CN107391869B - Design method of alternating current-direct current hybrid micro-grid system - Google Patents
Design method of alternating current-direct current hybrid micro-grid system Download PDFInfo
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Abstract
A design method of an alternating current-direct current hybrid micro-grid system comprises the steps of randomly generating simulated operation data in different connection modes and different seasonal characteristics through a Monte Carlo method to obtain scene data for planning and designing; establishing an installation cost model and an operation cost model of various power supplies, establishing an alternating current-direct current hybrid micro-grid system optimization design model taking the minimum annual cash flow as an objective function, and simultaneously meeting various constraint conditions such as reliability and the like; solving an alternating current-direct current hybrid micro-grid system optimization design model containing integer discrete variables and operation continuous variables by adopting a mathematical decomposition method, decomposing a complex mixed integer nonlinear optimization model into a capacity configuration main problem, a reliability checker problem and a simulation operation optimization sub-problem, returning the sub-problems to a main problem reliability cut and an optimization operation cut, and solving through iteration; through the steps, the optimal design scheme of the alternating current-direct current series-parallel micro-grid system is obtained finally.
Description
Technical Field
The invention relates to a design method of a microgrid system, in particular to a design method of an alternating current-direct current series-parallel connection microgrid system.
Background
A micro power grid, called a micro grid for short, consists of a load and a micro power supply. The micro power supply is primarily responsible for the conversion of energy by the power electronics and provides the necessary control. Compared with an external large power grid, the microgrid is represented as a single controlled unit, and can meet the requirements of users on electric energy quality, power supply safety and the like; the microgrid realizes the localized utilization of renewable energy, and compared with the traditional power supply mode, the microgrid has no power transmission link, and is an efficient and environment-friendly resource integration utilization mode. With the continuous progress of renewable energy power generation technology, power electronic technology, information technology and internet technology, the micro-grid system is rapidly developed from few to many. However, at present, main research work of the microgrid focuses on aspects of operation control, energy management, system integration and the like, the microgrid planning design, particularly the design research of the alternating current-direct current hybrid type microgrid, is less, most of the microgrid planning design is designed manually by virtue of engineering experience, the planning design result is relatively rough, and the microgrid planning design is often not scientific and reasonable enough.
The micro-grid usually comprises a large number of direct current devices such as electric vehicles, lighting, communication, energy storage and the like, and meanwhile, power supplies such as solar photovoltaic power generation and the like are also in a direct current form, so that the intermediate conversion links can be greatly reduced by adopting a direct current power supply mode, and the energy utilization efficiency of the system is improved; meanwhile, in a direct current system, because the problems in the aspects of reactive power, harmonic wave and the like do not exist, a lot of losses are obviously reduced, higher electric energy quality can be simply obtained, and compared with a three-phase four-wire system of alternating current power distribution, the direct current power distribution only needs two wires, and the required construction cost is low. Therefore, the situation that alternating current power supply and direct current power supply coexist in the microgrid can be formed, and the alternating current power supply and the direct current power supply are matched with each other and complement each other.
In the alternating current-direct current hybrid micro-grid, the power supply of a ring network can be realized through a flexible direct current device, the power flow control capability of a system is greatly improved, and the utilization efficiency of a distributed power supply installation of the system is greatly improved; meanwhile, due to the double fluctuation of renewable energy sources and loads, whether the power supply installation condition is reasonable or not needs to be analyzed and evaluated through a large amount of simulation of a future operation scene. Therefore, the existing alternating current distribution planning design and economic evaluation method is difficult to adapt to new requirements, and a new solution is urgently needed for the design problem of the alternating current-direct current series-parallel micro-grid system.
