CN113469424B - Multi-target planning method for comprehensive energy system - Google Patents
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Abstract
The invention discloses a multi-target planning method for a comprehensive energy system, which comprises the following steps: constructing a comprehensive energy system multi-target planning model containing an optimization target and operation constraints based on the practical interval safety domain; solving the planning model by adopting an NSGA-II algorithm to obtain an optimal system planning scheme set; and for each set of planning scheme, a system with more balanced security domains and lower influence degree of uncertainty of renewable energy resources is obtained at the minimum economic cost by reconfiguring key elements of the system to increase the capacity of the key elements of the system, and the method is favorable for improving the security state of the system and expanding the absolutely safe operation area of the system.
Description
Technical Field
The invention relates to the field of comprehensive energy systems, in particular to the field of safety analysis of regional comprehensive energy systems containing renewable energy sources, and particularly relates to a comprehensive energy system multi-target planning method based on a practical interval safety domain theory.
Background
Due to the aggravation of energy crisis and the increasing environmental pollution caused by the heavy use of fossil energy, there is an urgent need to construct efficient, clean and sustainable energy systems worldwide. Renewable energy power generation forms such as wind power, photoelectricity and the like are taken as one of green power generation representatives, and the low-carbon environment-friendly sustainable power generation device has the characteristics of low carbon, environmental protection and sustainability. Therefore, an integrated energy system integrating renewable energy is rapidly developing and widely used, which can reasonably utilize renewable energy, improve the consumption capacity thereof, and simultaneously reduce carbon emission, improve the energy use efficiency and economic benefit through coupling and cascade utilization of various energy sources.
The capacities of key equipment and pipeline sections of the comprehensive energy system are reasonably configured, and multi-objective planning is carried out on the capacities. At present, multi-objective planning research of an integrated energy system mainly optimizes the economy and the environment of the planned system and ensures the safety of the system in a penalty function form, and the method has the following defects:
(1) for an integrated energy system comprising renewable energy, the existing research is not deep enough for the N-1 safety consideration of the planned system;
(2) compared with an independent safety optimization index, the system safety index in the penalty function form is difficult to quantify the safety degree of the planned system;
(3) the existing research fails to deeply consider how to reduce the influence degree of uncertainty of renewable energy sources after planning on the system.
At present, the research on the safety of the comprehensive energy system is mostly based on a traditional point-by-point method, the safety state is judged by locally limiting operating points through point-by-point simulation check, the obtained safety information is relatively unilateral, and the calculation amount is large and the consumed time is long. The security domain method is an important security analysis method, can obtain a complete region in which the system can safely operate, effectively and conveniently observes the security boundary of the system, and greatly simplifies the solution of various optimization problems related to security. Considering the uncertainty of renewable energy, the boundary of an absolute N-1 safe region of a system and the boundary of a probability N-1 safe region caused by the influence of the randomness of the renewable energy can be accurately quantized by the existing practical interval safety domain theory, and meanwhile, the system safety state index is obtained according to the relative position of a working point in the safe region under a full-dimensional view angle.
In conclusion, the system safety information based on the practical interval safety domain lays a foundation for quantifying the influence degree of the N-1 safety and the renewable energy uncertainty after the comprehensive energy system is planned. Therefore, it is necessary to research a multi-objective planning method for an integrated energy system based on a practical interval safety domain theory. How to reduce the influence degree of the uncertainty of the renewable energy on the system and improve the safety degree of the system N-1 is an urgent problem to be solved.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a comprehensive energy system multi-target planning method based on a practical interval security domain theory, which can solve the problem that the safety of a system N-1 and how to quantify the influence degree of renewable energy uncertainty on the system in the conventional planning method are not deeply considered, obtain a planning scheme which has lower planning cost, realizes more balance of the planned system security domain and lower influence degree of the renewable energy uncertainty, and is described in detail as follows:
the purpose of the invention is realized by the following technical scheme:
a multi-target planning method for an integrated energy system is based on a practical interval safety domain theory and comprises the following steps:
Constructing a comprehensive energy system multi-target planning model containing an optimization target and operation constraints based on the practical interval safety domain;
solving the multi-target planning model by adopting an NSGA-II algorithm to obtain an optimal system planning scheme set;
and for each group of planning schemes, the capacity of the integrated energy system is increased by reconfiguring key elements of the integrated energy system, so that the degree of the safety domain equalization of the system practical interval is increased, and the degree of the influence of the randomness of the renewable energy sources on the system practical interval is reduced.
