CN110991733A - Inter-provincial peak regulation demand and peak regulation capacity evaluation analysis method for power system - Google Patents
Inter-provincial peak regulation demand and peak regulation capacity evaluation analysis method for power system Download PDFInfo
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Abstract
The invention discloses an inter-provincial peak regulation demand and peak regulation capability evaluation analysis method for an electric power system, belongs to the technical field of electric power system dispatching automation, and relates to an inter-provincial peak regulation demand and peak regulation capability evaluation analysis method considering power grid transmission section safety. According to the method, conventional constraints such as unit operation constraint, power grid safety constraint, unit group constraint, power generation and utilization balance constraint and the like are considered, constraints such as electric heat storage peak regulation, electric energy storage peak regulation, thermal power unit deep peak regulation, thermal power unit start-stop peak regulation, controllable load peak regulation, power generation and power plan peak regulation, new energy blocking and the like are introduced, the cross-provincial peak regulation requirement and the peak regulation capability under the condition of using up of intra-provincial peak regulation resources are analyzed by setting the priority of different components of an optimization target, effective elimination of new energy blocked power caused by intra-provincial network safety is achieved, and the effectively executable cross-provincial peak regulation requirement and the peak regulation capability are obtained.
Description
Technical Field
The invention belongs to the technical field of power system dispatching automation, and relates to an inter-provincial peak regulation demand and peak regulation capacity evaluation analysis method considering power grid transmission section safety.
Background
At present, the main reasons for increasing the peak-load regulation pressure of the domestic power grid include the factors of high thermal power installation occupation ratio, shortage of peak-load regulation resources, large-scale new-energy grid connection, gradual increase of load peak-valley difference and the like, wherein the main reasons are that the peak-load regulation resources of the power grid cannot meet the safe operation requirement of the large-scale new-energy grid connection, and the problems of wind abandonment and light abandonment are particularly prominent in the heating period in the three north areas in winter.
In order to relieve the peak regulation pressure of the power grid and promote the consumption of new energy, experts and scholars at home and abroad carry out deep research from the following aspects. 1) A multi-cycle coordinated optimization technique. Through multi-cycle coordinated optimization of medium-and-long-term unit combination, a day-ahead power generation plan, a day-in power generation plan and a real-time power generation plan, the refinement level of scheduling operation is improved, and the peak load regulation pressure of a power grid is relieved to the greatest extent. 2) A multi-source coordination optimization technology. The domestic expert scholars make a large amount of researches on the fast start-stop peak regulation of a gas-fuel oil unit, the water pumping peak regulation of a pumped storage power station, the peak regulation of a nuclear power unit, the deep peak regulation of a thermal power unit and the like, and the optimal configuration of various energy sources such as thermal power, hydropower, pumped storage, nuclear power and the like is realized by adopting a multi-source coordination optimization technology. 3) High-precision load prediction and new energy prediction technology. By adopting technical means such as big data analysis, deep learning, gridding prediction and the like, the system load and the new energy prediction precision are improved, and the execution force of the day-ahead and real-time power generation plan is improved.
