CN115425697A - Distributed trans-regional and trans-provincial scheduling method and system based on alternative direction multiplier method - Google Patents
Distributed trans-regional and trans-provincial scheduling method and system based on alternative direction multiplier method Download PDFInfo
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Abstract
The invention discloses a distributed trans-regional trans-provincial dispatching method and a distributed trans-regional trans-provincial dispatching system based on an alternating direction multiplier method, wherein various constraints of generator set operation and power constraints of inter-regional or inter-provincial tie lines are considered, and a trans-regional trans-provincial economic dispatching model for centralized solution is established by taking the minimum operating cost of each region as a target; reconstructing to obtain a distributed cross-region and cross-province economic dispatching model taking sub-regions as basic optimization units, taking each region as a dispatching main body in the distributed cross-region and cross-province economic dispatching model, solving the optimization model by each region dispatching mechanism to obtain tie line power and transmitting the tie line power to an upper dispatching mechanism, updating parameters by the upper dispatching mechanism according to the tie line power transmitted by each region and issuing the parameters to each region dispatching mechanism, and taking balanced solution obtained after multiple iterations of each region dispatching mechanism and the upper dispatching mechanism as a dispatching scheme to realize distributed cross-region and cross-province dispatching. The problem of large-scale information exchange among different areas is avoided, and privacy data in the areas are effectively protected.
Description
Technical Field
The invention belongs to the technical field of power system operation, and particularly relates to a distributed trans-regional and trans-provincial dispatching method and system based on an alternating direction multiplier method.
Background
In recent years, renewable energy sources represented by wind power photovoltaic are rapidly developed, and a coal electric machine set serving as a main power source of a traditional power system is limited. Coupled with the rapid growth of loads, power system power flow balancing presents new challenges. The difference distribution of resources and loads on space makes the local area power grid difficult to realize power and electricity balance by scheduling self resources, and the large-scale development of renewable energy represented by wind power and photovoltaic aggravates the contradiction between supply and demand in local areas. Supply and demand balance and consumption are major challenges faced by a system after large-scale access of new energy, and are fundamental problems for constructing a novel power system. With the gradual construction of an extra-high voltage alternating current and direct current power grid, the trans-regional and trans-provincial dispatching capacity is improved, and the electric power and electric quantity balance among a plurality of regions becomes possible. Resources can be configured in a large range through trans-regional scheduling, the complementary characteristics of different regions are fully utilized to relieve the contradiction between the power supply and demand of local regions, and the overall economy and safety are improved. With the continuous increase of the permeability of new energy, due to the characteristics of intermittence, volatility and randomness of new energy power generation and the deep changes of characteristics of a power grid side and a load side, the traditional operation mechanisms such as trans-provincial trans-regional power transmission and reception planning and the like do not adapt to new requirements.
Under the background, in order to balance the power supply capacity and the power consumption capacity of each region, a cross-region and cross-provincial scheduling strategy needs to be researched, and the power and electricity balance of each region power system is realized by making a reasonable cross-region and cross-provincial power transmission and receiving plan.
At present, the domestic research on cross-region and cross-provincial scheduling in China mainly focuses on a power model of an extra-high voltage direct current transmission line and a scheduling method suitable for a hierarchical scheduling mode. There is less research on cross-region and cross-provincial economic dispatch, and the following problems exist in the current research:
(1) The inter-provincial dispatching model is a centralized optimization model, generator set and load information of each region are needed for solving the model, on one hand, each dispatching mechanism is needed to exchange a large amount of information, and communication burden is increased. On the other hand, information exchange may cause leakage of sensitive data, causing a security risk.
(2) Uncertainty of renewable energy and load is not considered well in a trans-provincial and trans-regional scheduling model, power transmission and reception plans in most scenes are difficult to obtain, and risks caused by uncertainty cannot be measured.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a distributed trans-regional trans-provincial dispatching method and system based on an alternative direction multiplier method, aiming at the deficiencies in the prior art, and to establish a distributed trans-regional trans-provincial economic dispatching model based on an alternative direction multiplier method, so as to solve the technical problems of large-scale data exchange and uncontrollable uncertain risks of renewable energy and load in a centralized dispatching manner.
