system double-layer low-carbon planning method, the objective function for constructing the energy system comprises, Calculating operation and maintenance cost through operation and maintenance cost of renewable energy equipment; calculating fuel cost through natural gas consumption cost of the gas turbine and the gas boiler; And calculating the interaction cost of the power grid through the electricity purchasing cost and the electricity selling benefits. As a preferable scheme of the jackal energy system double-layer low-carbon planning method for optimizing d