The means relieves the peak load regulation pressure of the power grid to a great extent, but is mostly limited in provincial power grids, and for provincial/regional power grids rich in clean energy, the optimal configuration of the clean energy in the whole power grid is realized through inter-provincial transactions and cross-regional spot transactions. With the rapid development of a large alternating-current and direct-current hybrid power grid, inter-provincial transactions and cross-regional spot goods become daily means for promoting the consumption of clean energy in the whole network, however, the transaction amount of the inter-provincial transactions and the cross-regional spot goods transactions depends on the detailed analysis of provincial-level and regional power grid peak regulation requirements and peak regulation capabilities, and the prediction of the inter-provincial transaction capability and the transaction requirement is realized by the network-provincial two-level real-time transaction prediction coordination optimization method under the existing generalized tie line mode, which can also be called as the prediction of the inter-provincial peak regulation capability and the peak regulation requirement. In addition, the method considers the abandoned wind power quantity caused by the internal network security of the power grid, finely corrects the prediction result, is favorable for improving the intelligent level and decision-making capability of the cross-provincial real-time transaction, and achieves the ultimate goal of cross-provincial new energy consumption. However, the method has the problems that the provincial power grid is divided into the sub-control areas and the main control area according to different unit regulation authority limits, and the peak regulation requirements and the peak regulation capabilities of the main control area and the sub-control area are respectively predicted, so that although the coordinated operation of the sub-center and the provincial power grid is realized, the optimal peak regulation capability and the peak regulation requirements of the safe and stable operation of the power grid cannot be met by the angle analysis of the whole power grid; in addition, the air abandoning amount generated by network safety in the power grid and the main/sub control area transaction prediction are calculated separately, so that the coupling relation between the air abandoning amount and the main/sub control area transaction cannot be accurately controlled, and meanwhile, the inter-provincial transaction inevitably causes the change of the inter-provincial connecting line plan; moreover, the inter-provincial peak regulation requirement and the peak regulation capability guide inter-provincial transactions, which should not be frequently performed, and therefore, a new solution is urgently needed in the prior art to solve the above-mentioned problems.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a new technical scheme, which comprises the following steps:
an assessment and analysis method for inter-provincial peak regulation demand and peak regulation capability of an electric power system comprises the following steps,
s1, acquiring basic data of peak regulation influence factors of the power system, and establishing a peak regulation demand and peak regulation capability evaluation analysis scene, wherein the peak regulation influence factors comprise system load prediction, new energy prediction, maintenance plan, section quota, unit shutdown information, initial plan of a tie line, the limit of the tie line, adjustable output of the unit, economic parameters of the unit, sensitivity of the unit to monitoring elements, electric heat storage parameter information, electric energy storage parameter information, controllable load active power and thermal power depth peak regulation parameters;
s2, establishing a peak regulation demand and peak regulation capacity evaluation analysis model;
and S3, reading the basic data of the evaluation analysis scene in the step S1 from the peak regulation demand and peak regulation capacity analysis model constructed in the step S2, and performing safety check iterative calculation on the peak regulation demand and peak regulation capacity of the provincial power grid to obtain an optimal model of the peak regulation demand and the peak regulation capacity.
And S4, acquiring new energy limited penalty cost and electricity balance relaxation cost with different magnitudes, and obtaining an optimization target through the combination of the conventional energy unit output, the new energy unit output and the tie line plan.
In step S2, the peak shaving demand cost is determined by the following formula:
in the formula: fdThe required cost for peak regulation,
An initial plan for a tie line m period t; tau ism,tPlanning for a tie m period t;
the peak shaver capacity cost is determined by the following formula:
in the formula: fcCost for peak regulation capability,
An initial plan for a tie line m period t; tau ism,tTime period t plan for tie line m.
The optimal model in step S3 is obtained by:
determining that the power receiving plan is increased and the power receiving plan is decreased by the same provincial power grid at the same time, and the maximum of the optimization targets is equal to the minimum of the reverse targets:
thereby determining
The optimization target of the peak regulation demand and peak regulation capacity evaluation analysis model can adopt a unified expression:
wherein F is an optimization objective;
the optimized target expression after the new energy limited penalty cost and the distribution electric balance relaxation cost in the step S4 is as follows:
in the formula:
represents the time period tA power imbalance relaxation penalty cost function; deltaw,tAnd representing the w period t limited penalty cost of the new energy source unit.
The constraint conditions of the peak shaving demand and peak shaving capacity evaluation analysis model in the step S2 are determined by the following formula:
in the formula: p is a radical ofi,tOptimizing variables for the output of the unit in the period i and t; tau ism,tOptimizing variables for the plan of the tie line m time period t; p is a radical ofw,tA constant value is used for active prediction of a new energy unit in a w time period t; deltaw,tOptimizing variables for the blocked power of the new energy unit in the w time period t; rtReserving a spare system for a time period t; l istSystem load for time period t;
the issue charge for time period t balances the amount of forward and reverse relaxation, respectively.
And further constraining the peak regulation demand and the peak regulation capability evaluation analysis model by adding a connecting line plan component, wherein the expression is as follows:
in the formula:
d,tκrespectively representing forward and reverse power flow limits of the device d in a period t; sd,i,tRepresenting the sensitivity of the device d to the tie-line m for a period t; sd,m,tRepresenting the sensitivity of the device d to the unit i in the time period t; zetatRepresenting the load flow component over time period t.