The invention adopts the following technical scheme:
a distributed cross-region and cross-province scheduling method based on an alternate direction multiplier method comprises the following steps:
s1, considering various constraints of the operation of a generator set and power constraints of inter-regional or inter-provincial tie lines, and establishing a cross-region and cross-provincial economic dispatching model for centralized solution by taking the operation cost and minimum of each region as targets;
s2, reconstructing the trans-regional and trans-provincial economic dispatching model obtained in the step S1 based on an alternating direction multiplier method to obtain a distributed trans-regional and trans-provincial economic dispatching model taking sub-regions as basic optimization units, wherein each region in the distributed trans-regional and trans-provincial economic dispatching model is taken as a dispatching main body, each region and a connected region exchange tie line power, each region dispatching mechanism solves the optimization model according to a parameter lambda issued by a superior dispatching mechanism to obtain the tie line power and transmits the tie line power to the superior dispatching mechanism, the superior dispatching mechanism updates the parameter lambda according to the tie line power transmitted by each region and issues the tie line power to each region dispatching mechanism, and balanced solution obtained after each region dispatching mechanism and the superior dispatching mechanism iterate for multiple times is taken as a dispatching scheme to achieve distributed trans-regional and trans-provincial dispatching.
Specifically, in step S1, the cross-regional and cross-provincial economic dispatching model aims at minimizing the operation cost of each region, and the constraint conditions include power balance of the power transmission and reception region, upper and lower limits of unit output, unit climbing, region standby requirements, and tie line power constraints.
Further, the objective function is obtained by taking the minimum and running cost of each region as the target:
wherein A and T are respectively the set of region and time,
respectively, a coal electric machine set, a photovoltaic set and a wind electric machine set in the area a, P a,i,t The output of the ith coal-electric unit in the area a in the time period t, C a,i In order to achieve the corresponding coal consumption cost,
respectively is a predicted value and a decision variable of the power output of the p-th photovoltaic in the area a，
Respectively is the predicted value and decision variable, gamma, of the w-th wind power output in the area a PV ,γ W Punishment cost of abandoned light and abandoned wind respectively.
Further, the power balance constraint of the power transmission region:
the power balance constraints of the powered region are:
wherein the content of the first and second substances,
for the load of the region a during the period t,
transmitting power of a sending end and a receiving end of a connecting line l in a time period t;
the output constraint of the coal-electric unit comprises the following steps:
the output upper and lower limits of the coal-electric machine set are restricted:
and (3) climbing restraint of the coal electric unit:
spare constraint of sub-area:
wherein the content of the first and second substances,
respectively the lower limit and the upper limit of the output of the ith coal-electric machine set in the area a,
the ascending slope limit and the descending slope limit of the ith coal-electric unit in the area a are respectively,
respectively the requirements of positive standby and negative standby in the area a;
the tie-line power constraint includes:
planning electric quantity constraint:
and (3) power balance constraint of a sending end and a receiving end of the connecting line:
tie line adjustment constraint:
tie line power peak-to-valley difference constraint:
wherein E is l Planned electric quantity xi determined in advance for the areas at the two ends of the link line l l Is the loss of the tie line l.
Respectively the maximum up-regulation quantity and the maximum down-regulation quantity of the connecting line, | | | represents the number of elements contained in the set T,
alpha is an adjustment coefficient for the average transmission power.
Specifically, step S2 specifically includes:
setting a penalty coefficient rho, initializing a decision variable, setting an iteration variable k =0, and setting a termination condition E pri0 ,∈ dual0 (ii) a Each region considers each constraint of the unit in the region, and sequentially solves each region optimization problem, wherein the region solved first needs to transmit the obtained tie line power to the connected region; updating the parameter lambda; computing original residual error
Sum and dual residual
When e is pri ≤∈ pri0 And e dual ≤∈ dual0 And (5) stopping iteration and outputting a result, otherwise, returning to solve the optimization problem of each region again by k + 1.
Further, each region is solved as follows:
wherein, a is the identification of the region, A is all region groupsThe set of the (C) data is obtained,
the power generation cost of the region a, L a The objective function, λ, to be solved for the region a l,t Corresponding Lagrange multipliers are constrained for tie line power balance,
power of the tie given to the sending end region, xi l In order to reduce the loss of the tie line,
the tie line power given to the receiver area.
Further, the original residual error
Sum and dual residual
Respectively as follows:
wherein, L is the identification of the connecting lines, L is the set formed by all the connecting lines, T is the identification of the time period, T is the set of all the time periods,
the power of the connecting line given by the sending end region at the (k + 1) th iteration,
the tie line power, xi, given for the receiving end region at the k +1 th iteration l In order to avoid the loss of the connecting line,
is a Lagrange multiplier corresponding to the power balance constraint of the connecting line l in the (k + 1) th iteration,
and the lagrangian multiplier corresponding to the power balance constraint of the connecting line l in the k iteration.
