CN114844119A - Energy storage power generation installation and capacity optimal configuration method and system - Google Patents
Energy storage power generation installation and capacity optimal configuration method and system Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract
An energy storage power generation installed and capacity optimal configuration method and system comprises the following steps: inputting the obtained power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model, and calculating to obtain an annual electricity discharge sequence of the new energy; calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence; substituting the minimum proportion coefficient of waste electricity consumption and the new energy annual waste electricity sequence into a pre-constructed energy storage power generation installed machine and capacity optimization model to obtain the energy storage power generation installed machine and capacity requirements meeting the new energy utilization rate; the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function and setting constraint conditions when the new energy utilization rate is met. Random fluctuation of new energy output is fully considered, and the problem of model solution caused by simultaneous optimization of new energy output, energy storage power generation installation, capacity and the like at one time is solved.
Description
Technical Field
The invention relates to the technical field of new energy and energy storage power generation, in particular to an energy storage power generation installation and capacity optimal configuration method and system.
Background
After the high-proportion new energy is connected into the power grid, the peak load and frequency modulation pressure of the power grid is increased. The large-scale grid-connected operation of the new energy enables the supply and demand sides to have the characteristic of random fluctuation, the output of the conventional power supply needs to change along with the load, the output fluctuation of the new energy needs to be balanced, the regulation pressure of the conventional power supply is increased, and the balancing difficulty of a power grid is increased. The randomness and the volatility of new forms of energy output can be stabilized to the electrochemistry energy storage, and the period of abandoning electricity at the new forms of energy takes place promptly, and the energy storage charges, and the period of abandoning electricity at the new forms of energy does not take place, and the energy storage discharges. The electrochemical energy storage is configured to solve one of the important technical means of solving the problem of new energy consumption.
At present, the investment cost of electrochemical energy storage is still relatively high, two factors of economy and new energy consumption need to be considered when electrochemical energy storage is configured, and reasonable optimal configuration of energy storage scale is realized on the premise of ensuring the utilization rate of new energy. The energy storage optimization configuration needs to determine two factors of an energy storage power generation installation and an energy storage capacity, wherein the energy storage power generation installation, namely the rated power value of an energy storage inverter, represents the maximum charging and discharging power of energy storage at each time interval; the energy storage capacity represents the maximum value of the stored electric quantity. The installation and capacity of the energy storage and power generation have influence on accepting new energy and electricity abandonment, such as: when the abandoned electric power of the new energy is large, if the energy storage power generation installation is insufficient, part of abandoned electric power cannot be consumed; when long-time electricity abandonment occurs, if the energy storage capacity is small, the energy can not be abandoned after the energy storage is too early fully charged. However, the cost of energy storage investment is increased due to the overlarge power generation installed capacity, so that the balance between the energy storage power generation installed capacity and the energy storage capacity needs to be found under the condition of meeting the requirement of new energy utilization rate, and the most economic energy storage configuration scheme is obtained.
The time sequence production simulation technology is a commonly used technical method in the planning problem, and random fluctuation of new energy output, system power and electric quantity balance and power supply regulation can be fully considered through 8760h per year time section operation optimization simulation. However, for large-scale power grids such as provincial power grids, the number of power supply units is large, the power grid structure is complex, when energy storage is optimally configured by adopting a 8760h time sequence production simulation method all the year round, various factors such as system operation, conventional power supply unit combination, energy storage charging and discharging states and new energy consumption need to be considered, and the direct solving difficulty of the model is extremely high.
To solve this problem, the existing methods generally adopt the following methods: firstly, only the typical sunrise force of the new energy in each season or each month is taken as input, so the time range considered is greatly reduced, the problem solving difficulty is simplified, but the typical sunrise force curve of the new energy cannot completely reflect the random fluctuation of the new energy output, and the scientificity of an energy storage planning result can be influenced. Secondly, a plurality of energy storage configuration schemes are given, year-round time sequence production simulation calculation is carried out on each configuration scheme to calculate the corresponding new energy utilization rate condition, and then the result of each scene is compared to carry out preferential selection. However, because both the installed capacity and the installed capacity of the energy storage and power generation are configurable parameters, there are infinite possible energy storage configuration schemes, and because all the possible schemes cannot be exhausted, the method cannot obtain an optimal configuration result. In addition, the energy storage configuration needs to simultaneously realize the optimization of the power generation installation machine and the capacity, and part of methods optimize the energy storage capacity in a mode of setting the energy storage duration, so that although the problem is simplified, the flexibility of an energy storage configuration scheme is greatly limited due to the fact that the ratio between the energy storage capacity and the power generation installation machine is kept fixed, and the result is inaccurate.