Furthermore, the key elements of the comprehensive energy system comprise a power feeder line, a heat distribution pipeline, a natural gas pipeline, a transformer, a gas turbine, a CHP unit and a compressor.
Further, the multi-objective planning model of the integrated energy system specifically comprises:
(1) optimizing the target I: the degree of influence of renewable energy uncertainty (IDREU) is minimized:
in the formula, xi 1 A minimum value representing a degree of influence of renewable energy uncertainty;PIFR m,u ,
respectively representing the upper and lower limits of the practical interval full-dimensional upper radius corresponding to the key pipeline segment m;
when the renewable energy is not accessed to the comprehensive energy system, all pipeline sections of the comprehensive energy system correspond to the average value of the practical full-dimensional radiuses;
(2) Optimization objective II: the Balance Degree (BD) of the full-dimensional practical interval security domain of the comprehensive energy system is maximized:
in the formula, xi 2 The maximum value of the balance degree of the full-dimensional practical interval security domain of the comprehensive energy system is represented;PIFR average,u 、
respectively representing the upper limit and the lower limit of the average value of the full-dimensional upper radius of the corresponding practical interval of all pipeline sections of the comprehensive energy system; m represents the number of system pipeline segments;
(3) optimization objective III: and (3) minimizing the planning cost of the comprehensive energy system:
in the formula, xi 3 Represents the minimum value of the system planning cost; c ex,a And C ex,b Respectively representing the capacity of the a-th reconfiguration device and the capacity of the b-th reconfiguration pipeline section; eta a 、η b Respectively representing the configuration cost coefficients of the a-th reconfiguration device and the b-th reconfiguration pipeline segment; n is a radical of a And N b The number of reconfiguration devices and pipeline sections, respectively; len (a) b Indicating the length of the b-th reconfigured pipeline segment.
And the constraint condition of the multi-target planning is capacity expansion upper limit constraint.
The capacity expansion upper limit constraint is:
in the formula (I), the compound is shown in the specification,
and
representing the maximum capacity of the ith reconfiguration device and the b-th reconfiguration pipeline section, respectively.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
1. the invention establishes the multi-target planning model of the security domain which enables the comprehensive energy system to obtain more balanced renewable energy uncertainty influence degree at the minimum economic cost, is beneficial to improving the security state of the comprehensive energy system and expanding the absolute safe operation area of the comprehensive energy system.
2. Through solving the model, a specific planning scheme can be obtained, including the equipment and pipeline section numbers needing capacity configuration measures in the integrated energy system and the size of specific capacity expansion, which is beneficial to improving the safety of the integrated energy system and reducing the uncertain influence degree of renewable energy.
Drawings
Fig. 1 is a pareto frontier for a capacity optimized configuration scheme.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In order to enable the integrated energy system to obtain a planning scheme for achieving higher safety and lower renewable energy influence degree at the minimum economic cost, this embodiment provides a multi-objective planning method for the integrated energy system based on the practical interval security domain theory, which is shown in fig. 1 and specifically follows:
101: constructing a comprehensive energy system multi-target planning model containing an optimization target and operation constraints based on the practical interval safety domain;
102: solving the planning model by adopting an NSGA-II algorithm to obtain an optimal system planning scheme set;
103: the planning scheme is specifically described as follows: for each set of planning schemes, the capacity of the system key elements (power feeders, heat pipelines, natural gas pipelines, transformers, gas turbines, CHP units, compressors and the like) is increased by reconfiguring the system key elements, so that the degree of safety domain equalization of the system practical range is increased and the degree of influence of randomness of renewable energy sources on the system practical range is reduced.