At present, research on a design method of an alternating current and direct current hybrid micro-grid system at home and abroad is relatively few, the technology is relatively blank, a coupling relation among an alternating current and direct current micro-grid connection mode, power supply installed capacity and system dynamic operation is not considered in detail in design, and the design scheme is difficult to meet the requirements of economic operation and reliability.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and solve the problem that the design result is difficult to adapt to the future operation mode because the existing alternating-current and direct-current hybrid microgrid system is not designed in detail by considering the coupling relation among the alternating-current and direct-current microgrid connection mode, the installed capacity of a power supply and the dynamic operation of the system, and provides a design method of the alternating-current and direct-current hybrid microgrid system. On the premise of ensuring the design specification and safe and reliable design of the system, the invention optimizes and selects the connection mode of the alternating current-direct current microgrid and the installed capacity of the system power supply; optimization is carried out on the basis of establishing an optimization model reflecting the comprehensive investment economy and the operation economy of the system, the problems that the reliable operation of the system is influenced due to the fact that the installation is too large and the waste is caused or the installation is insufficient due to conventional design are solved, and the planning and design level of the micro-grid system is improved.
The alternating current-direct current hybrid micro-grid system comprises a renewable energy power generation device, a distributed power supply, an electric vehicle charging station, an energy storage device, an alternating current-direct current converter and the like, and is connected to an external power grid through a transformer. Renewable energy power generation and load in the alternating current-direct current hybrid micro-grid system have bidirectional fluctuation and randomness, operation scenes are complex and various, and how to handle the coupling relation among a system connection mode, installed capacity and a system operation mode is the key of system design.
The design method of the alternating current-direct current hybrid micro-grid system comprises the steps of generating a planning design scene, modeling the alternating current-direct current hybrid micro-grid system, solving an optimized design model and the like, and the connection mode and the installed power capacity of the alternating current-direct current micro-grid system are obtained in an optimized mode, and specifically the method comprises the following steps:
the planning design scene generation method comprises the steps of designing a feasible connection mode of an AC/DC micro-grid according to the size and distribution of system AC/DC loads, the curve and distribution of solar photovoltaic power generation, the curve and distribution of wind power generation and the curve and distribution of electric power for an electric vehicle charging station to obtain a connection mode set; meanwhile, in order to evaluate and calculate future complex operation scenes of the alternating-current and direct-current hybrid micro-grid, simulated operation data under different connection modes and different seasonal characteristics are randomly generated through a Monte Carlo method, and scene data for planning and designing are obtained.
The modeling of the alternating current-direct current hybrid micro-grid system needs to consider installation cost models and operation cost models of various power supplies, establish an alternating current-direct current hybrid micro-grid system optimization design model taking the minimum annual cash flow as a target function, and simultaneously meet various constraint conditions such as reliability. The annual cash flow in the objective function comprises four parts, wherein the first part is the annual reduced cost of the initial investment of the power supply to be selected and represents the influence of the investment cost on the power supply installation; the second part is the annual running cost of the generator set and represents the influence of the running state of the generator set on the installation; the third part is the cost of exchanging electric energy between the alternating current-direct current microgrid system and an external power grid, and represents the influence of the power grid state on the installation; the fourth part is the cost of abandoning wind and light, and represents the waste caused by the surplus of the renewable energy power generation machine. In order to ensure safe, reasonable and reliable operation of the system, the optimal design model should also satisfy the following constraint conditions: an electrical power balance constraint; the unit operation is limited, and the unit should operate between the minimum load rate and the maximum load rate; node voltage boundary constraints; carrying out power exchange constraint between the microgrid and an external power grid; machine set boundary constraint and integer constraint. By the method, a mixed integer nonlinear optimization design scheme of the alternating current-direct current series-parallel micro-grid system is finally obtained.
And in the model solving step, a mathematical decomposition method is used for solving an optimization design model of the alternating current-direct current hybrid micro-grid system containing integer discrete variables and operation continuous variables. The complex mixed integer nonlinear optimization model established by the invention contains investment-related integer variables and a large number of operation-related continuous variables, so that the model is difficult to solve by a conventional method. The invention applies a mathematical decomposition method to decompose a complex mixed integer nonlinear optimization model into a capacity configuration main problem, a reliability checker problem and a simulation operation optimization sub problem, the sub problems are returned to the main problem reliability cut and the optimization operation cut, and iterative solution is carried out. And finally, obtaining an optimal design scheme of the alternating current-direct current series-parallel micro-grid system.