The optimization goal in step S4 is represented as:
in the formula: f0Represents the peak shaver cost, which can be further expressed as:
in the formula: i represents the number of the depth peak shaving units and the starting peak shaving units; deltai,tRepresenting the depth peak regulation and start-up peak regulation cost of the conventional unit i time period t; b represents the number of electric energy storage units; deltab,tRepresenting the peak shaving cost of the period t of the electrical energy storage b; h represents the number of electric heat storages; deltah,tRepresenting the peak shaving cost of the electric heat accumulation h time period t; k represents the number of controllable loads; deltak,tRepresenting the peak shaver cost for the controllable load k period t.
The invention has the beneficial effects that: according to the method, conventional constraints such as unit operation constraint, power grid safety constraint, unit group constraint, power generation and utilization balance constraint and the like are considered, constraints such as electric heat storage peak regulation, electric energy storage peak regulation, thermal power unit deep peak regulation, thermal power unit start-stop peak regulation, controllable load peak regulation, power generation and power plan peak regulation, new energy blocking and the like are introduced, the cross-provincial peak regulation requirement and the peak regulation capability under the condition of using up of intra-provincial peak regulation resources are analyzed by setting the priority of different components of an optimization target, effective elimination of new energy blocked power caused by intra-provincial network safety is achieved, and the effectively executable cross-provincial peak regulation requirement and the peak regulation capability are obtained. In addition, the time span of cross-provincial peak regulation requirements and peak regulation capability evaluation analysis is hours in the future, and the invention solves and obtains an effective and executable inter-provincial peak regulation quantitative index by introducing an extremely-small and extremely-large optimization target and adopting an extremely-small and extremely-large linearization method, thereby providing technical support for cross-provincial peak regulation of each provincial power grid and promoting maximum consumption of new energy in the whole grid range.
Detailed Description
An assessment and analysis method for inter-provincial peak regulation demand and peak regulation capability of an electric power system comprises the following steps,
s1, acquiring basic data of peak regulation influence factors of the power system, and establishing a peak regulation demand and peak regulation capability evaluation analysis scene, wherein the peak regulation influence factors comprise system load prediction, new energy prediction, maintenance plan, section quota, unit shutdown information, initial plan of a tie line, the limit of the tie line, adjustable output of the unit, economic parameters of the unit, sensitivity of the unit to monitoring elements, electric heat storage parameter information, electric energy storage parameter information, controllable load active power and thermal power depth peak regulation parameters;
s2, establishing a peak regulation demand and peak regulation capacity evaluation analysis model;
and S3, reading the basic data of the evaluation analysis scene in the step S1 from the peak regulation demand and peak regulation capacity analysis model constructed in the step S2, and performing safety check iterative calculation on the peak regulation demand and peak regulation capacity of the provincial power grid to obtain an optimal model of the peak regulation demand and the peak regulation capacity.
And S4, acquiring new energy limited penalty cost and electricity balance relaxation cost with different magnitudes, and obtaining an optimization target through the combination of the conventional energy unit output, the new energy unit output and the tie line plan.
In step S2, the peak shaving demand cost is determined by the following formula:
in the formula: fdThe required cost for peak regulation,
An initial plan for a tie line m period t; tau ism,t is the plan of the tie line m time period t;
the peak shaver capacity cost is determined by the following formula:
in the formula: fcCost for peak regulation capability,
An initial plan for a tie line m period t; tau ism,tIs connected toAnd (4) planning the period t of the line m.
The optimal model in step S3 is obtained by:
determining that the power receiving plan is increased and the power receiving plan is decreased by the same provincial power grid at the same time, and the maximum of the optimization targets is equal to the minimum of the reverse targets:
thereby determining
The optimization target of the peak regulation demand and peak regulation capacity evaluation analysis model can adopt a unified expression:
the optimized target expression after the new energy limited penalty cost and the distribution electric balance relaxation cost in the step S4 is as follows:
in the formula:
representing a relaxation penalty cost function of the electricity utilization unbalance generated in the time period t; deltaw,tAnd representing the w period t limited penalty cost of the new energy source unit.