The scheme in this embodiment is further described below with reference to fig. 1 and the calculation formula, which is described in detail below:
with respect to step 101: constructing a comprehensive energy system multi-target planning model containing an optimization target and operation constraints based on the practical interval safety domain;
first, a practical compartmentalized security domain theory is briefly introduced, which can be defined as: the system working point set meeting the N-1 transfer range interval safety inequality constraint and the multi-energy flow balance constraint of the comprehensive energy system has the following mathematical form:
wherein, L represents a working point vector; h (L) 0 represents the energy balance equation of the multi-energy flow of the comprehensive energy system; lambda [ alpha ] l 、λ u Respectively representing pipeline proportion parameter matrixes corresponding to N-1 transfer band interval lower limit and upper limit safety constraint;
and respectively representing an upper limit energy supply capacity column matrix and a lower limit energy supply capacity column matrix of the d rows.
The safety inequality constraint of N-1 transition interval is as follows:
in the formula, L m 、L n Supplying loads to the critical pipeline segments m, n; c n Is the rated capacity of the key pipeline segment n; c RE,z Indicating the rated capacity of the z th renewable energy device; s represents the number of accesses of renewable energy devices on the interconnecting pipeline segment, and S is 0 for the natural gas and thermal side;
respectively representing the upper and lower limits of the interval upper limit safety constraint of the pipeline segment side during the distributed access of the renewable energy sources, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme;
respectively representing the upper and lower limits of the interval upper limit safety constraint at the pipeline segment side during the centralized access of the renewable energy sources, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme;
the upper and lower limits of the pipeline segment side interval lower limit safety constraint during distributed or centralized access of renewable energy respectively correspond to the y th fault under the special condition of unbalanced supply and demand j A belt rotating scheme; p con Representing the energy consumption of electric driving equipment such as a heat pump and a compressor; p sup Represents the minimum output of the interconnection critical equipment; h i 、H j Representing the sum of supply loads of the key pipeline sections corresponding to the ith and jth equipment; c j Indicating the rated capacity of the jth equipment; c. C u An electric heating ratio upper limit coefficient representing the air extraction type cogeneration; l is h1 Representing the load supplied by the key pipeline segment for heat output of the air extraction type cogeneration;
respectively representing the upper and lower limits of the interval upper limit safety constraint of the equipment side when the renewable energy sources are accessed in a distributed manner, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme; c RE Representing the rated capacity of the renewable energy device;
respectively representing the upper and lower limits of the interval upper limit safety constraint of the equipment side when the renewable energy sources are accessed in a centralized way, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme; c. C m The lower limit coefficient of the electric heating ratio of the extraction type cogeneration is expressed;
C RE，equ the upper and lower limits of the interval lower limit safety constraint of the device side are respectively distributed or centralized access of renewable energy sources.
The balance constraint of the multi-energy flow is as follows:
in the formula, h PDS (L)＝0、h NGS (L)＝0、h DHS (L)＝0、h EH And (L) ═ 0 represents the energy flow balance equation corresponding to the power system, the natural gas system, the regional thermodynamic system and the energy hub respectively.