Further, the update parameter λ is as follows:
wherein the content of the first and second substances,
is a Lagrange multiplier corresponding to the power balance constraint of the connecting line l in the (k + 1) th iteration,
is a Lagrange multiplier corresponding to the power balance constraint of a connecting line l in the kth iteration, rho is a penalty coefficient,
the power of the tie line, xi, given to the sending end region in the (k + 1) th iteration l In order to avoid the loss of the connecting line,
the tie line power given by the receiving end region at the (k + 1) th iteration.
Specifically, in step S2, a conditional value risk method is used to improve the distributed cross-region and cross-province economic dispatch model obtained in step S2 and using the sub-region as a basic optimization unit, so as to control the cost fluctuation caused by uncertainty, specifically:
setting a confidence level epsilon, an epsilon quantile of the operation cost probability distribution as a risk threshold, the probability of exceeding the risk threshold as 1-epsilon, and optimizing C VaR Minimizing the cost beyond the threshold is expected to reduce the fluctuation of the operating cost, and convert the multi-objective problem of performing multiple iterations on each region into a single-objective problem, which is specifically as follows:
wherein, delta is a risk aversion coefficient, S is an identifier of a scene, S is a set of scenes, and pi s Is the probability of occurrence of scene s, L a,s Optimization objective function for region a under scene s, C VaR Is a conditional value risk.
In a second aspect, an embodiment of the present invention provides a distributed cross-region and cross-provincial scheduling system based on an alternating direction multiplier method, including:
the optimization module is used for establishing a cross-region and cross-province economic dispatching model for centralized solution by taking various constraints of the operation of the generator set and power constraints of inter-regional or inter-province tie lines as targets of the minimum operation cost of each region;
the dispatching module reconstructs the cross-region and cross-province economic dispatching model obtained by the optimizing module based on an alternating direction multiplier method to obtain a distributed cross-region and cross-province economic dispatching model taking a sub-region as a basic optimizing unit, each region in the distributed cross-region and cross-province economic dispatching model serves as a dispatching main body, tie line power is communicated between each region and connected regions, each region dispatching mechanism solves the optimizing model according to parameter lambda issued by a superior dispatching mechanism to obtain the tie line power and transmits the tie line power to the superior dispatching mechanism, the superior dispatching mechanism updates Lagrange multiplier lambda according to the tie line power transmitted by each region and issues the tie line power to each region dispatching mechanism, balance obtained after the region dispatching mechanisms and the superior dispatching mechanism iterate for many times is used as a dispatching scheme, and distributed cross-region and cross-province dispatching is achieved.
Compared with the prior art, the invention has at least the following beneficial effects:
a distributed cross-regional and trans-provincial scheduling method based on an alternating direction multiplier method is characterized in that constraint conditions such as upper and lower limits of output of units in regions, climbing, standby and the like and constraint conditions such as inter-region tie line trading plans and the like are considered, a centralized model is reconstructed based on the alternating direction multiplier method, a distributed scheduling model with sub-regions as basic units is established, cross-region tie line power is only exchanged among the regions, transmission of the units in the regions and load information is not needed, the problem of large-scale data exchange in the centralized scheduling mode is avoided, and private data in the regions are effectively protected. In order to deal with uncertainty of output and load of the renewable energy unit, a condition value risk model is adopted to convert a single-target problem solved in a sub-region into a multi-target optimization problem, cost fluctuation caused by uncertainty is controlled, a distributed solving cross-region and cross-province economic dispatching problem is achieved, and data safety of the region is protected. Furthermore, the cross-region and cross-provincial economic dispatching model aims at the minimum running cost of each region, the constraint conditions comprise power balance of power transmission and receiving regions, upper and lower limits of unit output, unit climbing, region standby requirements and tie line power constraint, and all constraint conditions in actual dispatching are considered.
Further, an objective function which aims at the minimum and the running cost of each area enables the scheduling scheme to be optimal in economy under the constraint condition.
Furthermore, various constraints of the operation of the generator set and power constraints of regional or inter-provincial connecting lines take constraints in actual production into consideration in detail, so that the scheduling scheme has practicability.
Furthermore, the optimization problem of each region is solved in sequence, and cross-region economic dispatching distributed solving avoids transmission of a large amount of privacy information among the regions.
Furthermore, the sub-problem solving of each region is carried out in a distributed mode, and local data can be protected.
Furthermore, the setting of the original residual error and the dual residual error provides a criterion for convergence of the model solving process.
Furthermore, the superior scheduling mechanism updates Lagrange multipliers and coordinates the solving results of all the regions.
Further, the step S2 improves the area solution problem, and can effectively control the cost fluctuation caused by the uncertainty of the new energy.
