Self-scheduling method and system for micro-grid containing energy storage equipment and providing active standby

Abstract

The invention discloses a self-scheduling method and a self-scheduling system for a micro-grid with active standby and energy storage equipment, and the method comprises the steps: analyzing the scheduling process of the self-scheduling of the micro-grid with active standby and energy storage equipment based on a system framework diagram of a self-scheduling technology of the micro-grid with active standby and energy storage equipment, and building a decision dependence uncertainty set; establishing a renewable energy source and load demand uncertainty set according to the historical information of the random factors; establishing a micro-grid multi-stage robust optimization model which provides active standby and contains energy storage equipment by taking the minimum operation cost in an expected scene as a target; the method comprises the following steps: establishing a feasibility range of a scheduling scheme meeting safety and economy, and establishing a micro-grid mixed integer programming scheduling model which provides active standby and contains energy storage equipment; and solving positive and negative reserve capacities provided for an external system or a main power grid by the energy storage micro-grid in each time period under the condition of keeping self optimal scheduling, an optimal safety decision range of decisions in each time period and a day-ahead optimal power injection curve for ensuring system safety.

Description

Background Art

[0002] Since 1990, global carbon dioxide emissions caused by power systems and industry have continued to grow at an annual rate of 2.3%, and a series of problems such as climate anomalies and environmental pollution have continued to worsen. The global consensus on addressing climate change and promoting sustainable development is to significantly reduce the carbon intensity of the power grid, actively develop renewable energy, and achieve the transformation of the current energy industry to a clean, low-carbon, environmentally friendly, safe and efficient energy system.

[0003] Due to the influence of weather factors such as wind speed and light intensity, renewable energy generation represented by wind power and solar power presents the characteristics of high intermittency, strong volatility, strong randomness, poor controllability and low prediction accuracy, resulting in increasingly prominent problems in system energy supply and demand balance and safety, which has brought great challenges to the safe, stable and reliable operation of the power system. Therefore, it is urgent to efficiently integrate a high proportion of renewable energy into the power grid while ensuring the safe and stable operation of the power grid.

[0004] As the most representative flexible regulation resource, energy storage equipment can realize energy storage and transfer through charging and discharging functions. Energy storage equipment can remove the restriction that power production, transmission and use must be completed simultaneously, give full play to the coupling and complementary functions of multiple resources, improve the renewable energy consumption rate and power quality, and provide strong support for renewable energy grid connection. It is a key technology to improve the safety, economy and flexibility of the power system and build a new energy system.

[0005] Microgrids are mainly powered by renewable energy and use energy storage devices to adjust to meet load demand. They are small power systems with complete power generation, distribution and power consumption functions. Microgrids can serve as a buffer between renewable energy and the main power grid, effectively alleviating the impact of the randomness and intermittency of renewable energy on the external power grid, improving the penetration rate of renewable energy, power quality, power supply reliability and energy efficiency, and providing new opportunities for the application of renewable energy in power systems, thereby maximizing economic and environmental benefits.

[0006] At present, the research on microgrid systems with energy storage and renewable energy is mainly aimed at the dispatching problem with power balance as the main concern. The main grid provides sufficient backup services for the energy storage system to compensate for possible fluctuations, which plays an important role in the safe and stable operation of the system. At this time, the system is regarded as a backup consumer. However, this mode of operation will increase the backup burden of the main grid and the difficulty of dispatching the main grid. The backup potential of the system with energy storage equipment has not been fully utilized, so it is not an economical and reliable solution. As a highly efficient and fast-response device, energy storage has the ability to quickly provide positive and negative backup for the system, and the backup reliability provided is equivalent to that provided by traditional units, which can ensure the safe and stable operation of the system. However, there is still a great lack of understanding of the backup provided by microgrid systems with energy storage and renewable energy as backup providers.

[0007] Therefore, further optimizing energy storage functions, actively promoting the application of energy storage technology in the backup auxiliary market, fully tapping the potential of energy storage, enhancing the flexibility of grid operation, and improving the economic benefits of the system are important directions for the development of new power systems and important means to cope with the challenges of large-scale uncertain power injection. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a self-scheduling method and system for a microgrid containing energy storage equipment that provides active backup in response to the deficiencies in the above-mentioned prior art, which is used to solve the technical problem that when the microgrid system containing energy storage provides backup to an external system or a main grid as a backup consumer, the backup burden of the main grid is increased, the scheduling difficulty of the main grid is increased, and the backup potential of the microgrid containing energy storage cannot be fully utilized. The present invention provides technical support for the feasibility of the microgrid system containing energy storage as a backup provider, provides a safe and economical scheduling scheme for the microgrid system containing energy storage, provides an effective positive and negative backup capacity scheme for the external system or the main grid, and provides a decision-making basis for the planning scheme of the microgrid system containing energy storage, thereby promoting the consumption of new energy and the low-carbon process.

[0009] The present invention adopts the following technical solutions:

[0010] A method for self-dispatching a microgrid including an energy storage device with active standby is provided, comprising the following steps:

[0011] S1. Build a system framework for self-dispatching technology of microgrids with energy storage devices that provide active backup;

[0012] S2. Analyze the dispatching process of the microgrid containing energy storage equipment that provides active backup in the system framework of the microgrid self-dispatching technology containing energy storage equipment, establish a decision-dependent uncertainty set for the uncertainty of positive and negative backup demand; establish a renewable energy and load demand uncertainty set based on the historical information of random factors obtained;

[0013] S3, obtaining key parameters of the microgrid system, constructing an objective function with the goal of minimizing the operating cost under the expected scenario, and constructing a multi-stage robust optimization model of a microgrid with energy storage equipment that provides active backup based on the renewable energy and load demand uncertainty set obtained in step S2;

[0014] S4, according to the multi-stage robust optimization model of the microgrid with energy storage equipment providing active backup obtained in step S3, using its constraint structure characteristics to establish a scheduling plan that meets feasibility and safety for the microgrid system in each period;

[0015] S5. Based on the multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup obtained in step S3 and the scheduling plan obtained in step S4, a hybrid integer programming day-ahead scheduling model for the microgrid with energy storage equipment that provides active backup is established, the decision feasibility range, the optimal positive and negative backup capacity and the optimal power injection curve of the microgrid system are solved, and self-scheduling of the microgrid is achieved based on the results obtained.

