CN110034572B - Energy storage configuration method for alternating current-direct current hybrid system containing multi-port power electronic transformer - Google Patents
Energy storage configuration method for alternating current-direct current hybrid system containing multi-port power electronic transformer Download PDFInfo
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Abstract
The invention discloses an energy storage configuration method of an alternating current-direct current hybrid system containing a multi-port power electronic transformer, which considers renewable energy power generation subsidies and carbon trading environmental protection benefits and establishes a net ready cost optimization configuration target in a system life cycle; establishing optimized configuration model constraint conditions including power balance constraint, energy storage system model constraint, reliability constraint, power curtailment constraint and the like; establishing a system transmission conversion efficiency model; considering the electricity abandonment quantity and the reliability, establishing a coordinated operation strategy of a plurality of energy storage systems; and solving the optimal configuration scheme of the alternating current-direct current hybrid system by adopting a Markov chain Monte Carlo method and a heuristic algorithm. The invention solves the energy storage configuration problem of the AC/DC hybrid system containing the multi-port power electronic transformer, considers the transmission conversion efficiency of the system, the allowable electricity abandonment amount and the reliability of the system, and considers the collaborative optimization operation of the energy storage systems, thereby realizing the collaborative optimization configuration of a plurality of energy storage systems, reducing the total energy storage configuration amount and improving the system economy.
Description
Technical Field
The invention relates to the technical field of distributed power grids, in particular to an energy storage configuration method of an alternating current-direct current hybrid system with a power electronic transformer.
Background
The access of distributed power sources and stored energy makes the power flow of the power system generate multiple flow directions, so that the students propose a new power distribution network (fresh electrical power generation and management) based on power electronics, high bandwidth digital communication and distributed control. A Power Electronic Transformer (PET) is a key device of a FREEDM system and an energy internet, and is used as an energy route to realize flexible interconnection and energy multidirectional flow of a medium-low voltage alternating current-direct current network. In addition, different from the traditional power transformer, the PET has the functions of voltage and power factor regulation, power control, voltage interference suppression, load interference suppression and the like, and can be conveniently accessed to various distributed energy sources, energy storage and loads.
Due to the randomness, the intermittence and the uncontrollable property of renewable energy sources such as photovoltaic and wind power, along with the access of the power sources, the smooth power fluctuation of an energy storage system is required to be adopted to enable the micro-grid system to meet the grid-connected requirement of a power grid. Currently, two methods are generally adopted for optimal configuration of the capacity of the energy storage system. Firstly, a double-layer optimization method is adopted, and the inner layer optimizes the operation state of the stored energy in order to consider the minimum daily operation cost of the micro-grid system. And secondly, modeling an optimized configuration model for the stored energy by adopting a set operation strategy, and determining the charge and discharge amount of the stored energy according to the relation between the generated energy of the microgrid and the load demand and the stored energy operation constraint. For a multi-voltage-grade alternating current-direct current hybrid system, the stored energy is respectively connected to different buses. The electric quantity and the reliability of the AC/DC hybrid system need to be considered during actual optimal configuration, and in order to more accurately configure the energy storage capacity, the transmission conversion efficiency of the AC/DC hybrid system needs to be considered so as to coordinate the energy storage capacities accessed by different buses. The energy storage of the current AC/DC hybrid system can be set to be accessed at a low-voltage DC bus, and the transmission conversion efficiency, the electric quantity abandonment, the reliability and the like of the AC/DC hybrid system are less considered. Therefore, the configuration of the energy storage system needs to be further optimized to reduce the investment and operation and maintenance costs of the alternating current and direct current hybrid system.
Disclosure of Invention
In order to solve the problems, the invention provides an energy storage configuration method for an alternating current-direct current hybrid system with a multiport power electronic transformer, which fully considers the transmission conversion efficiency of the power electronic transformer, the relation between the service life of the energy storage system and the charging and discharging power, and the allowable electricity abandonment and reliability of the alternating current-direct current hybrid system, optimizes the capacity configuration of the energy storage system of the alternating current-direct current hybrid system, and reduces the capacity of the configured energy storage system, thereby improving the energy efficiency and the economical efficiency of the alternating current-direct current hybrid system with the multiport power electronic transformer.