The invention has the following characteristics:
(1) the invention provides a method for generating a planning design scene available for a system by adopting a Monte Carlo method by considering an alternating-current and direct-current connection mode and a complex operation scene of the system when designing an alternating-current and direct-current series-parallel micro-grid system.
(2) The method analyzes the relation between the installation cost and the operation cost of the alternating current-direct current hybrid micro-grid system, and establishes the annual cash flow model of the optimization design of the comprehensive evaluation system.
(3) According to the method, the optimization design model of the alternating current-direct current hybrid micro-grid system is decomposed into a capacity configuration main problem, a reliability tester problem and a simulation operation optimization sub-problem by using a mathematical decomposition method, the alternating current-direct current hybrid micro-grid system mixed integer nonlinear optimization design model is solved through iteration, and the method has good expandability.
Drawings
Fig. 1 is a schematic structural diagram of an alternating current-direct current series-parallel micro-grid system;
FIG. 2 is a flow chart of the steps involved in practicing the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings and the detailed description.
Fig. 1 shows an ac/dc series-parallel microgrid system as a main application object of the present invention. The system comprises an alternating current bus, a direct current bus, an alternating current load, a direct current load, solar photovoltaic power generation PV, wind power generation WT, a distributed power supply DG, an electric vehicle charging station EV, an energy storage unit ES, an alternating current-direct current converter and the like. The solar photovoltaic power generation, the wind power generation, the electric vehicle charging station, the energy storage unit and the direct current load are connected with the direct current bus to form a direct current power supply part, the distributed power supply, the alternating current load and the alternating current bus are connected to form an alternating current power supply part, the direct current power supply part and the alternating current power supply part are connected through an alternating current-direct current converter, an alternating current-direct current series-parallel micro-grid system is connected with an external power grid, and grid connection and double-mode island operation can be achieved.
The design method of the alternating current-direct current hybrid microgrid system comprises the steps of generating a planning design scene, modeling the alternating current-direct current hybrid microgrid system, solving an optimization design model and the like, and is shown in fig. 2: firstly, generating a planning design scene by using a Monte Carlo method according to the power supply and load conditions of the alternating-current and direct-current series-parallel micro-grid system, establishing a system optimization design model, decomposing the optimization design model into a capacity configuration main problem, a reliability sub-problem and a simulation operation sub-problem, and performing iterative solution to obtain an optimization design scheme of the alternating-current and direct-current series-parallel micro-grid system. The specific steps are detailed as follows:
(1) firstly, generating a planning design scene of an alternating current-direct current series-parallel micro-grid system;
according to the size and distribution of the alternating current and direct current loads of the microgrid system, the solar photovoltaic power generation curve and distribution, the wind power generation curve and distribution and the electric vehicle charging station power utilization curve and distribution which are obtained through prediction, a feasible connection mode of the alternating current and direct current microgrid is designed, and a connection mode set is obtained; meanwhile, in order to evaluate and calculate future complex operation scenes of the alternating-current and direct-current hybrid micro-grid, simulated operation data under different connection modes and different seasonal characteristics are randomly generated through a Monte Carlo method, and scene data for planning and designing are obtained.
(2) Establishing an alternating current-direct current series-parallel connection microgrid system model;
1) and establishing an installation cost model and an operation cost model of various power supplies.
Solar photovoltaic power generation output model:
in the formula, ppvOutputting power for solar photovoltaic power generation; pSTCIs the maximum test power under standard test conditions; gSTCThe illumination intensity under standard test conditions; gTThe intensity of light actually incident on the photovoltaic panel; k is a power temperature coefficient; t iscThe working temperature of the battery plate; t isrFor reference temperature, 25 ℃ was taken.
Wind power generation power output model:
in the formula: p is a radical ofwtOutputting power for wind power generation; v. ofinFor cutting into the wind speed, vnRated wind speed, voutCutting out the wind speed; p is a radical ofwtnRated power for the fan; a iswt、bwt、cwt、dwtFitting parameters for a wind speed-power curve.