It is understood that the beneficial effects of the second aspect can be referred to the related description of the first aspect, and are not described herein again.
In conclusion, the invention solves the cross-region and cross-provincial power dispatching problem in a distributed mode, avoids the problem of large-scale information exchange among different regions, and can effectively protect private data in the regions. Meanwhile, cost fluctuation caused by uncertainty of new energy can be controlled through parameter setting, and applicability of a scheduling scheme is enhanced.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a diagram of an exemplary regional topology;
FIG. 2 is a wind power photovoltaic output reference curve;
FIG. 3 is a diagram of a distributed cross-regional economic dispatch solution process;
FIG. 4 is a graph of marginal cost for each region without regard to cross-region scheduling for scenario one;
fig. 5 is a graph of marginal cost of each area when cross-region scheduling is considered in scenario two.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be understood that the terms "comprises" and/or "comprising" indicate the presence of the stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and including such combinations, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
It should be understood that although the terms first, second, third, etc. may be used to describe preset ranges, etc. in embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from one another. For example, the first preset range may also be referred to as a second preset range, and similarly, the second preset range may also be referred to as the first preset range, without departing from the scope of the embodiments of the present invention.
The word "if" as used herein may be interpreted as "at 8230; \8230;" or "when 8230; \8230;" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
Various structural schematics according to the disclosed embodiments of the invention are shown in the drawings. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of the various regions, layers and their relative sizes, positional relationships are shown in the drawings as examples only, and in practice deviations due to manufacturing tolerances or technical limitations are possible, and a person skilled in the art may additionally design regions/layers with different shapes, sizes, relative positions, according to the actual needs.
The invention provides a distributed trans-regional trans-provincial dispatching method based on an alternating direction multiplier method, which is characterized in that a trans-regional interconnected electric power system centralized dispatching model is established by considering various constraints such as upper and lower limits of unit output, climbing, standby and the like in a region and an inter-regional tie line trading plan;
and then, reconstructing the centralized model based on an alternating direction multiplier method, establishing a distributed scheduling model taking sub-regions as basic units, and only exchanging cross-region tie line power among the regions without transmitting internal unit and load information of the regions, thereby effectively protecting private data in the regions. In order to deal with uncertainty of output and load of the renewable energy unit, a condition value risk model is adopted to convert a single-target problem solved by a subregion into a multi-target optimization problem, and cost fluctuation caused by uncertainty is controlled.
The invention relates to a distributed trans-regional trans-provincial scheduling method based on an alternating direction multiplier method, which comprises the following steps of:
s1, centralized cross-district economic dispatching model
And (4) considering various constraints of the operation of the generator set and power constraints of the inter-regional or inter-provincial tie lines, and establishing a cross-regional and trans-provincial economic dispatching model for centralized solution.
The centralized cross-district economic dispatching aims at the minimum and running cost of each district, and the running cost comprises coal consumption cost and wind and light abandoning penalty cost. Meanwhile, constraints such as upper and lower limits of unit output, unit climbing, standby and tie line trading electric quantity are considered. The objective function is shown in equation (1):
wherein A and T are respectively the set of region and time,
respectively, the coal electric machine set, the photovoltaic and the wind electric machine set in the area a, P a,i,t The output of the ith coal-electric unit in the area a in the time period t, C a,i For corresponding coalThe consumption cost is represented by the formula (2) in the form of a quadratic function,
respectively is a predicted value and a decision variable of the photovoltaic output of the p-th station in the area a,
respectively is the predicted value and decision variable, gamma, of the w-th wind power output in the area a PV ,γ W The punishment cost of abandoned light and abandoned wind is respectively.
The power balance constraint of the power transmission area is as follows:
the power balance constraints of the powered region are:
wherein the content of the first and second substances,
for the load of the region a during the period t,
and transmitting the transmission power of the sending end and the receiving end of the connecting line l in the time period t.
The output constraint of the coal-electricity unit is as follows:
wherein, the formula (5) is the restriction of the upper and lower limits of the output of the coal-electric machine set,
respectively is the lower limit and the upper limit of the output of the ith coal-electric machine set in the area a. The formulas (6) and (7) are the climbing constraint of the coal-electricity unit,
the ascending and descending limits of the ith coal-electric unit in the area a are respectively set. The formulas (8) and (9) are standby constraints of subareas, and provide positive and negative standby for the coal-electric unit to deal with the fluctuation of renewable energy sources and loads,
respectively positive spare and negative spare requirements in area a.