Practical interval safety boundary PISB corresponding to mth key pipeline segment based on N-1 strip-transferring interval safety inequality constraint m Can be expressed as:
and is
In the formula: l is k Supplying a load λ to a critical pipeline segment k k Representing a pipeline ratio parameter; PISB m,u 、PISB m,l Respectively representing practical interval safe upper boundary and practical interval safe lower boundary corresponding to the key pipeline segment m;
PISB m,l respectively representing PISB m,l The upper and lower limits of (a) are,
PISB m,u respectively representing PISB m,u The upper and lower limits of (d); Θ represents the set of all N-1 faults associated with the critical pipeline segment m, except for supply-demand imbalance faults; II, representing all the tape transferring scheme sets under the N-1 fault related to the key pipeline segment m except the supply and demand imbalance fault; y represents the set of all tape-transferring schemes under the supply-demand imbalance fault associated with the critical pipeline segment m;
respectively representing the upper and lower limits of the interval upper limit safety constraint of the pipeline segment side during the distributed access of the renewable energy sources, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme;
respectively representing the upper and lower limits of the interval upper limit safety constraint at the pipeline segment side during the centralized access of the renewable energy sources, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme;
the upper and lower limits of the pipeline segment side interval lower limit safety constraint during distributed or centralized access of renewable energy respectively correspond to the y th fault under the special condition of unbalanced supply and demand j A belt rotating scheme;
respectively representing the upper and lower limits of the interval upper limit safety constraint of the equipment side when the renewable energy sources are accessed in a distributed manner, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A tape rotating scheme;
respectively representing the upper and lower limits of the interval upper limit safety constraint of the equipment side when the renewable energy sources are accessed in a centralized way, corresponding to the y < th > fault under the x < th > fault except the unbalanced supply and demand i A belt rotating scheme;
C RE,equ the upper and lower limits of the interval lower limit safety constraint of the device side are respectively distributed or centralized access of renewable energy sources.
Respectively represent
One of the collection elements.
Next, a full-dimensional observation method based on a practical interval safety domain is briefly introduced, a practical interval full-dimensional radius is modeled, and the practical interval safety distance value from a zero-load working point to each practical interval safety boundary is defined as:
in the formula (I), the compound is shown in the specification,PIFR m,u ,
representing the upper and lower limits of the practical interval full-dimensional upper radius corresponding to the pipeline section m;PIFR m,l ,
representing the upper and lower limits of the practical interval full-dimensional lower radius corresponding to the pipeline section m;
after the full-dimensional radius of the interval is solved, the full-dimensional radius boundary is drawn in a radar map form to realize the full-dimensional observation of the interval.
Aiming at the defects of the multi-target planning method of the current comprehensive energy system, the full-dimensional radius index obtained according to the relative position of the working point in the safety domain under the full-dimensional visual angle based on the existing practical interval safety domain theory is considered to represent the size of the absolute safe operation and probability safe operation range of the system, so that in order to improve the N-1 safety degree of the system and reduce the influence degree of the uncertainty of the renewable energy source on the system, the planning cost is considered at the same time, and the influence degree function of the uncertainty of the renewable energy source, the equilibrium degree function of the full-dimensional practical interval safety domain of the system and the planning cost function are provided. And establishing a multi-target planning model based on the method, and discussing a solving method of the multi-target planning model.
Firstly, defining a system practical interval full-dimensional upper radius set PIFR u ＝(PIFR 1,u ,PIFR 2,u ,…PIFR m,u ,…PIFR M,u ) The average of all elements is:
in the formula (I), the compound is shown in the specification,PIFR average,u 、
respectively representing the average values of upper and lower radius limits of all practical interval full-dimensional corresponding to all pipeline sections of the system;PIFR m,u ,
respectively representing the upper and lower limits of the practical interval full-dimensional upper radius corresponding to the pipeline segment m.
Assuming that the renewable energy unit is not connected to the system, PIFR u Is arranged as
Wherein the average PFR of all elements NRE,u Can be expressed as:
in the formula (I), the compound is shown in the specification,
and when the renewable energy source unit is not connected to the system, all pipeline sections of the system correspond to the average value of the radius in the practical interval full dimension.
Considering the uncertainty of renewable energy, the degree of influence of the uncertainty of renewable energy (IDREU) is defined as PIFR m,u Sum of interval widths
Can be defined as
The fact that IDREU is close to 0 indicates that the influence degree of the renewable energy uncertainty on the whole-dimensional security domain of the system is lower, namely the absolute security operation area of the system is larger, and indicates that the influence degree of the renewable energy uncertainty on the operation of the system is lower.
With reference to voltage harmonic distortion, the Balance Interval (BI) of a full-dimensional practical interval security domain may be defined as:
in the formula (I), the compound is shown in the specification,PIFR average,u 、
respectively representing the average values of upper and lower radius limits of all practical interval full-dimensional corresponding to all pipeline sections of the system; M represents the number of system pipeline segments.