In order to achieve the purpose, the technical scheme of the invention is as follows:
an energy storage configuration method for an alternating current-direct current hybrid system with a multi-port power electronic transformer comprises the following steps:
considering renewable energy power generation subsidies and carbon trading environmental protection benefits, establishing a net cost-ready optimal configuration target in the life cycle of the alternating current-direct current hybrid system;
establishing constraint conditions of an alternating current-direct current hybrid system optimization configuration model, wherein the constraint conditions comprise power balance constraint, energy storage system model constraint, reliability constraint, renewable energy source installed proportion/power generation proportion constraint, power abandonment rate constraint and energy storage system capacity configuration upper and lower limit constraint;
establishing a conversion efficiency model of the multi-port power electronic transformer;
considering the electricity abandonment quantity and the reliability, and establishing a coordinated operation strategy of a plurality of energy storage systems in the alternating current-direct current hybrid system;
and generating a random scene by adopting a Markov chain Monte Carlo method, reducing the scene, and solving an optimized configuration model of the alternating current-direct current hybrid system based on the reduced scene and a heuristic algorithm.
Further, the net cost of the hybrid system includes net present values of all costs and incomes in the life cycle of the ac-dc hybrid system, the costs specifically include initial investment costs, operation and maintenance costs, equipment replacement costs and electricity purchasing costs, and the incomes specifically include the sum of renewable energy power generation subsidies, electricity selling incomes and equipment residual values.
Further, the power balance constraint is the balance of load power on each bus, distributed power generation power, energy storage device charging and discharging power and power electronic transformer interaction power. And the energy storage system model is restricted to limit the charge and discharge rate of the energy storage system and the maximum and minimum capacity of the energy storage equipment. The reliability constraint establishes a constraint by not satisfying the load rate. The unsatisfied load rate is the percentage of the total load of the part of the AC/DC hybrid system with the load exceeding the sum of the generated energy of the distributed power supply, the electric quantity of the power grid and the discharged quantity of the energy storage system. The renewable energy source power generation installed proportion is the proportion of renewable energy source power generation installed capacity to the maximum load, the renewable energy source power generation proportion is the proportion of renewable energy source power generation amount to load power consumption, the renewable energy source electricity abandoning rate is the proportion of renewable energy source electricity abandoning amount to the total power generation amount, and the load rate, the renewable energy source installed proportion/power generation proportion constraint, the electricity abandoning rate constraint, the energy storage system capacity configuration upper and lower limit constraint and the like are set according to the requirements of the alternating current-direct current hybrid system.
Furthermore, a multi-port power electronic transformer conversion efficiency model is established, and load rate and efficiency curves of all current transformation links in the power electronic transformer are fitted according to the internal topological structure of the power electronic transformer and efficiency data of key load points.
Further, a plurality of energy storage system cooperative operation strategies are established, and specifically, (1) the total energy storage charge and discharge power required by the alternating current-direct current hybrid system and the charge and discharge power required by independent balance of each bus are calculated. (2) And simultaneously, the SOC state of each energy storage system is considered to calculate the charge and discharge amount of each energy storage system. (3) And calculating the local balance amount of the electric quantity shortage and the balance of each bus.
Further, based on solar radiation, wind speed data and distribution functions thereof, generating a solar radiation and wind speed long-time scale stochastic model by a Markov chain Monte Carlo method; generating a long-time scale random model of the load by adopting specific distribution based on historical load data or load types and characteristics; generating renewable energy resources, loads and fault scenes of each element of an alternating current-direct current hybrid system according to a Markov chain Monte Carlo method; and (3) scene reduction is carried out by adopting a k-means method, and a heuristic algorithm is adopted to solve an optimal configuration scheme of energy storage of the alternating current-direct current hybrid system for the scene after the scene reduction.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention solves the energy storage configuration problem of the AC/DC hybrid system containing the multi-port power electronic transformer, realizes the economic optimization of energy storage and improves the economical efficiency of the AC/DC hybrid system.