The tie line power constraint mainly comprises a planning electric quantity, and constraints such as power balance of transmission and reception are as follows, wherein the formula (10) is the planning electric quantity constraint, the formula (11) is the tie line transmission and reception end power balance constraint, the formulas (12) and (13) are the tie line adjustment constraints, and the formula (14) is the tie line power peak-valley difference constraint.
P l,t+1 -P l,t ≤P l RU (12)
P l,t -P l,t+1 ≤P l RD (13)
Wherein E is l Planned electric quantity, xi, determined in advance for the areas at the two ends of the link l l Loss of the tie line l.
Respectively the maximum up-regulation quantity and the maximum down-regulation quantity of the connecting line, | | | represents the number of elements contained in the set T,
α is an adjustment coefficient for the average transmission power.
S2, distributed trans-regional trans-provincial economic dispatching model
The centralized trans-regional and trans-provincial economic dispatching model is reconstructed based on an alternating direction multiplier method, each region is taken as a dispatching main body, the power of the tie lines is exchanged between each region and the connected regions, and the units and the load information in the regions do not need to be published to the outside. Each regional scheduling mechanism transmits tie line power to a superior scheduling mechanism, the superior scheduling mechanism updates Lagrange multipliers and issues the Lagrange multipliers to each regional scheduling mechanism, and a balanced solution is obtained after multiple iterations to obtain a scheduling scheme.
The centralized cross-regional economic dispatching model needs unit and load information of each region for solving, which relates to the problem of data privacy.
For the following form of problem:
the corresponding augmented lagrange function is:
wherein y is a lagrangian multiplier corresponding to the equality constraint.
ADMM gives the solution to the problem (15) as follows:
y k+1 ＝y k +ρ(Ax k+1 +Bz k+1 -c) (19)
where the superscript k denotes the kth iteration.
In each iteration process, x is solved in sequence k+1 ,z k+1 ,y k+1 . Solving for x k+1 In the process of (1), z k ,y k Is a fixed value, where g (z) is a fixed value, and can be omitted, meaning that x is solved for k+1 Does not need information of g (z), and only needs to know the partial variable coupled by z and x. In a similar manner, solve for z k+1 In time, only need x k+1 And (4) transmitting the variables for neutralizing the z coupling to the model.
The centralized cross-regional economic dispatch model has similar properties to the problem (15), and the overall cost is decomposed into the sum of the area costs:
each region solves the following problem:
in the case of the power transmission area,
to decide a variable, and
the parameters are transmitted by the corresponding power receiving areas, and the same applies to the power receiving areas; it should be noted that when a solution is completed for a certain area, the solution is to be executed
Or
To the corresponding region.
After all regions solve the subproblems, updating the Lagrange multiplier λ:
this completes an iteration.
The termination condition of iteration is that the original residual error and the dual residual error are reduced to a certain range, and the definition of the original residual error and the dual residual error is as follows:
the distributed solving process of the cross-region economic dispatching comprises the following steps:
1. inputting parameters, setting a penalty coefficient rho, initializing a decision variable, setting an iteration variable k =0, and setting a termination condition E pri0 ,∈ dual0 。
2. Each region considers each constraint of the internal unit of the region, and the sub-problems (22) are solved in sequence. It should be noted that areas without links can be solved simultaneously, areas with links are solved sequentially, and areas with links need to transfer the solved link power to the connected areas.
3. The lagrange multiplier is updated according to equation (23).
4. The convergence criterion for the original and dual residuals is calculated according to equation (24).
5. When is e pri ≤∈ pri0 And e dual ≤∈ dual0 And (4) stopping iteration and outputting a result, otherwise, returning to the step 2 by using k + 1.
S3, improving scheduling model based on condition value risk
And improving a sub-region solution problem by adopting a condition value risk method, and controlling the cost fluctuation caused by uncertainty.
Uncertainty of new energy output and load can influence system operation cost, and the method introduces condition value risk (C) VaR ) And carrying out risk management on the uncertainty. The confidence level ε is set, the ε quantile of the running cost probability distribution is the risk threshold (VaR), and the probability of exceeding the risk threshold is 1- ε.
C VaR Minimizing cost over threshold expectations:
wherein, the optimization result of the variable zeta is the VaR value of the operation cost, S is the scene set, and pi s Is the probability, χ, of the scene s s By the amount that VaR is exceeded in scene s,
is the running cost of region a in scene s.
Fluctuations in operating costs are reduced by optimization problems (25).
The cross-region economic dispatching model considering the condition risk value is a multi-objective optimization problem, an equation (22) is rewritten into an equation (27), and the multi-objective problem is converted into a single-objective problem.