The constraint conditions of the peak shaving demand and peak shaving capacity evaluation analysis model in the step S2 are determined by the following formula:
in the formula: p is a radical ofi,tOptimizing variables for the output of the unit in the period i and t; tau ism,tOptimizing variables for the plan of the tie line m time period t; p is a radical ofw,tA constant value is used for active prediction of a new energy unit in a w time period t; deltaw,tOptimizing variables for the blocked power of the new energy unit in the w time period t; rtReserving a spare system for a time period t; l istSystem load for time period t;
the issue charge for time period t balances the amount of forward and reverse relaxation, respectively.
And further constraining the peak regulation demand and the peak regulation capability evaluation analysis model by adding a connecting line plan component, wherein the expression is as follows:
in the formula:
d,tκrespectively representing forward and reverse power flow limits of the device d in a period t; sd,i,tRepresenting the sensitivity of the device d to the tie-line m for a period t; sd,m,tRepresenting the sensitivity of the device d to the unit i in the time period t; zetatRepresenting the load flow component over time period t.
The optimization goal in step S4 is represented as:
in the formula: f0Represents the peak shaver cost, which can be further expressed as:
in the formula: i represents the number of the depth peak shaving units and the starting peak shaving units; deltai,tRepresenting the depth peak regulation and start-up peak regulation cost of the conventional unit i time period t; b represents the number of electric energy storage units; deltab,tRepresenting the peak shaving cost of the period t of the electrical energy storage b; h represents the number of electric heat storages; deltah,tRepresenting the peak shaving cost of the electric heat accumulation h time period t; k represents the number of controllable loads; deltak,tRepresenting the peak shaver cost for the controllable load k period t.
Examples
The inter-provincial peak regulation demand and peak regulation capacity evaluation analysis method considering the safety of the power transmission section of the power grid can be applied to different time periods such as the day ahead, the day in, real time and the like. The evaluation analysis of day-ahead peak regulation demand and peak regulation capacity is carried out according to basic data such as a next-day power grid operation mode, a unit operation state, day-ahead load prediction, day-ahead new energy prediction, a day-ahead overhaul plan, day-ahead section quota, a power receiving plan, a thermal power deep peak regulation parameter, an electric heat storage peak regulation parameter, controllable load active power, an electric energy storage peak regulation parameter and the like, under the conditions of comprehensively considering system balance constraint, unit operation constraint, new energy limitation constraint, network security constraint, unit group constraint, electric heat storage peak regulation constraint, electric energy storage peak regulation constraint, controllable load peak regulation constraint, thermal power unit deep peak regulation constraint and the like, a unit output plan, a tie line plan, provincial peak regulation demand or peak regulation capacity, different peak regulation resource peak regulation plans and the like at the granularity of 15 minutes on the next day are optimized and decided, and auxiliary decision is provided for day-ahead power generation plan compilation. The evaluation and analysis of the demand and the capacity of peak regulation in the daytime and in real time are similar to those before the day, but the optimization cycle is changed from the next day to hours in the future, so that auxiliary decisions are provided for the planning of the power generation in the daytime and in real time respectively.
S1, acquiring basic data of peak regulation influence factors of the power system, and establishing a peak regulation demand and peak regulation capability evaluation analysis scene, wherein the peak regulation influence factors comprise system load prediction, new energy prediction, maintenance plan, section quota, unit shutdown information, initial plan of a tie line, the limit of the tie line, adjustable output of the unit, economic parameters of the unit, sensitivity of the unit to monitoring elements, electric heat storage parameter information, electric energy storage parameter information, controllable load active power and thermal power depth peak regulation parameters;
s2, establishing a peak regulation demand and peak regulation capacity evaluation analysis model;
and S3, reading the basic data of the evaluation analysis scene in the step S1 from the peak regulation demand and peak regulation capacity analysis model constructed in the step S2, and performing safety check iterative calculation on the peak regulation demand and peak regulation capacity of the provincial power grid to obtain an optimal model of the peak regulation demand and the peak regulation capacity.
And S4, acquiring new energy limited penalty cost and electricity balance relaxation cost with different magnitudes, and obtaining an optimization target through the combination of the conventional energy unit output, the new energy unit output and the tie line plan.