Disclosure of Invention
In order to solve the problems that the random fluctuation of new energy output is not fully considered and the optimal power generation installed capacity and capacity of stored energy are difficult to obtain at one time in the prior art, the invention provides an energy storage power generation installed capacity and capacity optimal configuration method, which comprises the following steps:
inputting the obtained power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandonment sequence of the new energy;
calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence;
substituting the minimum proportion coefficient of electricity abandonment consumption and the new energy annual electricity abandonment sequence into a pre-constructed energy storage power generation installed machine and capacity optimization model to obtain the energy storage power generation installed machine and capacity requirements meeting the new energy utilization rate;
the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of the power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions;
the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function when the utilization rate of new energy is met and setting constraint conditions for the objective function.
Preferably, the building of the energy storage and power generation installation and capacity optimization model comprises:
setting energy storage capacity constraint, energy storage system charge and discharge power constraint, energy storage charge state constraint, energy storage duration constraint and electricity abandonment consumption constraint for the objective function by taking the minimum economic cost of energy storage power generation installation and capacity as the objective function;
and constructing an energy storage power generation installation and a capacity optimization model by the objective function and the energy storage capacity constraint, the energy storage system charge and discharge power constraint, the energy storage charge state constraint, the energy storage duration constraint and the electricity abandoning and consumption constraint.
Preferably, the step of bringing the minimum proportion coefficient of electricity abandonment consumption and the new energy annual electricity abandonment sequence into a pre-constructed energy storage and power generation installation and capacity optimization model to obtain the energy storage and power generation installation and capacity requirements meeting the new energy utilization rate includes:
and inputting the new energy annual power abandoning sequence into the energy storage power generation installed capacity optimization model, and solving by using a mathematical programming solver to obtain the optimal energy storage power generation installed capacity and capacity.
Preferably, the new energy annual energy abandonment sequence is calculated according to the following formula:
P c ＝{P c (t),t＝1,2,…,T}
in the formula, P c Is a new energy whole year electricity abandoning sequence, P c And (T) the electric power of the new energy abandoned in the period T, the period T and the number of all the time periods in the whole year.
Preferably, the electricity abandonment consumption minimum proportionality coefficient is calculated according to the following formula:
in the formula, alpha is the lowest proportion coefficient of electricity abandonment and consumption, r is the utilization rate of new energy, P 0 (t) is the theoretical power sequence, P c And (T) is a new energy power abandoning sequence, and T is the number of all time periods in the whole year.
Preferably, the objective function of the energy storage and power generation installed and capacity optimization model is calculated according to the following formula:
min c 1 E max +c 2 P max
in the formula, c 1 Cost per unit energy storage capacity, E max To energy storage capacity, c 2 For unit energy storage installation cost, P max And the energy storage power generation machine is used.
Preferably, the curtailment consumption constraint is calculated according to the following formula:
in the formula, P ch (t) is the charging power of the stored energy at the moment t, alpha is the lowest proportional coefficient of the abandoned electricity consumption, P c And (T) is a new energy power abandoning sequence, and T is the number of all time periods in the whole year.
Based on the same invention concept, the invention also provides an energy storage power generation installed and capacity optimal configuration system, which comprises:
the calculation sequence module is used for inputting the acquired power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandonment sequence of the new energy;
the calculation coefficient module is used for calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence;
the model solving module is used for substituting the electricity abandonment minimum proportion coefficient and the new energy annual electricity abandonment sequence into a pre-constructed energy storage and power generation installation and capacity optimization model to obtain the energy storage and power generation installation and capacity requirements meeting the new energy utilization rate;
the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of the power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions;
the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function when the utilization rate of new energy is met and setting constraint conditions for the objective function.