[0016] Preferably, in step S2, the renewable energy and load demand uncertainty set are specifically:

[0017]

[0018] Where t is the current scheduling period; and is the wind power and photovoltaic power output during period t; and The upper and lower limits of wind power output in period t; and is the upper and lower limits of photovoltaic output during period t; d t is the load demand during period t; and are the upper and lower limits of load demand during period t; and is the positive and negative reserve demand during period t; and are the positive and negative reserve capacity limits during period t.

[0019] Preferably, in step S3, the objective function is specifically:

[0020]

[0021] Where T is the set of scheduling periods; τ is the period length; The unit price of electricity purchased by the microgrid system from the main grid during period t; The unit price of electricity sold by the microgrid system to the main grid during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the positive reserve and negative reserve unit price in period t; and is the amount of wind and solar power abandoned during period t; is the energy storage charging and discharging power during period t; and are the positive and negative reserve capacity limits during period t.

[0022] Preferably, the constraints satisfied by the microgrid system scheduling operation include:

[0023] Power balance constraints, charging / discharging power limits, upper and lower bounds of energy storage energy levels, energy storage SOC dynamic equations, wind and solar power abandonment constraints, positive and negative reserve positive value limits, and power exchange limits between microgrids and the main grid.

[0024] Preferably, the power balance constraint is:

[0025]

[0026] Charge / discharge power limit:

[0027]

[0028] The upper and lower bounds of energy storage level are:

[0029]

[0030] Energy storage SOC dynamic equation:

[0031]

[0032] Wind curtailment constraints:

[0033]

[0034] Abandonment Constraints:

[0035]

[0036] Positive and negative reserve positive value limits:

[0037]

[0038] Limitations on power exchange between microgrid and main grid:

[0039]

[0040] Among them, Ω t is an uncertain set; is the energy storage charging and discharging power during period t; and is the amount of wind and solar power abandoned during period t; and is the wind power and photovoltaic power output during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the positive and negative reserve capacity limit for period t; d t is the load demand during period t; and is the positive and negative reserve demand during period t; and are the charging and discharging power limits of the energy storage system during period t; E t is the energy level of the energy storage system at the end of period t; and They are the upper and lower bounds of the energy level of the energy storage system at the end of period t respectively; and The upper and lower limits of power exchanged with the main network during period t; and is the positive and negative reserve capacity limit for period t; is the uncertainty in period t; is the realized value of the uncertainty from period 1 to period T, h(·) and h -1 (·) is an auxiliary function.

[0041] Preferably, the auxiliary function h(·) and its inverse function are:

[0042]

[0043] Among them, τ is the length of a period; η c and η d are the charging and discharging efficiency coefficients respectively; x is the independent variable of the auxiliary variable, corresponding to the discharge and charging power p of the energy storage device t .

[0044] Preferably, in step S4, the range of scheduling solutions that meet feasibility and safety in each time period of the multi-stage robust optimization model of the microgrid system is as follows:

[0045]

[0046] in, are the minimum and maximum values ​​of the safety range at the end of period t-1 respectively; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; d t and are the upper and lower limits of load demand during period t; and is the positive and negative reserve capacity limit for period t; is the lower limit of wind power output during period t; is the lower limit of photovoltaic output during period t; and are the charging and discharging power limits of the energy storage system during period t; E t-1 and are the upper and lower bounds of the energy level of the energy storage system at the end of period t-1, respectively; min and max are the minimum and maximum functions, respectively; h(·) is an auxiliary function.

[0047] Preferably, step S5 is specifically:

[0048] The system operating parameters and uncertainty set parameters are obtained, and the day-ahead reserve supply model is solved once by the solver to obtain the decision feasibility range, optimal positive and negative reserve capacity, and optimal power injection curve of the microgrid system.

[0049] Preferably, the objective function for minimizing the operating cost within the scheduling period is:

[0050]

[0051] The power exchange between the microgrid and the main grid is limited to:

[0052]

[0053] The positive and negative reserve positive value limits are:

[0054]

[0055] The prerequisite for the system to be solvable is:

[0056]

[0057] The safe range of energy storage level is:

[0058]

[0059] Where T is the set of scheduling periods; τ is the length of a period; The unit price of electricity purchased by the microgrid system from the main grid during period t; The unit price of electricity sold by the microgrid system to the main grid during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the positive reserve and negative reserve unit price in period t; and is the amount of wind and solar power abandoned during period t; is the energy storage charging and discharging power during period t; and is the positive and negative reserve capacity limit for period t; Ω t is an uncertain set; and The upper and lower limits of power exchanged with the main network during period t; and are the upper and lower limits of load demand during period t; and are the charging and discharging power limits of the energy storage system during period t respectively; is the lower limit of wind power output during period t; is the lower limit of photovoltaic output during period t; are the minimum and maximum values ​​of the safety range at the end of period t-1 respectively; and are the upper and lower bounds of the energy level of the energy storage system at the end of period t-1, respectively; min and max are the minimum and maximum functions, respectively; h(·) is an auxiliary function.

[0060] In a second aspect, an embodiment of the present invention provides a microgrid self-dispatching system including energy storage equipment that provides active backup, characterized in that it includes:

[0061] System module, building a system framework for microgrid self-dispatching technology with energy storage equipment that provides active backup;

[0062] The data module analyzes the dispatching process of the microgrid with energy storage equipment that provides active backup in the system framework of the microgrid self-dispatching technology with energy storage equipment, establishes a decision-dependent uncertainty set for the uncertainty of positive and negative backup demand; and establishes a renewable energy and load demand uncertainty set based on the historical information of random factors obtained;

[0063] Function module, which obtains the key parameters of the microgrid system, constructs the objective function with the goal of minimizing the operating cost under the expected scenario, and constructs a multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup based on the obtained renewable energy and load demand uncertainty set;

[0064] The optimization module uses the obtained multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup to establish a scheduling plan that meets the feasibility and safety requirements of the microgrid system in each period by using its constraint structure characteristics;

[0065] The scheduling module establishes a mixed integer programming day-ahead scheduling model for a microgrid with energy storage equipment that provides active backup based on the obtained multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup and the obtained scheduling scheme, solves the decision feasibility range, optimal positive and negative backup capacity and optimal power injection curve of the microgrid system, and realizes self-scheduling of the microgrid based on the obtained results.