The optimization objectives will first be explained in detail. The optimization target expression of the peak regulation demand evaluation analysis model considering the safety of the power transmission section of the power grid is as follows:
in the formula:
an initial plan for a tie line m period t; tau ism,tTime period t plan for tie line m. The power receiving plan takes the acceptance as positive, when the acceptance is reduced, the peak regulation requirement is represented, a minimum maximum target is introduced to calculate the minimum peak regulation requirement, the intra-provincial peak regulation capability is fully excavated, and the maximum requirement of the inter-provincial peak regulation in a period of time in the future is given.
The optimization target expression of the peak regulation capability evaluation analysis model considering the power transmission section safety of the power grid is as follows:
in the formula:
an initial plan for a tie line m period t; tau ism,tTime period t plan for tie line m. The power receiving plan (namely the tie-line plan) takes the acceptance as positive, when the acceptance is increased, the peak regulation capability is represented, the maximum minimum target is introduced to calculate the maximum peak regulation capability, and the minimum capability of the peak regulation in a time section in the future is given.
Since there is only one case at the same time for the same provincial power grid for the increase of the power plan and the decrease of the power plan, and the maximum of the optimization objectives is equal to the minimum of the objectives in the opposite direction:
therefore, the optimization target of the peak regulation demand and peak regulation capacity evaluation analysis model considering the safety of the power transmission section of the power grid can adopt a unified expression:
wherein F is an optimization objective;
therefore, the peak regulation requirement and the peak regulation capacity evaluation analysis model considering the safety of the power transmission section of the power grid realize the unification of optimization targets, and the peak regulation requirement and the peak regulation capacity can be analyzed by solving the same optimization model.
In order to analyze the effectively executable trans-provincial peak regulation demand and peak regulation capacity and eliminate the new energy limited power caused by the safety of the intra-provincial section, the new energy limited penalty cost and the electricity utilization balance relaxation cost with different magnitudes are further introduced into the evaluation and analysis optimization target of the peak regulation demand and the peak regulation capacity of the power transmission section safety of the power grid, and the trans-provincial peak regulation demand and the peak regulation capacity are optimized and analyzed through the combination of the conventional energy unit output, the new energy unit output and the tie line plan. The optimization target expression after introducing the new energy limited penalty cost and the distribution electric balance relaxation cost is as follows:
in the formula:
representing a relaxation penalty cost function of the electricity utilization unbalance generated in the time period t; deltaw,tAnd representing the w period t limited penalty cost of the new energy source unit. Because the optimization target consists of three parts, namely the daily peak regulation demand/capacity, the new energy limited penalty cost and the distribution electric balance relaxation penalty cost, the optimization model is multi-target optimization, and the priorities of different components of the optimization target have certain difference.
The optimization target three components are subjected to priority division according to the invention purpose, the electricity balance relaxation penalty cost is the highest, the new energy limited penalty cost is the second, the tie line variation weight is the lowest, and the tie line variation is the peak regulation demand or the peak regulation capacity. The relaxation cost of the electricity distribution balance is the highest, which indicates that the electricity distribution balance can not be realized through new energy limitation and tie line adjustment when the electricity distribution unbalance occurs, and the new energy limitation punishment is higher than the tie line variation, which indicates that the new energy limited quantity is caused by the safe operation of the provincial power grid, and the new energy limited power caused by the safety of the provincial section is successfully removed through the transprovincial peak regulation requirement.
Next, the peak regulation requirement considering the power transmission section safety of the power grid and the constraint conditions of the peak regulation capability evaluation analysis model are explained in detail, and the optimization target is further explained. The method considers the constraint conditions of deep peak regulation, electric heat storage peak regulation, electric energy storage peak regulation and the like of the thermal power generating unit, the start-stop peak regulation is embodied in the optimization target through the start-stop peak regulation cost, and the constraint conditions are still the traditional constraint conditions of minimum start-stop time, start-stop times and the like; the unit operation constraint, the unit group constraint and the new energy prediction power limitation are all existing constraints and are not described any more.
Although the reserved electricity balance constraint is a traditional constraint, the invention is changed, the electricity plan (i.e. the junctor plan) component is a variable, and the expression is as follows:
in the formula: p is a radical ofi,tOptimizing variables for the output of the unit in the period i and t; tau ism,tOptimizing variables for the plan of the tie line m time period t; p is a radical ofw,tA constant value is used for active prediction of a new energy unit in a w time period t; deltaw,tOptimizing variables for the blocked power of the new energy unit in the w time period t; rtReserving a spare system for a time period t; l istSystem load for time period t;
the issue charge for time period t balances the amount of forward and reverse relaxation, respectively.