According to the interval algorithm, it can be updated as:
since BI is an interval number, the closer the upper and lower limits of BI are to 1, the more balanced structure of the full-dimensional practical interval security domain is obtained, so BD can be defined to measure the difference between the upper and lower limits of BI and 1:
BD close to 0 here represents a more balanced structure of the full-dimensional PISR-RIES, i.e. there is no recess in the system full-dimensional security domain, and the system is not likely to reach the security boundary in each critical pipeline segment direction during operation, indicating that the system N-1 is more secure.
During planning, the cost of reconstructing equipment or a pipe section after capacity expansion is considered, and the final configuration cost is as follows:
in the formula, C ex,a And C ex,b Respectively representing the capacity of the a-th reconfiguration device and the capacity of the b-th reconfiguration pipeline section; eta a 、η b Respectively representing the configuration cost coefficients of the a-th reconfiguration device and the b-th reconfiguration pipeline segment; n is a radical of a And N b The number of reconfiguration devices and pipeline sections, respectively; len (a) b Indicating the length of the b-th reconfigured pipeline segment.
Comprehensively considering three aspects of safety, uncertainty influence degree of renewable energy and planning cost after system planning, and carrying out multi-objective planning on the comprehensive energy system, wherein the planning optimization objective is as follows:
(1) Optimizing the target I: the degree of influence of renewable energy uncertainty (IDREU) is minimized:
in the formula, xi 1 A minimum value representing a degree of influence of renewable energy uncertainty;PIFR m,u ,
respectively representing the upper and lower limits of the practical interval full-dimensional upper radius corresponding to the key pipeline segment m;
when the renewable energy is not accessed to the comprehensive energy system, all pipeline sections of the comprehensive energy system correspond to the average value of the practical full-dimensional radiuses;
(2) optimization objective II: the Balance Degree (BD) of the comprehensive energy system full-dimensional practical range security domain is maximized:
in the formula, xi 2 The maximum value of the balance degree of the full-dimensional practical interval security domain of the comprehensive energy system is represented;PIFR average,u 、
respectively representing the upper limit and the lower limit of the average value of the full-dimensional upper radius of the corresponding practical interval of all pipeline sections of the comprehensive energy system; m represents the number of system pipeline segments;
(3) optimization objective III: and (3) minimizing the planning cost of the comprehensive energy system:
in the formula, xi 3 Represents the minimum value of the system planning cost; c ex,a And C ex,b Respectively representing the capacity of the a-th reconfiguration device and the capacity of the b-th reconfiguration pipeline section; eta a 、η b Respectively representing the configuration cost coefficients of the a-th reconfiguration device and the b-th reconfiguration pipeline segment; n is a radical of hydrogen a And N b The number of reconfiguration devices and pipeline sections, respectively; len (a) b Indicating the length of the b-th reconfigured pipeline segment.
And the constraint condition of the multi-target planning is capacity expansion upper limit constraint.
The capacity expansion upper limit constraint is:
in the formula (I), the compound is shown in the specification,
and
representing the maximum capacity of the ith reconfiguration device and the b-th reconfiguration pipeline section, respectively.
With respect to step 102: the invention discloses a comprehensive energy system multi-target programming based on a practical interval security domain theory, which belongs to a mixed nonlinear optimization problem. Each group of solution in the Pareto optimal solution set represents optimized system planning information, including the capacity of each key element, the full-dimensional security domain BD after system planning, the IDREU size and the planning cost. And then solving the difference between the capacity of the key elements of the system after planning and the original capacity of the elements of the system, wherein the difference is not zero, and the element corresponding to the difference is the element for planning the specific capacity needing to be reconfigured. All Pareto optimal solutions together constitute a planning solution set of the system.