[0066] In a third aspect, a computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the above-mentioned method for self-dispatching a microgrid containing an energy storage device that provides active backup are implemented.

[0067] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for self-dispatching a microgrid containing energy storage equipment that provides active backup.

[0068] Compared with the prior art, the present invention has at least the following beneficial effects:

[0069] A self-dispatching method for a microgrid with energy storage equipment that provides active backup is established by using the understanding of the dispatching mode of the microgrid system and the in-depth understanding of the backup capability of the energy storage system to establish a system framework diagram of the self-dispatching technology of a microgrid with energy storage equipment that provides active backup, reasonably and accurately describing the main functions of each component when the microgrid with energy storage provides backup, as well as the dispatching logic and dispatching process of the microgrid when realizing this concept; based on the analysis of the dispatching process of the microgrid with energy storage providing backup in the system framework diagram, a decision-dependent uncertainty set is established for the uncertainty range of positive and negative backup demand; based on the historical data of random factors in the microgrid system, a renewable energy (wind power, photovoltaic, etc.) and load demand uncertainty set is established to describe the distribution of random factors and represent the changes of random factors; based on the above The system framework diagram of the self-dispatching technology of a microgrid with energy storage equipment that provides active backup and two types of uncertainty sets are described, and a multi-stage robust optimization model of a microgrid with energy storage equipment that provides active backup is established. The model comprehensively considers the dispatching process of the microgrid with energy storage providing backup, the physical characteristics of each physical device, and the operating conditions of the microgrid system, and can reasonably reflect the dispatching characteristics of the microgrid with energy storage providing active backup; through the analysis of the constraint structure in the multi-stage model of the microgrid with energy storage equipment that provides active backup, an effective method is proposed, which can give the effective positive and negative backup capacity that can ensure the safe operation of the microgrid system and can cope with uncertain backup demand, the day-ahead power injection curve that ensures the safe operation of the microgrid system, and the safe dispatching range of decisions in each time period. If the physical equipment in the microgrid system is reasonably dispatched within the safety range, the positive and negative backup demands of the external system or the main grid are within the given positive and negative backup capacity range, and the main grid provides power to the microgrid according to the power injection curve, it can be ensured that the realization of any random factors in the uncertain set can be dealt with; based on the positive and negative backup capacity, the day-ahead power injection curve and the safe dispatch range of the decision given above, a hybrid integer programming dispatch model for a microgrid with energy storage equipment that provides active backup can be established, and the model aims to optimize the operating cost under the expected scenario.

[0070] Furthermore, obtaining the equipment composition in the microgrid system and establishing a system framework diagram of the microgrid self-dispatching technology with energy storage equipment that provides active backup can provide technical support for the microgrid self-dispatching technology with energy storage equipment that provides active backup.

[0071] Furthermore, according to the process and method of reserve provision scheduling, a decision-dependent uncertainty set is established for the uncertainty range of positive and negative reserve requirements.

[0072] Furthermore, the acquisition of relevant information such as equipment parameters, uncertain parameters (power load, wind power output, photovoltaic output), economic parameters, etc. can provide data support for the self-dispatching of microgrids containing energy storage equipment that provide active backup.

[0073] Furthermore, uncertainty sets are established for random factors such as electricity load, wind power output, and photovoltaic output to reflect the range of variation of uncertain quantities and make them consistent with actual conditions.

[0074] Furthermore, taking the minimization of operating costs under the expected scenario within the dispatching cycle as the objective function, the operating requirements of the self-dispatching of the microgrid with energy storage equipment that provides active backup are comprehensively considered, and a multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup is established. This model is a conceptual model. In theory, the dispatching scheme obtained by this model can ensure the safety and feasibility of the dispatching scheme and improve the operating economy of the dispatching scheme. However, since the model needs to consider the feasibility of the scenario with an infinite number of random factors, it is impossible to directly obtain an economically feasible dispatching scheme.

[0075] Furthermore, through the analysis of the multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup, the feasible range to ensure the safe operation of the dispatching scheme, the positive and negative backup capacity to ensure the safety and feasibility of the system, and the power injection curve from the main grid to the microgrid are given. For the microgrid system with energy storage equipment under different parameters, if it can be guaranteed that each main grid can install the optimal power injection curve to provide power to the microgrid in the day before and the dispatching scheme of each time period is within the safe decision range, then any positive and negative backup demand of the external system or the main grid within the positive and negative backup capacity range, and the realization value of any random variable in the future time period (within the given uncertainty set range) can be handled by the microgrid system with energy storage.

[0076] It can be understood that the beneficial effects of the second aspect mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0077] In summary, the present invention provides an economically feasible scheduling scheme for a microgrid containing energy storage equipment with active standby, and provides technical support for the economic feasibility of a planning scheme for a microgrid containing energy storage equipment with active standby.

[0078] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings to be used in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0080] Figure 1 A system framework diagram of a microgrid self-dispatching technology with active standby and energy storage equipment provided by the present invention;

[0081] Figure 2 It is a schematic diagram of the process of the present invention;

[0082] Figure 3 It is the operation scheduling flow chart of the present invention;

[0083] Figure 4 A block diagram of an electronic device provided according to an embodiment of the present invention;

[0084] Figure 5 It is the upper and lower limits of load demand and the expected scenario diagram of load demand;

[0085] Figure 6 It is the upper and lower limits of wind power output and the expected scenario diagram of wind power output;

[0086] Figure 7 It is the upper and lower limits of photovoltaic output and the expected scenario diagram of photovoltaic output;

[0087] Figure 8 The day-ahead reserve capacity and power injection curves obtained based on the method proposed in the present invention;

[0088] Fig. 9 A robust feasible region diagram of energy storage energy level obtained based on the method proposed in the present invention;

[0089] Fig.10 A schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0090] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0091] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0092] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0093] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0094] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0095] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0096] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0097] See also Figure 1, providing active backup microgrids with energy storage equipment, including energy storage systems, power loads (including mid-stage loads, transferable loads, flexible loads, etc.), wind power, photovoltaic and other renewable energy power stations; the microgrid is connected to the main grid system and can exchange energy with the main grid system, that is, it can purchase electricity from the main grid system and sell electricity to the main grid system. In addition, the energy storage system, power loads, and renewable energy sources such as wind power and photovoltaics are connected through the same bus, and can directly exchange energy in the microgrid, that is, the load can obtain electricity from the energy storage system and wind power, photovoltaic and other renewable energy power stations; the energy storage system can output electricity to the power load, and can also obtain electricity from wind power, photovoltaic and other renewable energy power stations; wind power, photovoltaic and other renewable energy generation can output electricity to the power load and the energy storage system.