Preferably, the model solving module is specifically configured to:
and inputting the new energy annual power abandoning sequence into the energy storage power generation installed capacity optimization model, and solving by using a mathematical programming solver to obtain the optimal energy storage power generation installed capacity and capacity.
Preferably, the calculation coefficient module calculates the electricity abandonment consumption lowest proportionality coefficient by the following formula:
in the formula, alpha is the lowest proportion coefficient of electricity abandonment and consumption, r is the utilization rate of new energy, P 0 (t) is the theoretical power sequence, P c And (T) is a new energy power abandoning sequence, and T is the number of all time periods in the whole year.
Compared with the prior art, the invention has the beneficial effects that:
an energy storage power generation installed and capacity optimal configuration method and system comprises the following steps: inputting the obtained power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandonment sequence of the new energy; calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence; substituting the minimum proportion coefficient of electricity abandonment consumption and the new energy annual electricity abandonment sequence into a pre-constructed energy storage power generation installed machine and capacity optimization model to obtain the energy storage power generation installed machine and capacity requirements meeting the new energy utilization rate; the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of a power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions; the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function and setting constraint conditions for the objective function when the utilization rate of new energy is met; the invention considers the random fluctuation of the new energy output by step-by-step calculation, and also considers the factors of energy storage investment economy, new energy consumption, thermal power unit combination optimization, model calculation efficiency and the like, and can directly obtain the optimal power generation installed capacity and capacity of the stored energy.
Drawings
FIG. 1 is a flow chart of an energy storage and power generation installation and capacity optimization configuration method of the invention;
FIG. 2 is a flow chart of a method for optimizing stored energy power and capacity to facilitate new energy consumption according to the present invention;
fig. 3 is a power abandon sequence diagram of the new energy 8760h of the present invention;
fig. 4 is a graph of the electric power abandon and the energy storage charge-discharge power of the new energy source before and after the energy storage configuration within 2 consecutive days.
Detailed Description
In order to promote the consumption of new energy and realize the optimal electrochemical energy storage rated capacity and rated power, the invention calculates the electricity abandoning sequence of the new energy by two-step optimization, firstly, not considering the energy storage access and establishing a new energy time sequence production simulation optimization model; then, calculating the scale setting of the electric quantity which needs to be recovered and consumed by using the stored energy in the electricity abandoning sequence based on the new energy electricity abandoning sequence and in combination with a new energy utilization rate target; and finally, establishing an energy storage and power generation installed and capacity optimization model based on the new energy abandoned power, and solving the model to obtain the scale of the energy storage and power generation installed and capacity under the minimum economic cost. For a better understanding of the present invention, reference is made to the following description taken in conjunction with the accompanying drawings and examples.
Example 1:
an energy storage and power generation installed and capacity optimal configuration method is shown in fig. 1, and comprises the following implementation processes:
step 1, inputting the acquired power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandoning sequence of the new energy;
step 2, calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence;
step 3, bringing the minimum proportion coefficient of electricity abandonment consumption and the new energy annual electricity abandonment sequence into a pre-constructed energy storage power generation installation and capacity optimization model to obtain the energy storage power generation installation and capacity requirements meeting the new energy utilization rate;
the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of the power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions;
the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function when the utilization rate of new energy is met and setting constraint conditions for the objective function.
The energy storage and power generation installation and capacity optimization configuration method of the present invention will be described in detail with reference to fig. 2.
In the step 1, inputting the obtained power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain energy storage, and calculating to obtain an annual electricity abandoning sequence of the new energy, specifically comprising:
and performing time sequence production simulation of new energy without electrochemical energy storage according to the parameters of the power system under a given scene. And establishing a new energy time sequence production simulation optimization model without energy storage, wherein the model takes the maximum consumption of the new energy of the whole network as an optimization target, and considers power grid power balance constraint, system standby demand constraint, various power supply operation constraints, section transmission safety constraint and the like.
Annual theoretical power sequence P with new energy 0 ＝{P 0 (T), the T is 1,2, …, T }, the electrical load, the power grid and the power supply parameter are used as input, and the new energy power abandoning sequence P is obtained through annual time sequence production simulation optimization calculation c ＝P c (T), T ═ 1,2, …, T }, where P is c (T) electric power abandonment of new energy in T period, T is the number of all the time periods in the whole year, P c Representing a new energy annual power abandonment sequence set. The annual time sequence production simulation optimization calculation can adopt the existing cycle-by-cycle calculation and other modes, and the solving efficiency is improved.