2. The invention considers the transmission conversion efficiency, allowable electricity abandonment quantity and reliability of the AC-DC hybrid system, and considers the collaborative optimization operation of the energy storage systems, thereby realizing the collaborative optimization configuration of a plurality of energy storage systems, reducing the total energy storage configuration amount and improving the economical efficiency of the AC-DC hybrid system.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram of an AC/DC hybrid system including a multi-port power electronic transformer according to an embodiment of the present invention;
FIG. 3 is a multi-port power electronic transformer topology according to an embodiment of the present invention;
fig. 4 is a graph illustrating the load factor and efficiency of the multi-port power electronic transformer according to the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and detailed description.
The embodiment is as follows:
an energy storage collaborative optimization configuration method for an alternating current-direct current hybrid system with a multi-port power electronic transformer comprises the following steps:
and 5, generating a random scene by adopting a Markov chain Monte Carlo method, reducing the scene, and solving the alternating current-direct current hybrid distributed energy system optimization configuration scheme based on the reduced scene and a heuristic algorithm.
For convenience of illustrating the specific implementation steps of the present invention, the specific embodiments of the method are as follows:
(1) And (2) considering renewable energy power generation subsidies and carbon trading environmental protection benefits, and establishing a Net Present Cost (NPC) optimization configuration target in the life cycle of the AC-DC hybrid system, as shown in the formula (1).
C NPC ＝C inv +C om +C re +C buy -B sub -B sell -B sal -B CCER (1)
In the formula, C NPC The net current value of the life cycle of the alternating current-direct current hybrid system is obtained; c inv Initial investment cost; c om For operating maintenance costs; c re Cost for equipment replacement; c buy For the cost of electricity purchase; b sub The method is a subsidy for power generation of renewable energy sources; b is sell Income for electricity sale; b sal Is the equipment residual value; b is CCER For carbon trading revenue.
Considering the expansion of the currency, the cost and the income of the alternating current and direct current hybrid system in the following year need to be converted to the first year so as to accurately evaluate the cost of the whole life cycle of the alternating current and direct current hybrid system. When the service life of the AC/DC hybrid system is K years and the current rate is r, the net current value C in the life cycle of the AC/DC hybrid system NPC Calculated as follows.
Wherein C (k) represents the cost of the k year; b (k) represents the k-year ac/dc hybrid system revenue.
For the embodiment, the initial investment cost, the operation and maintenance cost, the equipment replacement cost and the equipment residual value are corresponding numerical values of the energy storage battery. By setting the limitation of the energy storage charging and discharging times, the energy storage battery is replaced when the energy storage runs to the maximum charging and discharging times, so that the replacement cost is calculated according to the replacement time and times of the energy storage battery. When the AC/DC hybrid system runs to the designed system year, the energy storage battery margin is converted into a residual value in proportion based on the energy storage replacement cost.
(2) Fig. 2 shows a hybrid ac/dc system with a multi-port power electronic transformer, and fig. 3 shows a power electronic transformer topology. And establishing optimized configuration model constraint conditions for the alternating current-direct current hybrid system, wherein the optimized configuration model constraint conditions comprise power balance constraint, energy storage system model constraint, reliability constraint, renewable energy source installation proportion/power generation proportion constraint, power abandonment rate constraint, energy storage system capacity configuration upper and lower limit constraint and the like.
a. Establishing power balance and topological structure constraint, which is concretely as follows:
the power consumed by the load of the alternating current-direct current hybrid system on each bus at each moment, the power generated by the distributed power supply, the charging and discharging power of the energy storage equipment and the power obtained from the power grid are correspondingly balanced. The following constraints are established for the power electronic transformer with two parallel machines based on the power balance principle.
Power electronic transformer internal node constraint:
P A +P B +P C +P D ＝0 (3)
in the formula, P A 、P B 、P C 、P D Power, kW, flowing through points a, B, C, D inside the power electronic transformer, respectively.
And (3) power balance constraint of buses of each voltage class:
P 2 +P DG_HVDC +P B_HVDC ＝L HVDC (4)
P 3 +P DG_LVAC +P B_LVAC ＝L LVAC (5)
P 4 +P DG_LVDC +P B_LVDC ＝L LVDC (6)
in the formula, P 2 、P 3 、P 4 Power, kW, of the power electronic transformer ports 2, 3, 4, respectively; p DG_HVDC 、P DG_LVAC 、P DG_LVDC The power of distributed power supplies connected with a 10kV DC bus, a 380VAC bus and a +/-375V DC bus is kW; p B_HVDC 、P B_LVAC 、P B_LVDC The power of an energy storage system connected with a 10kV DC bus, a 380V AC bus and a +/-375V DC bus is kW; l is HVDC 、L LVAC 、L LVDC The load power, kW, connected with a 10kV DC bus, a 380VAC bus and a +/-375V DC bus are respectively.