[0098] The specific structural features of the microgrid containing energy storage equipment for active standby provided by the present invention are as follows:

[0099] The battery energy storage system includes battery packs, battery management systems, power conversion systems, collection lines and other auxiliary equipment for the storage, conversion and release of electrical energy;

[0100] Photovoltaic power stations include photovoltaic arrays, charge and discharge controllers, batteries and inverters, and use the photovoltaic effect of semiconductor interfaces to directly convert light energy into electrical energy.

[0101] The wind power source includes a wind turbine generator set, a tower supporting the generator set, a battery charge controller, an inverter, a load unloader, a grid connection controller, and a battery pack, which converts the kinetic energy of wind into electrical energy.

[0102] The electricity load is divided into various industrial loads, agricultural loads, transportation loads and people's daily life loads. Electricity is consumed to realize the operation of industry, agriculture, transportation and people's daily life. The total load of the power system is the sum of the total power consumed by all electrical equipment in the system.

[0103] Compared with the power system or other market participants, the capacity of the microgrid system with energy storage is lower, so it participates in the market as a price taker. According to the different stages of dispatch, the decision variables are divided into two categories, namely, the day-ahead stage decision variables and the real-time stage decision variables. The day-ahead decision variables include increasing the positive / negative reserve capacity to the main grid or external system (gray solid line) and the day-ahead power injection curve (orange solid line). The real-time stage decision variables include the positive / negative reserve amount provided to the main grid (green dotted line), as well as the dispatch decisions in the microgrid (black dotted line), such as the charging / discharging power of energy storage and the discarded amount of renewable energy output. The dispatch process is described as follows.

[0104] In the day-ahead phase, the microgrid with energy storage, as an independent backup supplier, will conduct transactions with the main grid in two aspects:

[0105] 1) Positive / negative reserve capacity provided to external systems or the main grid;

[0106] 2) The power injection curve obtained (provided) by the microgrid from (to) the main grid, which is an important resource to meet the feasibility of the system. There are two points to explain about the power injection curve.

[0107] First of all, the concept of "power injection curve" is introduced mainly to distinguish it from the concept of "exchange power" in the backup consumer model. The similarities between the two are that they both refer to the amount of power exchanged between the microgrid and the main grid, and a positive value indicates that the main grid provides power to the microgrid (buys electricity from the main grid), and a negative value indicates that the microgrid provides surplus power to the main grid (sells electricity to the main grid). The main difference is that the power injection curve is a deterministic curve determined a day ago, not a specific area. This means that the exchange power between the microgrid and the main grid remains unchanged during the scheduling process, and the main grid does not need to provide additional backup services. Therefore, the scheduling difficulty of the main grid and the burden on the main grid will also be reduced.

[0108] Second, even if the system does not consider providing backup, the power injection profile may be necessary to ensure the feasibility of the system.

[0109] Once the day-ahead decision is made, the microgrid with energy storage can not only achieve optimal self-dispatch for any uncertainty in the real-time stage, but also provide backup services for the main grid within the backup capacity given on the day-ahead.

[0110] The present invention provides an active backup microgrid containing energy storage equipment, which can cope with uncertain renewable energy output and uncertain load demand without the need for backup support from the main power grid, and achieve optimal self-dispatching; it can provide backup services for external systems (or the main power grid) when the backup demand is uncertain, thereby increasing the revenue of the microgrid and reducing the total operating cost.

[0111] See also Figure 2 The present invention provides a self-dispatching method for a microgrid including an energy storage device for providing active standby, comprising the following steps:

[0112] S1. Establish a system framework diagram of microgrid self-dispatching technology with energy storage equipment to provide active backup;

[0113] Specifically include:

[0114] (1) The composition of the microgrid system with energy storage as a backup provider;

[0115] (2) The microgrid system with energy storage provides a backup operating mode.

[0116] In the day-ahead phase, the microgrid with energy storage, as an independent backup supplier, will conduct transactions with the main grid in two aspects:

[0117] 1) Positive / negative reserve capacity provided to external systems or the main grid;

[0118] 2) The power injection curve obtained (provided) by the microgrid from (to) the main grid, which is an important resource to meet the feasibility of the system.

[0119] The power injection curve is a deterministic curve determined on the day-ahead, not a specific area. Once the day-ahead decision is made, the microgrid with energy storage can not only achieve optimal self-dispatch for any uncertain quantity in the real-time stage, but also provide backup services for the main grid within the given backup capacity on the day-ahead.

[0120] S2. Based on the analysis of the dispatching process of the microgrid with energy storage to provide backup in the system framework diagram, a decision-dependent uncertainty set is established for the uncertainty of positive and negative backup demand; based on the historical information of random factors obtained, an uncertainty set of renewable energy such as wind power and photovoltaic power and load demand is established;

[0121] Specifically include:

[0122] (1) Decision-making depends on uncertain sets

[0123]

[0124] Where t is the current scheduling period; and is the positive and negative reserve demand during period t; and are the positive and negative reserve capacity limits during period t.

[0125] (2) Obtaining the uncertainty set parameters, including the upper and lower limits of wind power output during period t and The upper and lower limits of photovoltaic output during period t and Upper and lower limits of load demand during period t and And establish the wind power output uncertainty set, photovoltaic output uncertainty set and load demand uncertainty set.

[0126]

[0127]

[0128] in, and is the wind power and photovoltaic power output during period t; d t is the load demand during period t.