In step 2, calculating to obtain a minimum proportion coefficient of electricity curtailment consumption based on the new energy annual electricity curtailment sequence and the new energy annual theoretical power sequence, specifically including:
based on new forms of energy abandon electricity sequence P c Acquiring a charge-discharge state sequence x ═ { x (T), T ═ 1,2, …, T } stored in each time period, wherein the charge-discharge state x (T) at the time T is equal to P of the abandoned electric power at the time T c The sign function of (t) is as follows:
x(t)＝sgn(P c (t))
wherein the sign function is:
the meaning of the charging and discharging state is that when the system has new energy and abandons electricity (P) c (t)>0) The energy storage charging and discharging state is set to be 1, which indicates that charging can be carried out; when the system has no new energy and abandons the electricity (P) c And (t) ═ 0), wherein the stored energy charging and discharging state is 0, and the stored energy can be discharged.
Based on new forms of energy abandon electricity sequence P c And theoretical power sequence P 0 And calculating the lowest proportionality coefficient alpha which needs to be absorbed in the electric quantity of the abandoned new energy under the condition of meeting the current r of the utilization rate of the new energy:
in step 3, the minimum proportion coefficient of electricity abandonment consumption and the new energy annual electricity abandonment sequence are brought into a pre-constructed energy storage and power generation installation and capacity optimization model to obtain the energy storage and power generation installation and capacity requirements meeting the new energy utilization rate, and the method specifically comprises the following steps:
and establishing an energy storage power generation installation and capacity optimization model based on the annual electricity abandoning sequence and the lowest proportion coefficient of electricity abandoning and consumption of new energy, and calculating the most economic power generation installation and capacity requirements of energy storage under the condition of meeting the utilization rate of the new energy.
The objective function of the energy storage power generation installation and capacity optimization model is as follows:
min c 1 E max +c 2 P max
in the formula: e max Representing the energy storage capacity as an optimization variable; p max Representing an energy storage power generation machine as an optimized variable; c. C 1 Representing cost per unit of energy storage capacity, c 2 And the unit energy storage power generation installation cost is shown.
The constraint conditions include:
(1) energy storage capacity constraint:
0≤E(t)≤E max
and E (t) is the electric energy storage quantity of the stored energy at the moment t, and is an optimization variable. The constraint indicates that the stored energy capacity E (t) at time t cannot be greater than the stored energy capacity E max 。
(2) And (3) energy storage system charge and discharge power constraint:
P ch (t) represents the charging power of the stored energy at the moment t, and is an optimization variable; p dc And (t) represents the discharge power of the stored energy at the moment t, and is an optimization variable. The constraint represents the charging power P at time t ch (t) and discharge power P dc (t) not exceeding its generating set P max And is determined by the charge-discharge state x (t), and the charge and discharge power is not simultaneously positive. From step 2, the charge-discharge state x (t) at the time of energy storage t is determined in advance and is a known quantity. When x (t) is equal to 1, the charging power P ch (t) is from 0 to P max Taking values between, i.e. charging can be carried out, and discharging power P dc (t) constrained to 0; on the contrary, when x (t) is equal to 0, the discharge power P dc (t) is from 0 to P max Value of interval, charging power P ch (t) is constrained to 0.
(3) Energy storage state of charge constraint:
the constraint describes the relationship between the amount of stored electricity and the charge and discharge power at the time of the energy storage adjacency. Namely: e (t) represents the energy storage capacity stored at the moment t, and is an optimized variable; e (t-1) represents the stored energy at the t-1 moment, and is an optimized variable; η represents the charge-discharge efficiency of stored energy.
(4) Energy storage time length constraint:
nP max ≤E max
the constraint indicates that the energy storage duration is greater than a given minimum energy storage duration, and n indicates the minimum energy storage duration.
(5) And (3) limiting the electricity abandoning consumption:
the constraint indicates that the electricity storage quantity of the energy storage year should be larger than the lowest proportion of the consumption of the new energy abandoned quantity.