Installing and operating cost model of the micro gas turbine:
F(pmt)＝αmtpmt+βmt
in the formula: f (p)mt) Fuel consumption cost for micro gas turbines; p is a radical ofmtPower output for micro gas turbine αmt、βmtIs a fitting coefficient for fuel consumption.
The installed cost of the solar photovoltaic power generation, the wind power generation and the micro gas turbine is calculated according to the unit installed cost multiplied by the installed capacity, and the equal annual cost calculation method of the installed cost comprises the following steps:
CAcap＝Ccap*CRF(γ,k)-Cs*SFF(γ,k)
in the formula: cAcapAnnual equivalent costs for equipment installation costs; ccapCost for equipment installation; csThe device is the final residual value of the equipment in the settling period; k is the life span of the equipment; CRF (γ, k) is the capital recovery factor; SFF (γ, k) is the repayment fund coefficient; gamma is the actual interest rate; gamma' is the nominal interest rate; f is the annual flatulence rate.
2) And establishing an alternating current-direct current hybrid micro-grid system optimization design model taking the minimum annual cash flow as an objective function, and simultaneously meeting various constraint conditions such as reliability and the like.
An objective function:
in the formula, Min represents minimization; cmInstallation cost per unit capacity of power supply m; pmThe installed capacity of the power supply m; c. Ce(t) is the time-of-use electricity price of the power grid at t; p is a radical ofe(t) inputting the electric power of the microgrid from the power grid when t is the time; p is a radical ofloss(t) abandoning wind and optical power when t is; m is the number of power supplies; t is the number of operating hours throughout the year. The first part in the objective function is the annual conversion cost of the initial investment of the power supply to be selected, and represents the influence of the investment cost on the power supply installation; the second part is annual operation and maintenance cost of the generator set, and represents the influence of the running state of the generator set on the installation; the third part is the cost of exchanging electric energy between the alternating current-direct current microgrid system and an external power grid, and represents the influence of the power grid state on the installation; the fourth part is the cost of abandoning wind and light, and represents the waste caused by the surplus of the renewable energy power generation machine.
Constraint conditions are as follows:
time-sharing electric power balance constraint:
pmt(t)+ppv(t)+pwt(t)+pe(t)＝pl(t)+ploss(t)
wherein pl (t) is the electric power of the load at t; p is a radical ofpv(t) the solar photovoltaic power generation output power when t is; p is a radical ofwtAnd (t) is the output power of the wind power generation when t is the time.
And (4) limiting power supply operation:
pm min≤pm(t)≤pm max
pm(t)≤Pm
in the formula, pm(t) is the power output of power supply m at t; p is a radical ofm maxMaximum electric power output limit, p, for power supply mm minIs the minimum electrical power output limit of the power supply m.
Node voltage boundary constraint:
in the formula, vac_iIs the voltage at the ac node i and,
the upper boundary of the ac node i is equal to,
is the lower boundary of the AC node i; v. ofdc_iIs the voltage at the dc node i,
is the upper boundary of the dc node i,
is the lower boundary of dc node i.
External grid interface power limit: the microgrid can only absorb power from an external power grid and is not allowed to transmit electric energy.
0≤pe(t)≤pe max
In the formula, pe maxTo maximize the electrical power that is allowed to be drawn from the external grid.
Power supply installed boundary and integer constraint:
in the formula, PmIn order to install the capacity of the machine,
which is the upper boundary of the installed capacity,
the lower bound of installed capacity.