Capacity constraint of external ports 1-3 of the power electronic transformer:
in the formula, P Converter1 ～P Converter3 The rated power of the converters 1-3 in the power electronic transformer is obtained.
Capacity constraints of internal ports A, C and D of the power electronic transformer:
b. establishing energy storage system model constraints as follows:
the energy storage system model is established by using the capacity, the charge state and the charge-discharge rate, and the operation constraint of the energy storage system model is shown as the formula.
In the formula, W ess (t) electric energy, kWh, stored in the energy storage system at time t; p ch (t)、P disch (t) power, kW, of the energy storage system during charging and discharging at the moment t respectively; eta ch 、η disch Efficiency of charging and discharging the energy storage system respectively; w ess,max 、W ess,min Upper and lower limits of stored electric energy, kWh, for the energy storage system, respectively; p ch,max 、P disch,max The maximum power, kW, when the energy storage system is charged and discharged, respectively.
c. Establishing a reliability constraint as follows:
the reliability constraint establishes a constraint by not satisfying the load rate. The unsatisfied load rate is the percentage of the total load occupied by the part of the system with the load exceeding the sum of the generated energy of the distributed power supply, the electric quantity of the power grid and the discharged quantity of the energy storage system. The unsatisfied load factor for an ac/dc hybrid system with a lifetime of K years can be calculated by equation (10).
In the formula, gamma UL In order to satisfy the load factor, the present example is set to 1%; l is the load of an AC/DC hybrid system, kW; p is DR The power generation capacity of the distributed power supply is kW; l is G The electric quantity of the alternating current-direct current hybrid system is supplied to the power grid, and the value of the alternating current-direct current hybrid system is negative kW when the alternating current-direct current hybrid system flows reversely.
d. Other constraints are specifically as follows:
the embodiment sets the installed proportion of renewable energy sources to be >60%, the power rejection rate to be <10%, and the upper and lower limits of each energy storage system capacity configuration to be [0,6000kwh ].
(3) A multi-port power electronic transformer conversion efficiency model is built based on fig. 3. The inside of the power electronic transformer is divided into 3 converters, the efficiencies of +/-375V DC-10 kVAC, 10kV DC- +/-375V DC and 380 VAC- +/-375V DC ports are respectively measured when the load factors are 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100%, and load factor-efficiency curves of the 3 converters are obtained by adopting polynomial fitting, as shown in figure 4.
(4) Considering the electric quantity abandonment and the reliability, establishing a coordinated operation strategy model of a plurality of energy storage systems, which specifically comprises the following steps:
a. based on an energy storage system operation strategy, not considering an energy storage SOC state, calculating total energy storage charge-discharge power required by the AC-DC hybrid system under the optimized operation and charge-discharge power required by the independent balance of each bus according to the total power generation power, total load, electricity price, energy storage electricity consumption cost and power constraint of a grid-connected point;
b. and if the two energy storage systems are charged or discharged simultaneously, respectively calculating the actual charging and discharging amounts of the two energy storage systems by considering the state of the energy storage SOC. And if the two energy storage systems simultaneously meet or do not meet the charging and discharging requirements, respectively calculating the charging and discharging amount of each energy storage system according to the bus power balance. If only one energy storage system does not meet the charging and discharging requirements of the local bus, the insufficient part is provided by the energy storage system under the other bus;
c. and c, comparing the charge and discharge amount of the energy storage system obtained by the calculation of the step b with the total charge and discharge power demand of the alternating current-direct current hybrid system calculated by the step a, when the charge and discharge amount calculated by the step b cannot meet the demand calculated by the step a, the shortage part is provided by a grid-connected point, and if the grid-connected point cannot complement the charge and discharge demand, the shortage/balance electric quantity is balanced on site at each bus.
(5) a, generating 1000 random scenes by adopting a Markov chain Monte Carlo method.
Solar radiation is often fitted with a beta distribution.