Because the charging and discharging states of the stored energy are determined in advance, the stored energy power generation installation and capacity optimization model is a linear programming model and does not contain integer variables.
And calling a mathematical programming solver, solving an energy storage power generation installed machine and capacity optimization model, and obtaining the optimal power generation installed machine and capacity of the energy storage.
And carrying out energy storage optimization configuration calculation based on a certain provincial power grid. Firstly, by establishing a time sequence production simulation optimization model of 8760h all year round, under the condition of not considering energy storage access, a power abandoning sequence of new energy 8760h all province is obtained through optimization calculation, and the power abandoning sequence is shown in an attached figure 3. According to statistics, under the condition of not configuring energy storage, the consumption of new energy in the whole province is 407.6 hundred million kilowatt hours, the electricity discard amount is 52.1 million kilowatt hours, and the utilization rate of the new energy is 88.7%. The target of the utilization rate of the new energy after the energy storage is configured is set to be 95%, the target of the utilization rate of the new energy to be 95% can be known to be met through calculation, at least 29.1 hundred million kilowatt-hour electricity abandonment is needed to be consumed, and the minimum proportion coefficient of the new energy electricity abandonment is 0.559.
Setting the cost of the energy storage and power generation installation to be 500 yuan/kilowatt, the capacity cost to be 2000 yuan/kilowatt hour, and the charging and discharging efficiency to be 95%, establishing an energy storage and power generation installation and capacity optimization model based on a power abandoning sequence of new energy of 8760h all the year, and obtaining the optimal power generation installation of 2924MW, the optimal capacity to be 11221MWh and the reduced energy storage time to be 3.8h through optimization solution. Fig. 4 shows that the new energy electric power abandon and the stored energy charge-discharge power before and after the stored energy is configured in 2 consecutive days, and the stored energy can be charged in the new energy electric power abandon period and discharged in the electric power abandon period, so that the new energy electric power abandon consumption is realized. Through statistics, the production simulation calculation time is 8.7 minutes when the energy storage is not configured, the calculation time of the energy storage power generation installation and the capacity optimization model is 0.75 minute, and the total time length can meet the engineering practicability requirement.
Example 2:
an energy storage and power generation installed and capacity optimal configuration system comprising:
the calculation sequence module is used for inputting the acquired power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandonment sequence of the new energy;
the calculation coefficient module is used for calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence;
the model solving module is used for substituting the electricity abandonment minimum proportion coefficient and the new energy annual electricity abandonment sequence into a pre-constructed energy storage and power generation installation and capacity optimization model to obtain the energy storage and power generation installation and capacity requirements meeting the new energy utilization rate;
the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of the power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions;
the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function when the new energy utilization rate is met and setting constraint conditions for the objective function.
A calculate sequence module, specifically configured to:
and performing time sequence production simulation of new energy without electrochemical energy storage according to the parameters of the power system under a given scene. And establishing a new energy time sequence production simulation optimization model without energy storage, wherein the model takes the maximum consumption of the new energy of the whole network as an optimization target, and considers power grid power balance constraint, system standby demand constraint, various power supply operation constraints, section transmission safety constraint and the like.
Annual theoretical power sequence P with new energy 0 ＝{P 0 (T), the T is 1,2, …, T }, the electrical load, the power grid and the power supply parameter are used as input, and the new energy power abandoning sequence P is obtained through annual time sequence production simulation optimization calculation c ＝P c (T), T ═ 1,2, …, T }, where P is c (T) electric power abandonment of new energy in T period, T is the number of all the time periods in the whole year, P c Representing a new energy annual power abandonment sequence set. The annual time sequence production simulation optimization calculation can adopt the existing cycle-by-cycle calculation and other modes, and the solving efficiency is improved.
A calculation coefficient module, graphically configured to:
based on new forms of energy abandon electricity sequence P c Acquiring a charge-discharge state sequence x ═ { x (T), T ═ 1,2, …, T } stored in each time period, wherein the charge-discharge state x (T) at the time T is equal to P of the abandoned electric power at the time T c The sign function of (t) is as follows:
x(t)＝sgn(P c (t))
wherein the sign function is:
the meaning of the charging and discharging state is that when the system has new energy and abandons electricity (P) c (t)>0) The energy storage charging and discharging state is set to be 1, which indicates that charging can be carried out; when the system has no new energy and abandons the electricity (P) c And (t) ═ 0), wherein the stored energy charging and discharging state is 0, and the stored energy can be discharged.