Where δ is the risk aversion coefficient, increasing δ increases the aversion of the decision maker to the risk.
In another embodiment of the present invention, a distributed trans-regional and trans-provincial scheduling system based on an alternating direction multiplier method is provided, and the system can be used to implement the distributed trans-regional and trans-provincial scheduling method based on the alternating direction multiplier method.
The optimization module is used for establishing a cross-region and cross-province economic dispatching model for centralized solution by taking various constraints of the operation of the generator set and power constraints of inter-regional or inter-province connecting lines into consideration and taking the minimum running cost and the minimum running cost of each region as targets;
the dispatching module reconstructs the cross-region and cross-province economic dispatching model obtained by the optimizing module based on an alternating direction multiplier method to obtain a distributed cross-region and cross-province economic dispatching model taking a sub-region as a basic optimizing unit, each region in the distributed cross-region and cross-province economic dispatching model serves as a dispatching main body, tie line power is communicated between each region and connected regions, each region dispatching mechanism solves the optimizing model according to parameter lambda issued by a superior dispatching mechanism to obtain the tie line power and transmits the tie line power to the superior dispatching mechanism, the superior dispatching mechanism updates Lagrange multiplier lambda according to the tie line power transmitted by each region and issues the tie line power to each region dispatching mechanism, balance obtained after the region dispatching mechanisms and the superior dispatching mechanism iterate for many times is used as a dispatching scheme, and distributed cross-region and cross-province dispatching is achieved.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
And (3) analyzing the effectiveness and the practicability of the established model by combining with an actual example, wherein the method specifically comprises the following steps:
referring to fig. 1, installed capacity and maximum load of each area are shown in table 1, areas 1, 2 and 3 have coal- electric machine units 19, 20 and 15, respectively, and a cost function of the coal-electric machine units is represented by a quadratic function represented by formula (2).
TABLE 1 regional installed capacity and maximum load
Referring to fig. 2, the wind and light abandoning penalty cost γ PV 、γ W The power supply system comprises a power supply, a power supply and a power supply, wherein the power supply is 50$/MW, positive standby of a sub-region is 5% of load, negative standby is 5% of renewable energy output, a region 2 supplies power to a region 1 at 3000MW · h, a region 3 supplies power to the region 1 at 200MW · h, and network loss of a regional tie line is 3%, randomness of renewable energy and load is simulated in normal distribution, a large number of samples are generated through Monte Carlo simulation, then 10 scenes are clustered through K-means, the confidence level epsilon is 0.6, and the scene with the cost exceeding 60% of a sub-site is represented as a risk scene.
Adopting ADMM to solve the distributed cross-district economic scheduling problem, setting the penalty coefficient rho to be 0.1, and setting the termination condition to be epsilon pri0 ,∈ dual0 Are respectively 10 -3 . The original residual 2-norm and dual residual 2-norm changes during the iteration are shown in fig. 3.
The ADMM algorithm reaches a termination condition after 81 iterations, the algorithm terminates the iterations, and as can be seen from FIG. 3, the convergence criterion after 3 iterations is very small, which can already meet the practical engineering application, thus proving that the ADMM algorithm has good convergence.
To illustrate the effectiveness of the algorithm presented herein and the advantages of cross-regional scheduling, three scenarios are set for comparison:
scene one: cross-region scheduling does not exist, and each region is optimized independently;
scene two: optimizing by adopting the ADMM-based trans-regional economic dispatching model;
scene three: and optimizing by adopting a centralized cross-region economic dispatching model.
The operating cost of each zone under three scenarios is shown in table 2:
TABLE 2 running cost of each zone under different scenarios
It is seen from table 2 that the operation costs of each area in scene two and scene three are almost the same, and the error is small enough to be ignored, which proves the correctness of the method provided by the present invention. Compared with the independent balance of each area in the first scene, in the second scene and the third scene, the operation cost of the first area is reduced, and the cost of the second area and the cost of the third area are increased, because the first area is a power receiving area, the second area and the third area are power transmission areas, and the cross-area scheduling power cost is counted into the power transmission areas; the total running cost of each area in the second and third scenes is reduced by 7283$, which shows that resources can be more reasonably allocated through cross-regional scheduling, the overall running cost is reduced, and the system economy is improved.
The marginal cost for each time period for each region in scene one and scene two is shown in fig. 4 and 5.
Referring to fig. 4, the marginal cost fluctuation of the area 1 is relatively large, because the load fluctuation of the area 1 is large, which can significantly affect the marginal cost of the generator set, and in the late peak period, the load of the area 1 is maximum, and the corresponding marginal cost is significantly increased.