[0129] S3, obtaining key system parameters, taking the minimum operating cost under the expected scenario as the goal, and establishing a multi-stage robust optimization model for the microgrid with energy storage equipment as a backup provider under the uncertainty set obtained in step S2;

[0130] Specifically include:

[0131] (1) Energy storage system parameters, such as the upper and lower bounds of the energy storage capacity of the energy storage system, the charging and discharging efficiency coefficient of the energy storage system, and the maximum charging and discharging power of the energy storage system;

[0132] (2) Operation parameters, such as the total scheduling period, the length of each scheduling period, and the power exchanged with the main grid;

[0133] (3) Economic parameters, such as the price at which the microgrid system buys electricity from the main grid, the price at which it sells electricity to the main grid, and the positive and negative reserve prices.

[0134] With the goal of minimizing the operating cost under the expected scenario, a multi-stage robust optimization model of a microgrid with energy storage equipment that provides active backup is established;

[0135] 1) Objective function

[0136] The objective of the multi-stage robust optimization model for a microgrid with energy storage devices that provides active backup is to minimize the system operating cost within the dispatch period.

[0137]

[0138] The first part of the above formula represents the cost (benefit) of power injection between the microgrid system and the main grid, and the second part represents the benefit of the microgrid system providing backup to the main grid or external system.

[0139] Where T is the set of scheduling periods; τ is the length of a period; The unit price of electricity purchased by the microgrid system from the main grid during period t; The unit price of electricity sold by the microgrid system to the main grid during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the unit price of positive reserve and negative reserve in period t; and is the amount of wind and solar power abandoned during period t; is the energy storage charging and discharging power during period t; and are the positive and negative reserve capacity limits during period t.

[0140] 2) Operational constraints

[0141] The self-dispatching operation of a microgrid with energy storage equipment that provides active backup requires a series of conditions:

[0142] Formula (2) is the power balance constraint, which requires that the algebraic sum of the energy storage charging / discharging power, the wind and solar power abandonment power, and the main grid power injection value must be equal to the algebraic sum of the uncertain wind power output realization value, the uncertain photovoltaic output realization value, the uncertain load demand realization value, and the uncertain positive and negative reserve demand realization value.

[0143]

[0144] Formula (3) is the charge / discharge power limit, which limits the discharge and charge power of the energy storage system:

[0145]

[0146] Formula (4) is the upper and lower bounds of the energy storage level, which is the physical operation requirement in actual operation.

[0147]

[0148] Formula (5) is the energy storage SOC (state of charge) dynamic equation:

[0149]

[0150] Among them, h(·) and h -1 (·) is an auxiliary function with a monotonically decreasing characteristic.

[0151]

[0152] Formula (7) is the wind curtailment constraint:

[0153]

[0154] Formula (8) is the light abandonment constraint:

[0155]

[0156] Formula (9) is the positive and negative reserve positive value limit:

[0157]

[0158] Formula (10) is the power exchange limit between the microgrid and the main grid, which defines the lower and upper limits of power exchange between the microgrid system and the main grid:

[0159]

[0160] Among them, Ω t is an uncertain set; is the energy storage charging and discharging power during period t; and is the amount of wind and solar power abandoned during period t; and is the wind power and photovoltaic power output during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the positive and negative reserve capacity limit for period t; d t is the load demand during period t; and is the positive and negative reserve demand during period t; and are the charging and discharging power limits of the energy storage system during period t; E t is the energy level of the energy storage system at the end of period t; E t and They are the upper and lower bounds of the energy level of the energy storage system at the end of period t respectively; and The upper and lower limits of power exchanged with the main network during period t; and is the positive and negative reserve capacity limit for period t; is the uncertainty matrix of period t It is the realized value of the uncertain quantity from period 1 to period T. and Respectively represent the charging and discharging power of the energy storage system during period t; η c and η d They represent the charging and discharging efficiency coefficients during period t respectively; x is the independent variable of the auxiliary variable, corresponding to the discharge and charging power p of the energy storage device t .

[0161] S4. Based on the multi-stage robust optimization model obtained in step S3, using its constraint structure characteristics, establish the dispatching scheme range (11) that satisfies feasibility and safety in each period of the microgrid system;

[0162]

[0163] in, are the minimum and maximum values ​​of the safety range at the end of period t-1 respectively; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; d t and are the upper and lower limits of load demand during period t; and is the positive and negative reserve capacity limit for period t; is the lower limit of wind power output during period t; is the lower limit of photovoltaic output during period t; and are the charging and discharging power limits of the energy storage system during period t; E t-1 and are the upper and lower bounds of the energy level of the energy storage system at the end of period t-1, respectively; min and max are the minimum and maximum functions, respectively; h(·) is an auxiliary function.

[0164] Specifically include:

[0165] First, for brevity, the real-time stage decision variables are abbreviated as:

[0166]

[0167] In order to simplify the constraint structure and facilitate the subsequent analysis, select E t As core variables, replace real-time decision variables in constraints and The specific details are as follows.

[0168] First, according to equations (5) and (6), It is equivalent to formula (13).

[0169]

[0170] According to equation (3), equation (13) and the monotonically decreasing characteristics of the auxiliary function h(·), we can get

[0171]

[0172] According to formula (2) and formula (13), Convert to

[0173]

[0174] Furthermore, according to equation (15), constraint (7) can be transformed into equation (16).

[0175]

[0176] Rearranging equation (16) yields

[0177]

[0178] According to equations (8) and (17), if we want to ensure If it is not empty, constraint (18) must be satisfied.

[0179]

[0180] E t -E t-1 Rearranging (18) for the variables yields

[0181]

[0182] From the above analysis, we can see that the decision variables in the real-time stage and The relevant constraints can be transformed into t -E t-1 Therefore, by transforming the constraints, and variable.

[0183] For the sake of simplicity, formula (20) is introduced.

[0184]

[0185] Then, from equation (4), equation (14), equation (19) and equation (20), equation (2) to equation (8) can be rewritten as:

[0186]

[0187] If there is a feasible solution that satisfies constraints (2)-(8), then (21) should be non-empty. That is,

[0188]

[0189] Specifically, in each time period t All items should be less than Therefore, we can get three sets of inequalities.