Based on new forms of energy abandon electricity sequence P c And theoretical power sequence P 0 And calculating the lowest proportionality coefficient alpha which needs to be absorbed in the electric quantity of the abandoned new energy under the condition of meeting the current r of the utilization rate of the new energy:
the model solving module is specifically configured to:
and establishing an energy storage power generation installation and capacity optimization model based on the annual electricity abandoning sequence and the lowest proportion coefficient of electricity abandoning and consumption of new energy, and calculating the most economic power generation installation and capacity requirements of energy storage under the condition of meeting the utilization rate of the new energy.
The objective function of the energy storage power generation installation and capacity optimization model is as follows:
min c 1 E max +c 2 P max
in the formula: e max Representing the energy storage capacity as an optimization variable; p max Representing an energy storage power generation machine as an optimized variable; c. C 1 Representing cost per unit of energy storage capacity, c 2 And the unit energy storage power generation installation cost is shown.
The constraint conditions include:
(1) energy storage capacity constraint:
0≤E(t)≤E max
and E (t) is the electric energy storage quantity of the stored energy at the moment t, and is an optimization variable. The constraint indicates that the stored energy capacity E (t) at time t cannot be greater than the stored energy capacity E max 。
(2) And (3) energy storage system charge and discharge power constraint:
P ch (t) represents the charging power of the stored energy at the moment t, and is an optimization variable; p dc And (t) represents the discharge power of the stored energy at the moment t, and is an optimization variable. The constraint represents the charging power P at time t ch (t) and discharge power P dc (t) not exceeding its generating machine P max And is determined by the charge-discharge state x (t), and the charge and discharge power is not simultaneously positive. From step 2, the charge-discharge state x (t) at the time of energy storage t is determined in advance and is a known quantity. When x (t) is equal to 1, the charging power P ch (t) is from 0 to P max Taking values between, i.e. charging can be carried out, and discharging power P dc (t) constrained to 0; on the contrary, when x (t) is equal to 0, the discharge power P dc (t) is from 0 to P max Value of interval, charging power P ch (t) is constrained to 0.
(3) Energy storage state of charge constraint:
the constraint describes the relationship between the amount of stored electricity and the charge and discharge power at the time of the energy storage adjacency. Namely: e (t) represents the energy storage capacity stored at the moment t, and is an optimized variable; e (t-1) represents the stored energy at the t-1 moment, and is an optimized variable; η represents the charge-discharge efficiency of stored energy.
(4) Energy storage time length constraint:
nP max ≤E max
the constraint indicates that the energy storage duration is greater than a given minimum energy storage duration, and n indicates the minimum energy storage duration.
(5) And (3) limiting the electricity abandoning consumption:
the constraint indicates that the electricity storage quantity of the energy storage year should be larger than the lowest proportion of the consumption of the new energy abandoned quantity.
Because the charging and discharging states of the stored energy are determined in advance, the stored energy power generation installation and capacity optimization model is a linear programming model and does not contain integer variables.
And calling a mathematical programming solver, solving an energy storage power generation installed machine and capacity optimization model, and obtaining the optimal power generation installed machine and capacity of the energy storage.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 present invention is not limited to the above embodiments, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention are included in the scope of the claims of the present invention.
Claims (10)
1. An energy storage and power generation installed and capacity optimal configuration method is characterized by comprising the following steps:
inputting the obtained power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandonment sequence of the new energy;
calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence;
substituting the minimum proportion coefficient of electricity abandonment consumption and the new energy annual electricity abandonment sequence into a pre-constructed energy storage power generation installed machine and capacity optimization model to obtain the energy storage power generation installed machine and capacity requirements meeting the new energy utilization rate;
the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of the power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions;
the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function when the utilization rate of new energy is met and setting constraint conditions for the objective function.