Because the tie line plan is a variable, the traditional unit output is not used as a unique variable in the load flow calculation any more, and the tie line plan component is added, and the expression is as follows:
in the formula:
d,tκrespectively representing forward and reverse power flow limits of the device d in a period t; sd,i,tRepresenting the sensitivity of the device d to the tie-line m for a period t; sd,m,tRepresenting the sensitivity of the device d to the unit i in the time period t; zetatRepresenting the load flow component over time period t.
The controllable load participates in peak regulation, and the expression is as follows:
pk,t＝θk,tψk
in the formula: p is a radical ofk,tRepresenting the active power of the load k in a period t, and optimizing variables; thetak,tRepresenting the state of the load k over a period t, is a variable 0/1, thetak,tWith 1 representing the load k for a period tset, θk,t0 means that the load k is not cut off for a period t; psikRepresenting the load k active power.
Because the peak regulation requirements and the peak regulation capability evaluation analysis model considering the safety of the power transmission section of the power grid consider the peak regulation resources such as electric heat accumulation, electric energy storage, thermal power deep peak regulation, start-stop peak regulation, controllable load and the like, the peak regulation cost is also included in the optimization target, and therefore, the final optimization target is expressed as:
in the formula: f0Represents the peak shaving cost, and can furtherExpressed as:
in the formula: i represents the number of the depth peak shaving units and the starting peak shaving units; deltai,tRepresenting the depth peak regulation and start-up peak regulation cost of the conventional unit i time period t; b represents the number of electric energy storage units; deltab,tRepresenting the peak shaving cost of the period t of the electrical energy storage b; h represents the number of electric heat storages; deltah,tRepresenting the peak shaving cost of the electric heat accumulation h time period t; k represents the number of controllable loads; deltak,tRepresenting the peak shaver cost for the controllable load k period t.
Since the intra-provincial peak shaving is prior to the inter-provincial peak shaving, the intra-provincial peak shaving cost F0The priority is lower than the tie-line plan, the distribution balance slack and the new energy blocked penalty cost.
The peak regulation demand and peak regulation capacity evaluation analysis model considering the safety of the power transmission section of the power grid is established, the coordination and optimization of deep peak regulation, electric energy storage peak regulation, electric heat storage peak regulation, tie line planning, controllable load and new energy of the thermal power generating unit are realized, the intra-provincial peak regulation resources are fully excavated, the intra-provincial new energy limited quantity is provided, and the effectively executable inter-provincial peak regulation demand and peak regulation capacity are analyzed.
For a peak regulation demand and peak regulation capability evaluation analysis model considering the safety of a power transmission section of a power grid, an optimization algorithm is a branch-bound tangent plane algorithm; the safety check algorithm is the same as the traditional safety check algorithm, and the check content is the same. The specific calculation and checking process is referred to in the prior art, and is not described herein in detail.
The method is suitable for different time periods such as day ahead, day in, real time and the like, evaluates and analyzes the peak regulation demand and the peak regulation capacity between the provinces of hours in the next day and in the future, provides real and effective peak regulation demand and peak regulation capacity for day ahead, day in and real time province peak regulation, provides auxiliary decision for day ahead, day in, real time and other different period province transactions, promotes maximum consumption in the new energy whole network range, and ensures safe and stable operation of a power grid. Meanwhile, the method has the characteristics of low calculation intensity and strong adaptability, and is more suitable for popularization and application in various-scale dispatching mechanisms in China.