Referring to fig. 5, the marginal cost trends of the regions are the same, and there is no large fluctuation, in the cross-regional scheduling model, the region 1 with a large load can use the power generation resources with lower cost in the regions 2 and 3 to reduce the power generation cost in the regions, which proves that the cross-regional scheduling can optimize the resource allocation.
In summary, the distributed trans-regional and trans-provincial scheduling method and system based on the alternative direction multiplier method solve the trans-regional and trans-provincial power scheduling problem in a distributed manner, avoid the problem of large-scale information exchange among different regions, and can effectively protect private data inside the regions. Meanwhile, cost fluctuation caused by uncertainty of new energy can be controlled through parameter setting, and applicability of the scheduling scheme is enhanced.
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.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. The distributed trans-regional trans-provincial scheduling method based on the alternative direction multiplier method is characterized by comprising the following steps of:
s1, considering various constraints of the operation of a generator set and power constraints of inter-regional or inter-provincial tie lines, and aiming at the minimum running cost and the minimum running cost of each region, establishing a cross-regional and trans-provincial economic dispatching model for centralized solution;
s2, reconstructing the trans-regional and trans-provincial economic dispatching model obtained in the step S1 based on an alternating direction multiplier method to obtain a distributed trans-regional and trans-provincial economic dispatching model taking sub-regions as basic optimization units, wherein each region in the distributed trans-regional and trans-provincial economic dispatching model is taken as a dispatching main body, each region and a connected region exchange tie line power, each region dispatching mechanism solves the optimization model according to a parameter lambda issued by a superior dispatching mechanism to obtain the tie line power and transmits the tie line power to the superior dispatching mechanism, the superior dispatching mechanism updates the parameter lambda according to the tie line power transmitted by each region and issues the tie line power to each region dispatching mechanism, and balanced solution obtained after each region dispatching mechanism and the superior dispatching mechanism iterate for multiple times is taken as a dispatching scheme to achieve distributed trans-regional and trans-provincial dispatching.
2. The distributed trans-regional and trans-provincial scheduling method based on the alternating direction multiplier method as claimed in claim 1, wherein in step S1, the trans-regional and trans-provincial economic scheduling model targets the minimum and the minimum running cost of each region, and the constraint conditions include power balance of power transmission and reception regions, upper and lower limits of unit output, unit climbing, region standby requirements, and tie line power constraints.
3. The distributed trans-regional and trans-provincial scheduling method based on the alternating direction multiplier method as claimed in claim 2, wherein an objective function is obtained with the minimum running cost sum of each region as a target as follows:
wherein A and T are respectively the set of region and time,
respectively, the coal electric machine set, the photovoltaic and the wind electric machine set in the area a, P a,i,t The output of the ith coal-electric unit in the area a in the time period t, C a,i In order to meet the corresponding coal consumption cost,
respectively a predicted value and a decision variable of the photovoltaic output of the p-th station in the area a,
respectively is the predicted value and decision variable, gamma, of the w-th wind power output in the area a PV ,γ W Punishment cost of abandoned light and abandoned wind respectively.
4. The distributed trans-regional and trans-provincial scheduling method based on the alternating direction multiplier method according to claim 2, wherein the power balance constraint of the power transmission region is as follows:
the power balance constraints of the powered region are:
wherein the content of the first and second substances,
for the load of the region a during the period t,
transmitting power of a sending end and a receiving end of a connecting line l in a time period t;
the output constraint of the coal-electric unit comprises the following steps:
the output upper and lower limits of the coal-electric machine set are restricted:
and (3) climbing restraint of the coal electric unit:
spare constraint of sub-area:
wherein, the first and the second end of the pipe are connected with each other,
respectively is the lower limit and the upper limit of the output of the ith coal-electric machine set in the area a,
the upper climbing limit and the lower climbing limit of the ith coal-electric machine set in the area a are respectively,
respectively the positive standby requirement and the negative standby requirement in the area a;
the tie line power constraint includes:
and (4) planning electric quantity constraint:
and (3) power balance constraint of a sending end and a receiving end of the connecting line:
tie line adjustment constraint:
P l,t+1 -P l,t ≤P l RU
P l,t -P l,t+1 ≤P l RD
tie line power peak-to-valley difference constraint:
wherein E is l For the areas at the two ends of the connecting line l to be determined in advancePredetermined planned electric quantity xi l In order to reduce the loss of the tie line l,
respectively the maximum up-regulation quantity and the maximum down-regulation quantity of the connecting line l, the | T | represents the number of elements contained in the set T,
alpha is an adjustment coefficient for the average transmission power.