PDF(S) n Beta distribution for the nth set of solar radiation data; n =1, 2.. N, N denotes the division of the time of day into N periods of solar radiation, α n And beta n A coefficient greater than zero; s n For the nth set of solar radiation data,
is the maximum of the nth set of solar radiation data; Γ is the gamma function.
Fitting the wind speed by applying double-parameter Weibull distribution, wherein the probability density function of the wind speed Weibull distribution is shown as a formula:
wherein PDF (V) is the Weibull distribution of wind speed; m is a shape parameter (dimensionless) of the weibull distribution; c is a scale parameter (m/s) of Weibull distribution, and reflects the average wind speed of the wind power plant; v is a given wind speed, m/s. The shape parameter m and the scale parameter c may be determined from actual wind speed data.
For the existing load scene, if insufficient historical load data exists, a load random scene can be generated through a typical daily load curve. The load stochastic model may be based on probability distribution of load prediction errorAnd modeling. The load prediction error can be considered to be mu and the variance sigma following the mathematical expectation 2 Normal distribution of (d) is expressed as N (μ, σ) 2 )。
The reliability calculation is based on the failure rate lambda of the device and the repair time T rep And generating a fault available state time sequence by adopting a two-state continuous time Markov chain Monte Carlo method on the assumption that the two are subjected to exponential distribution. The key elements for generating the fault available sequence in the submitted direct-current hybrid renewable energy system comprise photovoltaic, wind power, energy storage, a power electronic transformer, a power grid and the like.
b. Scene reduction
Renewable energy, load and fault scenes are reduced by adopting a k-means method respectively to 10 scenes, and 1 scene is further reduced respectively. The 10 renewable energy scenes are combined with 1 load and fault scene, the 10 load scenes are combined with 1 renewable energy and fault scene, and the 10 fault scenes are combined with 1 renewable energy and load scene to obtain 30 scenes.
c. Optimal configuration solution
And solving the reduced scenes by adopting a parallel genetic algorithm respectively to obtain the energy storage configuration of the alternating current-direct current hybrid system and the corresponding NPC range under different scenes.
The above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention accordingly, and not to limit the protection scope of the present invention accordingly. All equivalent changes or modifications made in accordance with the spirit of the present disclosure are intended to be covered by the scope of the present disclosure.
Claims (8)
1. An energy storage configuration method for an alternating current-direct current hybrid system with a multi-port power electronic transformer comprises the following steps:
considering renewable energy power generation subsidies and carbon trading environmental protection benefits, establishing a net cost-ready optimal configuration target in the life cycle of the alternating current-direct current hybrid system;
establishing constraint conditions of an alternating current-direct current hybrid system optimization configuration model, wherein the constraint conditions comprise power balance constraint, energy storage system model constraint, reliability constraint, renewable energy source installed proportion/power generation proportion constraint, power abandonment rate constraint and energy storage system capacity configuration upper and lower limit constraint;
establishing a conversion efficiency model of the multi-port power electronic transformer;
considering the electricity abandonment quantity and the reliability, and establishing a coordinated operation strategy of a plurality of energy storage systems in the alternating current-direct current hybrid system;
generating a random scene by adopting a Markov chain Monte Carlo method, reducing the scene, and solving an optimized configuration model of the alternating current-direct current hybrid system based on the reduced scene and a heuristic algorithm;
the net cost optimal configuration target comprises net present values of all costs and incomes in the life cycle of the alternating current-direct current hybrid system, the costs specifically comprise initial investment cost, operation and maintenance cost, equipment replacement cost and electricity purchasing cost, and the incomes specifically comprise renewable energy power generation subsidies, carbon transaction environmental protection income and equipment residual values;
net present cost C in life cycle of AC/DC hybrid system NPC Calculated as follows:
c (K) and B (K) respectively represent the cost and income of the AC-DC hybrid system in the K year, K =1,2, \\ 8230, and K, K represents the life cycle of the AC-DC hybrid system;
the power balance constraint is the balance of load power on each bus, distributed power generation power, energy storage device charge and discharge power and interaction power with the multi-port power electronic transformer, and the specific constraint conditions are as follows:
internal node power balance constraint of the multi-port power electronic transformer:
P A +P B +P C +P D ＝0
in the formula, P A 、P B 、P C 、P D Respectively flowing through multi-port power electronic transformerPower of internal ports a, B, C, D, kW;
and (3) power balance constraint of buses of each voltage class:
P 2 +P DG_HVDC +P B_HVDC ＝L HVDC
P 3 +P DG_LVAC +P B_LVAC ＝L LVAC
P 4 +P DG_LVDC +P B_LVDC ＝L LVDC
in the formula, P 1 、P 2 、P 3 、P 4 The power of external ports 1,2, 3 and 4 of the multi-port power electronic transformer is kW; p DG_HVDC 、P DG_LVAC 、P DG_LVDC The power of distributed power supplies connected with a 10kV DC bus, a 380V AC bus and a +/-375V DC bus is kW; p B_HVDC 、P B_LVAC 、P B_LVDC The power of an energy storage system connected with a 10kV DC bus, a 380VAC bus and a +/-375V DC bus is kW; l is HVDC 、L LVAC 、L LVDC The load power, kW, connected with a 10kV DC bus, a 380VAC bus and a +/-375V DC bus respectively;
capacity constraint of external ports 1-3 of the multi-port power electronic transformer:
in the formula, P Converter1 ～P Converter3 Rated power of a converter 1-3 in the multi-port power electronic transformer;
capacity constraints of internal ports A, C and D of the multi-port power electronic transformer are as follows:
2. the method of claim 1, wherein the method further comprises the steps of:
establishing an energy storage system model by using the capacity, the state of charge and the charge-discharge rate and the operation constraint thereof are as follows:
in the formula, W ess (t) electric energy stored in the energy storage system at time t, kWh; p is ch (t)、P disch (t) power when the energy storage system is charged and discharged at the moment t, kW; eta ch 、η disch Efficiency of charging and discharging the energy storage system respectively; w ess,max 、W ess,min Upper and lower limits of stored electric energy, kWh, for the energy storage system, respectively; p ch,max 、P disch,max The maximum power, kW, when the energy storage system is charged and discharged, respectively.
3. The method of claim 2, wherein the method further comprises the steps of:
the reliability constraint establishes a constraint by failing to satisfy a load rate, which can be calculated by:
in the formula, gamma UL In order to not meet the load rate, L is the load of an AC/DC hybrid system, kW; p DR The power generation capacity of the distributed power supply is kW; l is G The electric quantity of the alternating current-direct current hybrid system is supplied to the power grid, and the value is negative kW in the countercurrent process.
4. The method of claim 3, wherein the method further comprises the steps of:
the installed proportion of renewable energy is greater than 60%, the power rejection rate is less than 10%, and the upper limit and the lower limit of each energy storage system capacity configuration are constrained to be [0,6000kWh ].
5. The method of claim 4, wherein the method further comprises the steps of:
the inside of the multi-port power electronic transformer is divided into 3 converters, the efficiencies of +/-375V DC-10 kV AC, 10kV DC- +/-375V DC and 380V AC- +/-375V DC ports are respectively measured when the load rates are 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100%, and the load rate-efficiency curves of the 3 converters are obtained by adopting polynomial fitting.
6. The method of claim 5, wherein the method further comprises the steps of:
considering the electric quantity and the reliability, establishing a coordinated operation strategy model of a plurality of energy storage systems in the AC/DC hybrid system, specifically:
a. based on an energy storage system operation strategy, the energy storage SOC state is not considered, and the total energy storage charge-discharge power required by the energy storage system under the optimized operation and the charge-discharge power required by the independent balance of each bus are calculated according to the total power generation power, the total load, the electricity price, the energy storage electricity consumption cost and the power constraint of the grid-connected point of the energy storage system;
b. if the two energy storage systems are charged or discharged simultaneously, the actual charging and discharging amounts of the two energy storage systems are respectively calculated by considering the state of the energy storage SOC, if the two energy storage systems simultaneously meet or do not meet the charging and discharging requirements, the charging and discharging amounts of the energy storage systems are respectively calculated according to the power balance of the bus, and if only one energy storage system does not meet the charging and discharging requirements of the local bus, the insufficient amount is provided by the energy storage system under the other bus;
c. and c, comparing the charge and discharge capacity of the energy storage system calculated by the b with the total charge and discharge power demand of the energy storage system calculated by the a, when the charge and discharge capacity calculated by the b cannot meet the demand calculated by the a, providing insufficient charge by a grid-connected point, and if the grid-connected point cannot complement the charge and discharge demand, balancing the insufficient/residual electric quantity on each bus in place.