The technical scheme of the invention is applied to some provincial power grids, and the application effect is in line with expectations. Practical application shows that the method can combine the future operation condition of the power grid, fully evaluate the condition of peak regulation requirement and peak regulation capability among provinces, give out the inter-provincial trading suggestion, reduce the peak regulation pressure of the system, realize the maximum consumption of new energy and meet the increasingly lean safe operation requirement of the large power grid.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (7)
1. A method for evaluating and analyzing inter-provincial peak regulation requirements and peak regulation capacity of a power system is characterized by comprising the following steps of: comprises the following steps of (a) carrying out,
s1, acquiring basic data of peak regulation influence factors of the power system, and establishing a peak regulation demand and peak regulation capability evaluation analysis scene, wherein the peak regulation influence factors comprise system load prediction, new energy prediction, maintenance plan, section quota, unit shutdown information, initial plan of a tie line, the limit of the tie line, adjustable output of the unit, economic parameters of the unit, sensitivity of the unit to monitoring elements, electric heat storage parameter information, electric energy storage parameter information, controllable load active power and thermal power depth peak regulation parameters;
s2, establishing a peak regulation demand and peak regulation capacity evaluation analysis model;
and S3, reading the basic data of the evaluation analysis scene in the step S1 from the peak regulation demand and peak regulation capacity analysis model constructed in the step S2, and performing safety check iterative calculation on the peak regulation demand and peak regulation capacity of the provincial power grid to obtain an optimal model of the peak regulation demand and the peak regulation capacity.
And S4, acquiring new energy limited penalty cost and electricity balance relaxation cost with different magnitudes, and obtaining an optimization target through the combination of the conventional energy unit output, the new energy unit output and the tie line plan.
2. The method according to claim 1, wherein the method comprises the following steps: in step S2, the peak shaving demand cost is determined by the following formula:
in the formula: fdThe required cost for peak regulation,
An initial plan for a tie line m period t; tau ism,tPlanning for a tie m period t;
the peak shaver capacity cost is determined by the following formula:
in the formula: fcCost for peak regulation capability,
An initial plan for a tie line m period t; tau ism,tTime period t plan for tie line m.
3. The method according to claim 1, wherein the method comprises the following steps: the optimal model in step S3 is obtained by:
determining that the power receiving plan is increased and the power receiving plan is decreased by the same provincial power grid at the same time, and the maximum of the optimization targets is equal to the minimum of the reverse targets:
thereby determining
The optimization target of the peak regulation demand and peak regulation capacity evaluation analysis model can adopt a unified expression:
where F is the optimization objective.
4. The method according to claim 1, wherein the method comprises the following steps: the optimized target expression after the new energy limited penalty cost and the distribution electric balance relaxation cost in the step S4 is as follows:
in the formula:
representing a relaxation penalty cost function of the electricity utilization unbalance generated in the time period t; deltaw,tAnd representing the w period t limited penalty cost of the new energy source unit.
5. The method according to claim 1, wherein the method comprises the following steps: the constraint conditions of the peak shaving demand and peak shaving capacity evaluation analysis model in the step S2 are determined by the following formula:
in the formula: p is a radical ofi,tOptimizing variables for the output of the unit in the period i and t; tau ism,tOptimizing variables for the plan of the tie line m time period t; p is a radical ofw,tA constant value is used for active prediction of a new energy unit in a w time period t; deltaw,tOptimizing variables for the blocked power of the new energy unit in the w time period t; rtReserving a spare system for a time period t; l istSystem load for time period t;
the issue charge for time period t balances the amount of forward and reverse relaxation, respectively.
6. The method according to claim 5, wherein the method comprises the following steps:
and further constraining the peak regulation demand and the peak regulation capability evaluation analysis model by adding a connecting line plan component, wherein the expression is as follows:
in the formula:
d,tκrespectively representing forward and reverse power flow limits of the device d in a period t; sd,i,tRepresenting the sensitivity of the device d to the tie-line m for a period t; sd,m,tRepresenting the sensitivity of the device d to the unit i in the time period t; zetatRepresenting the load flow component over time period t.
7. The method according to claim 1, wherein the method comprises the following steps: the optimization goal in step S4 is represented as:
in the formula: f0Represents the peak shaver cost, which can be further expressed as:
in the formula: i represents the number of the depth peak shaving units and the starting peak shaving units; deltai,tRepresenting the depth peak regulation and start-up peak regulation cost of the conventional unit i time period t; b represents the number of electric energy storage units; deltab,tRepresenting the peak shaving cost of the period t of the electrical energy storage b; h represents the number of electric heat storages; deltah,tRepresenting the peak shaving cost of the electric heat accumulation h time period t; k represents the number of controllable loads; deltak,tRepresenting the peak shaver cost for the controllable load k period t.
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