5. The distributed trans-regional and trans-provincial scheduling method based on the alternating direction multiplier method as claimed in claim 1, wherein the step S2 is specifically:
setting a penalty coefficient rho, initializing a decision variable, setting an iteration variable k =0, and setting a termination condition E pri0 ,∈ dual0 (ii) a Each region considers each constraint of the unit in the region, and sequentially solves each region optimization problem, wherein the region solved first needs to transmit the obtained tie line power to the connected region; updating the parameter lambda; calculate the original residual oa pri And dual residual oa dual (ii) a When e is pri ≤∈ pri0 And e dual ≤∈ dual0 And (4) stopping iteration and outputting a result, otherwise, returning to solve the optimization problem of each region again by k + 1.
6. The distributed trans-regional trans-provincial scheduling method based on the alternating direction multiplier method according to claim 5, wherein each region is solved as follows:
wherein a is the identification of the region, A is the set formed by all the regions,
the power generation cost of the region a, L a Objective function solved for region a，λ l,t Lagrange multipliers corresponding to tie line power balance constraints,
power of the tie given to the sending end region, xi l In order to avoid the loss of the connecting line,
the tie line power given to the receiving end region.
7. The distributed trans-regional and trans-provincial scheduling method according to claim 5, characterized in that an original residual oa is pri And dual residual oa dual Respectively as follows:
wherein L is a tie line identifier, L is a set formed by all tie lines, T is a time period identifier, T is a set of all time periods,
the call wire power given by the sending end region at the (k + 1) th iteration,
the tie line power, xi, given for the receiving end region at the k +1 th iteration l In order to avoid the loss of the connecting line,
is a Lagrange multiplier corresponding to the power balance constraint of the connecting line l in the (k + 1) th iteration,
and the lagrangian multiplier corresponding to the power balance constraint of the connecting line l in the k iteration.
8. The distributed trans-regional trans-provincial scheduling method based on the alternating direction multiplier method according to claim 5, wherein the update parameter λ is as follows:
wherein the content of the first and second substances,
is a Lagrange multiplier corresponding to the power balance constraint of the connecting line l in the (k + 1) th iteration,
is a Lagrange multiplier corresponding to the power balance constraint of a connecting line l in the kth iteration, rho is a penalty coefficient,
the power of the tie line, xi, given to the sending end region in the (k + 1) th iteration l In order to avoid the loss of the connecting line,
the tie line power given by the receiver region at the (k + 1) th iteration.
9. The distributed trans-regional trans-provincial dispatching method based on the alternating direction multiplier method according to claim 1, wherein in step S2, a conditional value risk method is adopted to improve the distributed trans-regional trans-provincial economic dispatching model which is obtained in step S2 and takes the sub-region as a basic optimization unit, so as to control the cost fluctuation caused by uncertainty, and specifically:
setting a confidence level epsilon, an epsilon quantile of the operation cost probability distribution as a risk threshold, the probability of exceeding the risk threshold as 1-epsilon, and optimizing C VaR Minimizing cost over threshold is expected to reduce fluctuations in operating costs, and multi-objective problems that will perform multiple iterations for each region are transferred toThe problem is a single target, and the specific steps are as follows:
wherein, delta is risk aversion coefficient, S is identification of scene, S is set of scene, pi s Is the probability of occurrence of scene s, L a,s Optimization objective function for region a under scene s, C VaR Is a conditional value risk.
10. A distributed cross-region and cross-provincial scheduling system based on an alternate direction multiplier method is characterized by comprising the following steps:
the optimization module is used for establishing a cross-region and cross-province economic dispatching model for centralized solution by taking various constraints of the operation of the generator set and power constraints of inter-regional or inter-province connecting lines as targets of the minimum running cost and the minimum running cost of each region;
the dispatching module reconstructs the cross-region and cross-province economic dispatching model obtained by the optimizing module based on an alternating direction multiplier method to obtain a distributed cross-region and cross-province economic dispatching model taking sub-regions as basic optimizing units, each region in the distributed cross-region and cross-province economic dispatching model is taken as a dispatching main body, each region and connected regions exchange tie line power, each region dispatching mechanism solves the optimizing model according to the parameter lambda issued by a superior dispatching mechanism to obtain the tie line power and transmits the tie line power to the superior dispatching mechanism, the superior dispatching mechanism updates the parameter lambda according to the tie line power transmitted by each region and issues the tie line power to each region dispatching mechanism, and balanced solution obtained after each region dispatching mechanism and the superior dispatching mechanism iterate for many times is taken as a dispatching scheme to achieve distributed cross-region and cross-province dispatching.
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