With respect to step 103: firstly, according to the requirements on the full-dimensional domain balance degree after system planning, the influence degree of renewable energy sources or planning cost, an obtained planning scheme is selected, and the method specifically comprises the following steps: for each set of planning schemes, the capacity of the system key elements (power feeders, heat pipelines, natural gas pipelines, transformers, gas turbines, CHP units, compressors and the like) is increased by reconfiguring the system key elements, so that the degree of safety domain equalization of the system practical range is increased and the degree of influence of randomness of renewable energy sources on the system practical range is reduced.
In summary, the embodiment of the present invention provides a comprehensive energy system multi-target planning method based on a practical interval security domain theory, which is helpful for improving system security and reducing the uncertainty influence degree of renewable energy.
The feasibility of the optimization method provided by the embodiments of the present invention is verified by the following specific experiments, which are described in detail in the following:
referring to a comprehensive energy system setting example scene with electric power, natural gas and heat power as energy demand in a certain engineering case, and obtaining a Pareto front edge of an optimal capacity configuration scheme set of the comprehensive energy system after multi-objective planning solution, as shown in fig. 1. The pareto optimal planning solution thus obtained is not replaceable. In general, as IDREU decreases, the absolute value of BD increases along with the cost.
Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-described embodiments of the present invention are merely provided for description and do not represent the merits of the embodiments.
The present invention is not limited to the above-described embodiments. The foregoing description of the specific embodiments is intended to describe and illustrate the technical solutions of the present invention, and the above specific embodiments are merely illustrative and not restrictive. Those skilled in the art can make many changes and modifications to the invention without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (1)
1. A multi-target planning method for an integrated energy system is based on a practical interval safety domain theory and is characterized by comprising the following steps:
constructing a comprehensive energy system multi-target planning model containing an optimization target and operation constraints based on the practical interval safety domain; the comprehensive energy system multi-target planning model specifically comprises the following steps:
(1) optimizing the target I: minimizing the impact of renewable energy uncertainty:
in the formula, xi 1 A minimum value representing a degree of influence of renewable energy uncertainty;PIFR m,u ,
respectively representing the upper and lower limits of the practical interval full-dimensional upper radius corresponding to the key pipeline segment m;
when the renewable energy is not accessed to the comprehensive energy system, all pipeline sections of the comprehensive energy system correspond to the average value of the practical full-dimensional radiuses;
(2) optimization objective II: the balance degree of the comprehensive energy system full-dimensional practical interval security domain is maximized:
in the formula, xi 2 The maximum value of the balance degree of the full-dimensional practical interval security domain of the comprehensive energy system is represented;PIFR average,u 、
respectively representing the upper limit and the lower limit of the average value of the radius on the corresponding practical interval whole dimension of all pipeline sections of the comprehensive energy system; m represents the number of system pipeline segments;
(3) optimization objective III: and (3) minimizing the planning cost of the comprehensive energy system:
In the formula, xi 3 Represents the minimum value of the system planning cost; c ex,a And C ex,b Respectively representing the capacity of the a-th reconfiguration device and the capacity of the b-th reconfiguration pipeline section; eta a 、η b Respectively representing the configuration cost coefficients of the a-th reconfiguration device and the b-th reconfiguration pipeline segment; n is a radical of a And N b The number of reconfiguration devices and pipeline sections, respectively; len (a) b Indicating the length of the b-th reconfiguration pipe segment;
the constraint condition of the multi-target planning is capacity expansion upper limit constraint;
the capacity expansion upper limit constraint is:
in the formula (I), the compound is shown in the specification,
and
respectively representing the maximum capacity of the ith reconfiguration device and the b-th reconfiguration pipeline section;
solving the multi-target planning model by adopting an NSGA-II algorithm to obtain an optimal system planning scheme set;
for each group of planning schemes, the capacity of the comprehensive energy system is increased by reconfiguring key elements of the comprehensive energy system, so that the balance degree of the practical interval security domain of the system is increased, and the influence degree of the system on the randomness of renewable energy sources is reduced; the key elements of the comprehensive energy system comprise a power feeder line, a heat distribution pipeline, a natural gas pipeline, a transformer, a gas turbine, a CHP unit and a compressor.
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