(3) Solving an optimization design model of the alternating current-direct current series-parallel micro-grid system;
the invention adopts a mathematical decomposition method to solve an optimization design model of an alternating current-direct current hybrid micro-grid system containing integer discrete variables and operation continuous variables, decomposes a complex mixed integer nonlinear optimization model into a capacity configuration main problem, a reliability checker problem and a simulation operation optimization sub-problem, returns the sub-problems to a main problem reliability cut and an optimization operation cut, and solves the problems through iteration, and concretely comprises the following steps:
firstly, the optimization design model of the alternating current-direct current series-parallel micro-grid system in the step (2) is arranged into the following form:
an objective function:
Min f(x1,…,xn；y1,…,yw)
constraint conditions are as follows:
hk(x1,…,xn；y1,…,yw)＝0；k＝1,…,q
gl(x1,…,xn；y1,…,yw)≤0；l＝1,…,r
in the formula, f (x)1,…,xn；y1,…,yw) The system is an objective function and represents the annual cash flow of the alternating current-direct current series-parallel micro-grid system; x is the number ofiThe variables are optimized for the power supply installed capacity integer,
the upper bound of the variables is optimized for the power supply installed capacity integer,
the lower boundary of the power supply installed capacity integer optimization variable is defined, and n is the number of the power supply installed capacity integer optimization variables; y isiThe variables are optimized for the power supply operating power output,
the upper bound of variables is optimized for the power supply operating power output,
outputting the lower boundary of the optimized variable for the power supply running power, wherein w is the number of the optimized variables for the power supply running power; h iskIs an equality constraint, the number of which is q; glIs an inequality constraint, its number is r.
1) The capacity allocation main problem is expressed as follows:
an objective function:
Min α
constraint conditions are as follows:
αdown≤α
in the formula (I), the compound is shown in the specification,
annual cash flow f (x) for AC/DC series-parallel micro-grid system1,…,xn；y1,…,yw) The k-th iteration function value of (1), xiThe variables are optimized for the power supply installed capacity integer,
the upper bound of the variables is optimized for the power supply installed capacity integer,
the lower boundary of the power supply installed capacity integer optimization variable is defined, and n is the number of the power supply installed capacity integer optimization variables; y isiOptimizing variables for power supply running power output, w is the number of the optimizing variables for power supply running power output, α is the optimization target of the decomposed main problem, αdownIts lower boundary; lambda [ alpha ]iSolving the obtained dual variable values for the subproblems;
solving the obtained dual variable value for the kth simulation operation subproblem; superscript k represents the kth iteration; p represents the number of iterations.
The solution result of the main problem is
And α(p)The superscript p represents the p-th iteration,
as a known quantity for use in the simulation run subproblem.
2) The reliability checker problem is represented as follows:
checking whether the main problem of capacity configuration meets the following constraint conditions:
wherein χ is a system reliability evaluation coefficient; max (pl (t)) is the system maximum load.
And if the reliability test is not met, adding the constraint conditions as reliability segments into the main capacity configuration problem for re-optimization calculation, and if the reliability test is met, performing the next calculation.
3) The simulation run optimization sub-problem is represented as follows: :
an objective function:
Min f(x1,…,xn；y1,…,yw)
constraint conditions are as follows:
hk(x1,…,xn；y1,…,yw)＝0；k＝1,…,q
gl(x1,…,xn；y1,…,yw)≤0；l＝1,…,r
in the formula, hkIs an equality constraint, the number of which is q; glIs inequality constraint, the number of which is r; y isiThe variables are optimized for the power supply operating power output,
are each yiUpper and lower boundaries of (a); x is the number ofiThe variables are optimized for the power supply installed capacity integer,
solving the p iteration of the main problem; lambda [ alpha ]iSolving the obtained dual variable values for the subproblems; p represents the number of iterations.
The solution result of the simulation run subproblem is
And
as a known quantity for the capacity allocation main problem.
The optimal design scheme of the alternating current-direct current series-parallel micro-grid system can be obtained through the steps (1) to (3).