[0190]

[0191]

[0192]

[0193] According to equations (23)-(25), the following conclusions are obtained.

[0194] From constraints (3)-constraint (4), constraints (7) and constraints (8), we can see that the inequalities in the equations always hold.

[0195] The inequality in formula (24) and the state variable E t It is irrelevant, and equation (24) can be considered as a prerequisite. For any uncertain realization, equation (24) should always be satisfied, so it can be further known that equation (26) must be established.

[0196]

[0197] Rearranging equation (26) shows that equation (27) satisfies.

[0198]

[0199] In formula (25), the inequality and E t-1 This is to ensure that E t Sufficient conditions for the existence of a feasible solution.

[0200] For any uncertain realization, the inequality in equation (25) should hold. Then we have

[0201]

[0202] Note that the inequality in (28) is only to ensure that E t When the range is not empty, E t-1 In addition, E t-1 It also needs to satisfy its own physical constraints (4). Then we have

[0203]

[0204] Formula (29) gives the feasible range of E in period t (single period) to ensure the requirements of unexpectedness and multi-stage robustness. In order to ensure the feasibility of the solution in the entire scheduling period, Formula (29) should be extended to the entire scheduling period.

[0205] According to the recursive theory, for the period t = T, we have and For the period t=T-1, the formula can be further obtained based on formula (29).

[0206]

[0207] For t = T-2, we have

[0208]

[0209] Through recursive theory, we can know that for each time period, formula (32) should be satisfied.

[0210]

[0211] S5. Please refer to Figure 3 According to the multi-stage robust optimization model of the microgrid with energy storage equipment providing active backup obtained in step S3 and the dispatching scheme range obtained in step S4, a hybrid integer programming day-ahead dispatching model of the microgrid with energy storage equipment providing active backup is established, and the decision feasibility range, optimal positive and negative backup capacity and optimal power injection curve of the microgrid system are directly solved.

[0212] Formula (33) is the objective function, which requires that the operating cost within the dispatch period be minimized, including the cost (benefit) of power injection between the microgrid system and the main grid, and the benefit of the microgrid system providing backup to the main grid or external system.

[0213]

[0214] Formula (34) is the power exchange limit between the microgrid and the main grid, which limits the lower and upper limits of power exchange between the microgrid system and the main grid:

[0215]

[0216] Formula (35) is the positive and negative reserve positive value limit:

[0217]

[0218] The prerequisite for the solution of the system (36) is:

[0219]

[0220] Formula (37) is the safe range of energy storage level:

[0221]

[0222] Where T is the set of scheduling periods; τ is a time period; The unit price of electricity purchased from the main grid for the microgrid system; The unit price of electricity sold by the microgrid system to the main grid; The day-ahead power injection of the microgrid from (positive) to (negative) the main grid; and is the unit price for positive standby and negative standby; and The amount of wind and solar power abandoned; It is the charging and discharging power of energy storage; and is the positive and negative reserve capacity limit; Ω t is an uncertain set; and To exchange power upper and lower limits with the main network; and The upper and lower limits of load demand; and They are respectively the charging and discharging power limits of the energy storage system; It is the lower limit of wind power output; It is the lower limit of photovoltaic output; are the minimum and maximum values ​​of the safety range in period t-1 respectively; and are the upper and lower bounds of the energy level of the energy storage system in period t-1 respectively; min and max are the minimum and maximum functions respectively; h(·) is an auxiliary function.

[0223] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits", "modules" or "platforms".

[0224] In another embodiment of the present invention, a microgrid self-dispatching system containing energy storage devices that provides active backup is provided. The system can be used to implement the above-mentioned microgrid self-dispatching method containing energy storage devices that provides active backup. Specifically, the microgrid self-dispatching system containing energy storage devices that provides active backup includes a system module, a data module, a function module, an optimization module and a scheduling module.

[0225] Among them, the system module builds a system framework for microgrid self-dispatching technology with energy storage equipment that provides active backup;

[0226] The data module analyzes the dispatching process of the microgrid with energy storage equipment that provides active backup in the system framework of the microgrid self-dispatching technology with energy storage equipment, establishes a decision-dependent uncertainty set for the uncertainty of positive and negative backup demand; and establishes a renewable energy and load demand uncertainty set based on the historical information of random factors obtained;

[0227] Function module, which obtains the key parameters of the microgrid system, constructs the objective function with the goal of minimizing the operating cost under the expected scenario, and constructs a multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup based on the obtained renewable energy and load demand uncertainty set;

[0228] The optimization module uses the obtained multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup to establish a scheduling plan that meets the feasibility and safety requirements of the microgrid system in each period by using its constraint structure characteristics;

[0229] The scheduling module establishes a mixed integer programming day-ahead scheduling model for a microgrid with energy storage equipment that provides active backup based on the obtained multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup and the obtained scheduling scheme, solves the decision feasibility range, optimal positive and negative backup capacity and optimal power injection curve of the microgrid system, and realizes self-scheduling of the microgrid based on the obtained results.

[0230] In another embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used to provide an operation of a microgrid self-dispatching method containing an active standby energy storage device, including:

[0231] Construct a system framework for self-dispatching technology of microgrids with energy storage devices that provide active backup; analyze the dispatching process of microgrids with energy storage devices that provide active backup in the system framework of self-dispatching technology of microgrids with energy storage devices, and establish a decision-dependent uncertainty set for the uncertainties of positive and negative backup demands; establish an uncertainty set of renewable energy and load demands based on the historical information of random factors obtained; obtain the key parameters of the microgrid system, construct an objective function with the minimum operating cost under the expected scenario as the goal, and construct a multi-stage robust optimization model of microgrids with energy storage devices that provide active backup based on the obtained uncertainty set of renewable energy and load demands; based on the obtained multi-stage robust optimization model of microgrids with energy storage devices that provide active backup, use its constraint structure characteristics to establish a dispatching scheme that meets the feasibility and safety of the microgrid system in each period; based on the obtained multi-stage robust optimization model of microgrids with energy storage devices that provide active backup and the obtained dispatching scheme, establish a mixed integer programming day-ahead dispatching model of microgrids with energy storage devices that provide active backup, solve the decision feasibility range, optimal positive and negative backup capacity and optimal power injection curve of the microgrid system, and realize self-dispatching of the microgrid based on the obtained results.