2. The method of claim 1, wherein the building of the energy storage and generation installation and capacity optimization model comprises:
setting energy storage capacity constraint, energy storage system charge and discharge power constraint, energy storage charge state constraint, energy storage duration constraint and electricity abandonment consumption constraint for the objective function by taking the minimum economic cost of energy storage power generation installation and capacity as the objective function;
and constructing an energy storage power generation installation and a capacity optimization model by the objective function and the energy storage capacity constraint, the energy storage system charge and discharge power constraint, the energy storage charge state constraint, the energy storage duration constraint and the electricity abandoning and consumption constraint.
3. The method according to claim 1, wherein the step of bringing the electricity abandonment consumption minimum proportionality coefficient and the new energy annual electricity abandonment sequence into a pre-constructed energy storage and power generation installation and capacity optimization model to obtain the energy storage and power generation installation and capacity requirements meeting the new energy utilization rate comprises the following steps:
and inputting the new energy annual power abandoning sequence into the energy storage power generation installed capacity optimization model, and solving by using a mathematical programming solver to obtain the optimal energy storage power generation installed capacity and capacity.
4. The method of claim 1, wherein the new energy annual energy curtailment sequence is calculated as follows:
P c ＝{P c (t)，t＝1，2，…，T}
in the formula, P c Is a new energy whole year electricity abandoning sequence, P c And (T) the electric power of the new energy abandoned in the period T, the period T and the number of all the time periods in the whole year.
5. The method of claim 1, wherein the electricity curtailment consumption minimum scaling factor is calculated as:
in the formula, alpha is the lowest proportion coefficient of electricity abandonment and consumption, r is the utilization rate of new energy, P 0 (t) is the theoretical power sequence, P c And (T) is a new energy power abandoning sequence, and T is the number of all time periods in the whole year.
6. The method of claim 2, wherein the objective function of the energy storage and generation machine and capacity optimization model is calculated as follows:
min c 1 E max +c 2 P max
in the formula, c 1 Cost per unit energy storage capacity, E max To energy storage capacity, c 2 For unit energy storage installation cost, P max And the energy storage power generation machine is used.
7. The method of claim 2, wherein the curtailment consumption constraint is calculated as:
in the formula, P ch (t) is the charging power of the stored energy at the moment t, alpha is the lowest proportional coefficient of the abandoned electricity consumption, P c And (T) is a new energy power abandoning sequence, and T is the number of all time periods in the whole year.
8. An energy storage and power generation installed and capacity optimal configuration system, comprising:
the calculation sequence module is used for inputting the acquired power system parameters and the annual theoretical power sequence of the new energy into a pre-constructed new energy time sequence production simulation optimization model which does not contain stored energy, and calculating to obtain an annual electricity abandonment sequence of the new energy;
the calculation coefficient module is used for calculating to obtain a minimum proportion coefficient of electricity abandonment consumption based on the new energy annual electricity abandonment sequence and the new energy annual theoretical power sequence;
the model solving module is used for substituting the electricity abandonment minimum proportion coefficient and the new energy annual electricity abandonment sequence into a pre-constructed energy storage and power generation installation and capacity optimization model to obtain the energy storage and power generation installation and capacity requirements meeting the new energy utilization rate;
the new energy time sequence production simulation optimization model is constructed by taking the maximum consumption of new energy in the whole network as an optimization target and taking power balance of the power grid, system standby requirements, operation of various power supplies and section transmission safety as constraint conditions;
the energy storage power generation installed and capacity optimization model is constructed by taking the minimum economic cost of the energy storage power generation installed and capacity as an objective function when the utilization rate of new energy is met and setting constraint conditions for the objective function.
9. The system of claim 8, wherein the model solution module is specifically configured to:
and inputting the new energy annual power abandoning sequence into the energy storage power generation installed capacity optimization model, and solving by using a mathematical programming solver to obtain the optimal energy storage power generation installed capacity and capacity.
10. The system of claim 8, wherein the calculation coefficient module calculates the electricity curtailment consumption minimum scaling factor by:
in the formula, alpha is the lowest proportion coefficient of electricity abandonment and consumption, r is the utilization rate of new energy, P 0 (t) is the theoretical power sequence, P c And (T) is a new energy power abandoning sequence, and T is the number of all time periods in the whole year.
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