Claims (5)
1. A design method of an alternating current-direct current series-parallel connection microgrid system is characterized by comprising the following steps: the design method comprises the steps of generating a planning design scene, modeling the alternating current-direct current hybrid microgrid system and solving an optimization design model; the planning and designing scene generating step is that simulation operation data under different connection modes and different seasonal characteristics are randomly generated through a Monte Carlo method, and scene data used for planning and designing are obtained; the modeling step of the alternating current-direct current hybrid micro-grid system is to establish an installation cost model and an operation cost model of various power supplies, establish an alternating current-direct current hybrid micro-grid system optimization design model taking the minimum annual cash flow as a target function, and simultaneously meet the constraint conditions of reliability; the optimal design model solving step is that a mathematical decomposition method is used for solving an optimal design model of the alternating current-direct current hybrid micro-grid system containing integer discrete variables and operation continuous variables, a complex mixed integer nonlinear optimization model is decomposed into a capacity configuration main problem, a reliability checker problem and a simulation operation optimization sub-problem, and the sub-problems are returned to a main problem reliability cut and an optimal operation cut and are solved through iteration; through the steps, the optimal design scheme of the alternating current-direct current series-parallel micro-grid system is finally obtained;
in the modeling step of the alternating current-direct current hybrid microgrid system, an objective function of the mixed integer nonlinear optimization design model of the alternating current-direct current hybrid microgrid system comprises four parts, wherein the first part is the annual conversion cost of the initial investment of the power supply to be selected and represents the influence of the investment cost on the power supply installation; the second part is the annual running cost of the generator set and represents the influence of the running state of the generator set on the installation; the third part is the cost of exchanging electric energy between the alternating current-direct current microgrid system and an external power grid, and represents the influence of the power grid state on the installation; the fourth part is the cost of wind and light abandonment, and represents the waste caused by the surplus of the renewable energy power generation machine; the objective function is expressed as follows:
in the formula, CAcapAnnual equivalent costs for equipment installation costs; cmInstallation cost per unit capacity of power supply m; pmThe installed capacity of the power supply m; f (p)mt(t)) is the fuel consumption cost at the micro gas turbine t; p is a radical ofmt(t) is the output power at t of the micro gas turbine; c. Ce(t) is the time-of-use electricity price of the power grid at t; p is a radical ofe(t) inputting the electric power of the microgrid from the power grid when t is the time; p is a radical ofloss(t) abandoning wind and optical power when t is; m is the number of power supplies; t is the annual operating hours;
in the modeling step of the alternating current-direct current hybrid microgrid system, the constraint condition of the mixed integer nonlinear optimization design model of the alternating current-direct current hybrid microgrid system comprises electric power balance constraint; the unit operation is limited, and the unit should operate between the minimum load rate and the maximum load rate; node voltage boundary constraints; carrying out power exchange constraint between the microgrid and an external power grid; unit installation boundary constraint and integer constraint; the constraint expression is as follows:
time-sharing electric power balance equation constraint:
pmt(t)+ppv(t)+pwt(t)+pe(t)＝pl(t)+ploss(t)
in the formula, ppv(t) the solar power generation power when t is t; p is a radical ofwt(t) the solar power generation power when t is t; pl (t) is the electrical power of the load at t; p is a radical ofmt(t) is the output power at t of the micro gas turbine; p is a radical ofe(t) inputting the electric power of the microgrid from the power grid when t is the time; p is a radical ofloss(t) abandoning wind and optical power when t is;
the power supply operation limit inequality constrains:
pmmin≤pm(t)≤pmmax
pm(t)≤Pm
in the formula, pm(t) is the power output of power supply m at t; p is a radical ofmmax、pmminMaximum and minimum electrical power output limits for power supply m;
node voltage boundary inequality constraint:
in the formula, vac_iIs the voltage at the ac node i and,
the upper and lower boundaries thereof; v. ofdc_iIs the voltage at the dc node i,
the upper and lower boundaries thereof;
external grid interface power inequality constraints: the micro-grid can only absorb power from an external power grid and does not allow the electric energy to be transmitted backwards;
0≤pe(t)≤pemax
in the formula, pemaxElectric power absorbed from the external grid is maximally allowed;
the power supply installation boundary inequality constraint is as follows:
In the formula, PmIn order to be the capacity of the power source,
the upper and lower boundaries thereof.