[0232] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0233] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0234] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0235] One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the microgrid self-dispatching method for providing active backup with energy storage equipment in the above embodiment; one or more instructions in the computer-readable storage medium are loaded and executed by the processor as follows:

[0236] Construct a system framework for self-dispatching technology of microgrids with energy storage devices that provide active backup; analyze the dispatching process of microgrids with energy storage devices that provide active backup in the system framework of self-dispatching technology of microgrids with energy storage devices, and establish a decision-dependent uncertainty set for the uncertainties of positive and negative backup demands; establish an uncertainty set of renewable energy and load demands based on the historical information of random factors obtained; obtain the key parameters of the microgrid system, construct an objective function with the minimum operating cost under the expected scenario as the goal, and construct a multi-stage robust optimization model of microgrids with energy storage devices that provide active backup based on the obtained uncertainty set of renewable energy and load demands; based on the obtained multi-stage robust optimization model of microgrids with energy storage devices that provide active backup, use its constraint structure characteristics to establish a dispatching scheme that meets the feasibility and safety of the microgrid system in each period; based on the obtained multi-stage robust optimization model of microgrids with energy storage devices that provide active backup and the obtained dispatching scheme, establish a mixed integer programming day-ahead dispatching model of microgrids with energy storage devices that provide active backup, solve the decision feasibility range, optimal positive and negative backup capacity and optimal power injection curve of the microgrid system, and realize self-dispatching of the microgrid based on the obtained results.

[0237] See also Fig.10 , the terminal device is a computer device, and the computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the self-dispatching method of a microgrid containing energy storage devices providing active standby in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the self-dispatching system of a microgrid containing energy storage devices providing active standby in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0238] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Fig.10This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0239] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, central processing units, graphics processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, data processing logic based on quantum computing, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0240] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0241] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0242] Any reference to memory, database or other media used in the embodiments provided in the present application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0243] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0244] See also Figure 4 The terminal device is an electronic device 600, and the electronic device is in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0245] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 can perform the following steps: Figure 2 Follow the steps shown in .

[0246] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0247] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0248] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0249] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, etc.

[0250] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0251] It is planned to invest in the construction of a microgrid system including energy storage, wind farms and photovoltaic units in a microgrid park, and obtain the relevant information required for the dispatch of the microgrid system including energy storage equipment that provides active backup. Table 1 shows the main parameters of the microgrid system. Figure 5 , Figure 6 and Figure 7 It displays information related to load demand, wind power output, and photovoltaic output.

[0252] Table 1 Main parameters of microgrid system

[0253]

[0254] Table 1 contains the dispatch parameter information of 24 time periods, where the dispatch duration of each time period is 1 hour. The microgrid system can exchange energy with the gateway, that is, it can buy electricity from the gateway or sell electricity to the gateway, and the maximum purchase power is 4MW, and the maximum selling power is 4MW. In addition, the microgrid system contains energy storage equipment, which can transfer energy, and the physical range of its energy storage energy level is [2, 7.6] MWh. The energy level of the energy storage equipment in the initial period is 4.8 MWh, the maximum charge and discharge power is 2MW, and the charge and discharge efficiency is 90%.

[0255] Figure 5 , Figure 6 and Figure 7 It involves 24 time periods, each of which has a length of 1, and includes upper and lower limit information of load demand and expected load demand information, upper and lower limit information of wind power output and expected wind power output information, and upper and lower limit information of photovoltaic output and expected photovoltaic output information.

[0256] Based on the above parameters and uncertain information, the scheduling performance of the method can be obtained in the day-ahead phase as follows: Figure 8 and Fig. 9 shown.

[0257] The day-ahead scheduling results are as follows: Figure 8 As shown, the orange solid line is the power injection curve, and the heights of the green and blue column areas represent the maximum negative reserve capacity and positive reserve capacity that the microgrid can provide, respectively.

[0258] The power injection curve is determined in the day-ahead phase, and according to the curve, the main grid provides (obtains) specific power values ​​to (from) the microgrid in real time. By calculating the microgrid scheduling problem, it can be seen that when the injected power in each period of this case is zero, there is no feasible scheduling solution for the microgrid. This means that injected power is necessary for the stability and security of the microgrid. This is because energy storage can only transfer energy but cannot generate energy, so it may not be able to fill the power difference between wind power output and load demand. In addition, from Figure 8The trend of the orange solid line (power injection curve) shows that when the PJM market electricity price is low, the microgrid tends to buy electricity from the main grid (positive power injection), and vice versa. Therefore, it can be proved that the scheduling result obtained based on the method proposed in the present invention meets the economic requirements.

[0259] in addition, Figure 8 The paper shows that the microgrid with energy storage can provide positive and negative reserve capacity to the main grid or external system based on the method proposed in this chapter. Figure 8 It can be seen that the microgrid with energy storage can provide sufficient positive and negative backup capacity, indicating that the system has great potential in providing backup services. Figure 8 For any positive or negative reserve demand within the reserve capacity given in , the microgrid can find a feasible scheduling solution according to the method proposed in the present invention.

[0260] Finally, the range of feasible scheduling solutions is analyzed, that is, the feasible / safe domain of the energy level of the energy storage device, such as Fig. 9 As shown. Fig. 9 , we can draw the following conclusions: First, due to operational constraints, especially cross-period coupling constraints, the feasible region of energy storage energy levels is usually smaller than its physical boundaries. Second, Fig. 9 The feasible domain in is not empty, indicating that Figures 5 to 7 Any output value of renewable energy in Figure 8 For any reserve demand within the reserve capacity range, there is always a feasible solution that satisfies all operating constraints in the microgrid. For operators, the robust feasible region is extremely convenient. They only need to choose appropriate decisions within the feasible region of each time period to effectively deal with complex system constraints and uncertainties.

[0261] In summary, the present invention provides a self-dispatching method and system for a microgrid containing energy storage equipment that provides active backup. The microgrid containing energy storage can act as a backup provider to provide backup auxiliary services to an external system or a main grid, thereby increasing the total revenue of the microgrid.