7. The method of claim 6, wherein the method further comprises the steps of:
the Markov chain Monte Carlo method is adopted to generate 1000 random scenes, and the specific process is as follows:
fitting is carried out on solar radiation by using beta distribution;
in the formula, PDF (S) n Beta distribution for the nth set of solar radiation data; alpha is alpha n And beta n A coefficient greater than zero; s n For the nth set of solar radiation data,
is the maximum of the nth set of solar radiation data; gamma is a gamma function;
fitting the wind speed by applying double-parameter Weibull distribution, wherein the probability density function of the wind speed Weibull distribution is shown as a formula:
wherein PDF (V) is the Weibull distribution of wind speed; m is a shape parameter of Weibull distribution and is dimensionless; c is a scale parameter of Weibull distribution, m/s, and reflects the average wind speed of the wind power plant; v is given wind speed, m/s;
for the existing load scene, if the historical load data is insufficient, a load random scene is generated through a typical daily load curve, a load random model is modeled through probability distribution based on load prediction errors, the load prediction errors are regarded as mu and sigma according to mathematical expectation, and the variance is 2 Normal distribution ofIs denoted as N (μ, σ) 2 )；
The reliability calculation is based on the failure rate lambda of the device and the repair time T rep Assuming that the two conditions obey exponential distribution, generating a fault available state time sequence by adopting a two-state continuous time Markov chain Monte Carlo method, wherein key factors for generating the fault available state time sequence in the AC-DC hybrid system comprise photovoltaic power, wind power, energy storage, a multi-port power electronic transformer and a power grid.
8. The method of claim 7, wherein the method further comprises the steps of:
the specific scene reduction process comprises the following steps: respectively reducing renewable energy sources, loads and fault scenes by adopting a k-means method to respectively reduce 10 scenes, further respectively reduce 1 scene, combine 10 renewable energy source scenes with 1 load and fault scene, combine 10 load scenes with 1 renewable energy source and fault scene, combine 10 fault scenes with 1 renewable energy source and fault scene, and obtain 30 scenes;
and (4) solving the reduced scenes by adopting a parallel genetic algorithm respectively to obtain energy storage configuration schemes of the alternating current-direct current hybrid system and corresponding net cost ranges under different scenes.
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| CN110492721B (en) * | 2019-08-23 | 2022-06-17 | 西安西电电力系统有限公司 | Multiport power electronic transformer |
| CN110797923A (en) * | 2019-11-26 | 2020-02-14 | 国网江苏省电力有限公司南通供电分公司 | Power electronic transformer operation strategy optimization combination method |
| CN111049165A (en) * | 2019-11-28 | 2020-04-21 | 国网新疆电力有限公司经济技术研究院 | Method and system for energy storage configuration of new energy power system |
| CN111245027B (en) * | 2020-03-11 | 2023-10-13 | 国网天津市电力公司 | Alternating current/direct current hybrid system optimal scheduling method considering PET loss |
| CN112713621B (en) * | 2020-12-22 | 2023-06-09 | 广东电网有限责任公司电力科学研究院 | Multi-objective optimal configuration method and system for AC/DC hybrid system |
| CN112910001B (en) * | 2021-02-23 | 2022-05-27 | 广东电网有限责任公司 | Three-stage optimal configuration method and system for multi-voltage-level alternating current-direct current hybrid system |
| CN113644698A (en) * | 2021-06-30 | 2021-11-12 | 国网上海能源互联网研究院有限公司 | Source load storage capacity optimal configuration method and system for island micro-grid |
| CN113394780B (en) * | 2021-07-21 | 2022-08-19 | 国网江苏省电力有限公司南通供电分公司 | Power control method and system for automatic port fault ride-through |
| CN113644670B (en) * | 2021-10-14 | 2022-01-25 | 中国电力科学研究院有限公司 | Method and system for optimally configuring energy storage capacity |
| CN114676967B (en) * | 2022-02-22 | 2023-10-24 | 四川大学 | Multi-energy system distributed optimization scheduling method considering carbon transaction |
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