2. The design method of the alternating current-direct current series-parallel connection microgrid system according to claim 1, characterized in that: the optimization design model of the alternating current-direct current series-parallel micro-grid system comprising the objective function and the constraint conditions thereof is arranged into the following form:
an objective function:
Min f(x1,…,xn；y1,…,yw)
constraint conditions are as follows:
hk(x1,…,xn；y1,…,yw)＝0；k＝1,…,q
gl(x1,…,xn；y1,…,yw)≤0；l＝1,…,r
in the formula, f (x)1,…,xn；y1,…,yw) The system is an objective function and represents the annual cash flow of the alternating current-direct current series-parallel micro-grid system; x is the number ofiThe variables are optimized for the power supply installed capacity integer,
the upper bound of the variables is optimized for the power supply installed capacity integer,
the lower boundary of the power supply installed capacity integer optimization variable is defined, and n is the number of the power supply installed capacity integer optimization variables; y isiThe variables are optimized for the power supply operating power output,
the upper bound of variables is optimized for the power supply operating power output,
outputting the lower boundary of the optimized variable for the power supply running power, wherein w is the number of the optimized variables for the power supply running power; h iskIs an equality constraint, the number of which is q; glIs an inequality constraint, its number is r.
3. The design method of the alternating current-direct current series-parallel connection microgrid system according to claim 1 or 2, characterized in that: in the step of solving the optimization design model of the alternating current-direct current hybrid microgrid system, the used mathematical method decomposes the optimization design model of the alternating current-direct current hybrid microgrid system, and the solved main problem of capacity configuration has the following expression form:
an objective function:
Minα
constraint conditions are as follows:
αdown≤α
in the formula (I), the compound is shown in the specification,
for the objective function f (x)1,…,xn；y1,…,yw) The kth iteration function value is the kth iteration function value of the annual cash flow of the AC-DC series-parallel microgrid system, xiThe variables are optimized for the power supply installed capacity integer,
the upper bound of the variables is optimized for the power supply installed capacity integer,
the lower boundary of the power supply installed capacity integer optimization variable is defined, and n is the number of the power supply installed capacity integer optimization variables; y isiOptimizing variables for power supply running power output, w is the number of the optimizing variables for power supply running power output, α is the optimization target of the decomposed main problem, αdownIts lower boundary; lambda [ alpha ]iSolving the obtained dual variable values for the subproblems;
solving the obtained dual variable value for the kth simulation operation subproblem; superscript k represents the kth iteration; p represents the number of iterations; the solution result of the main problem is
And α(p)The superscript p represents the p-th iteration,
as a known quantity for use in the simulation run subproblem.
4. The design method of the alternating current-direct current series-parallel connection microgrid system according to claim 1 or 2, characterized in that: in the step of solving the optimization design model of the alternating current-direct current series-parallel micro-grid system, the expression form of the used reliability tester problem is as follows:
checking whether the main problem of capacity configuration meets the following constraint conditions:
wherein χ is a system reliability evaluation coefficient; max (pl (t)) is the maximum load of the system, xiOptimizing variables for the installed capacity integer; and if the reliability test is not met, adding the constraint conditions as reliability segments into the main capacity configuration problem for re-optimization calculation, and if the reliability test is met, performing simulation operation optimization sub-problem calculation.
5. The design method of the alternating current-direct current series-parallel connection microgrid system according to claim 1 or 2, characterized in that: in the step of solving the optimization design model of the alternating current-direct current hybrid microgrid system, the expression form of the simulation operation optimization subproblem obtained by using a mathematical method for decomposition is as follows:
an objective function:
Min f(x1,…,xn；y1,…,yw)
constraint conditions are as follows:
hk(x1,…,xn；y1,…,yw)＝0；k＝1,…,q
gl(x1,…,xn；y1,…,yw)≤0；l＝1,…,r
in the formula, hkFor equality constraint, number thereofIs q; glIs inequality constraint, the number of which is r; y isiThe variables are optimized for the power supply operating power output,
are each yiUpper and lower boundaries of (a); x is the number ofiThe variables are optimized for the power supply installed capacity integer,
solving the p iteration of the main problem; lambda [ alpha ]iSolving the obtained dual variable values for the subproblems; p represents the number of iterations; the solution result of the simulation run subproblem is
And
as a known quantity for the capacity allocation main problem.
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