[0262] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0263] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0264] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0265] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0266] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0267] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0268] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0269] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0270] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0271] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0272] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. Provide a self-dispatching method for a microgrid containing energy storage equipment with active standby, characterized in that: The following steps are involved: S1. Build a system framework for self-dispatching technology of microgrids with energy storage devices that provide active backup; S2. Analyze the dispatching process of the microgrid containing energy storage equipment that provides active backup in the system framework of the microgrid self-dispatching technology containing energy storage equipment, establish a decision-dependent uncertainty set for the uncertainty of positive and negative backup demand; establish a renewable energy and load demand uncertainty set based on the historical information of random factors obtained; S3, obtaining key parameters of the microgrid system, constructing an objective function with the goal of minimizing the operating cost under the expected scenario, and constructing a multi-stage robust optimization model of a microgrid with energy storage equipment that provides active backup based on the renewable energy and load demand uncertainty set obtained in step S2; S4, according to the multi-stage robust optimization model of the microgrid with energy storage equipment providing active backup obtained in step S3, using its constraint structure characteristics to establish a scheduling plan that meets feasibility and safety for the microgrid system in each period; S5. Based on the multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup obtained in step S3 and the scheduling plan obtained in step S4, a hybrid integer programming day-ahead scheduling model for the microgrid with energy storage equipment that provides active backup is established, the decision feasibility range, the optimal positive and negative backup capacity and the optimal power injection curve of the microgrid system are solved, and self-scheduling of the microgrid is achieved based on the results obtained.

2. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 1, characterized in that: In step S2, the renewable energy and load demand uncertainty set are specifically: Where t is the current scheduling period; and is the wind power and photovoltaic power output during period t; and The upper and lower limits of wind power output in period t; and is the upper and lower limits of photovoltaic output during period t; d t is the load demand during period t; and d t are the upper and lower limits of load demand during period t; + r t and - r t is the positive and negative reserve demand during period t; and are the positive and negative reserve capacity limits during period t.

3. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 1, characterized in that: In step S3, the objective function is specifically: Where T is the set of scheduling periods; τ is the period length; The unit price of electricity purchased by the microgrid system from the main grid during period t; The unit price of electricity sold by the microgrid system to the main grid during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the unit price of positive reserve and negative reserve in period t; and is the amount of wind and solar power abandoned during period t; is the energy storage charging and discharging power during period t; and are the positive and negative reserve capacity limits during period t.

4. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 3, characterized in that: The constraints satisfied by the microgrid system dispatching operation include: Power balance constraints, charging / discharging power limits, upper and lower bounds of energy storage energy levels, energy storage SOC dynamic equations, wind and solar power abandonment constraints, positive and negative reserve positive value limits, and power exchange limits between microgrids and the main grid.

5. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 4, characterized in that: Power balance constraints: Charge / discharge power limit: The upper and lower bounds of energy storage level are: Energy storage SOC dynamic equation: Wind curtailment constraints: Abandonment Constraints: Positive and negative reserve positive value limits: Limitations on power exchange between microgrid and main grid: Among them, Ω t is an uncertain set; is the energy storage charging and discharging power during period t; and is the amount of wind and solar power abandoned during period t; and is the wind power and photovoltaic power output during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the positive and negative reserve capacity limit for period t; d t is the load demand during period t; r t + and r t - is the positive and negative reserve demand during period t; and are the charging and discharging power limits of the energy storage system during period t; E t is the energy level of the energy storage system at the end of period t; and E t They are the upper and lower bounds of the energy level of the energy storage system at the end of period t respectively; and g t The upper and lower limits of power exchanged with the main network during period t; and is the positive and negative reserve capacity limit for period t; is the uncertainty in period t; is the realized value of the uncertainty from period 1 to period T, h(·) and h -1 (·) is an auxiliary function.

6. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 5, characterized in that: The auxiliary function h(·) and its inverse function are: Among them, τ is the length of a period; η c and η d are the charging and discharging efficiency coefficients respectively; x is the independent variable of the auxiliary variable, corresponding to the discharge and charging power p of the energy storage device t .

7. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 1, characterized in that: In step S4, the scope of the dispatching scheme that meets the feasibility and safety requirements of the multi-stage robust optimization model of the microgrid system in each period is as follows: in, are the minimum and maximum values ​​of the safety range at the end of period t-1 respectively; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and d t are the upper and lower limits of load demand during period t; and is the positive and negative reserve capacity limit for period t; is the lower limit of wind power output during period t; is the lower limit of photovoltaic output during period t; and are the charging and discharging power limits of the energy storage system during period t respectively; and E t-1 are the upper and lower bounds of the energy level of the energy storage system at the end of period t-1, respectively; min and max are the minimum and maximum functions, respectively; h(·) is an auxiliary function.

8. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 1, characterized in that: Step S5 is specifically as follows: The system operating parameters and uncertainty set parameters are obtained, and the day-ahead reserve supply model is solved once by the solver to obtain the decision feasibility range, optimal positive and negative reserve capacity, and optimal power injection curve of the microgrid system.

9. The self-dispatching method for a microgrid containing energy storage equipment providing active backup according to claim 8, characterized in that: The objective function for minimizing the operating cost within the scheduling period is: The power exchange between the microgrid and the main grid is limited to: The positive and negative reserve positive value limits are: The prerequisite for the system to be solvable is: The safe range of energy storage level is: Where T is the set of scheduling periods; τ is the length of a period; The unit price of electricity purchased by the microgrid system from the main grid during period t; The unit price of electricity sold by the microgrid system to the main grid during period t; is the day-ahead power injection of the microgrid from (positive) to (negative) the main grid during period t; and is the unit price of positive reserve and negative reserve in period t; and is the amount of wind and solar power abandoned during period t; is the energy storage charging and discharging power during period t; and is the positive and negative reserve capacity limit for period t; Ω t is an uncertain set; and g t The upper and lower limits of power exchanged with the main network during period t; and d t are the upper and lower limits of load demand during period t; and are the charging and discharging power limits of the energy storage system during period t respectively; is the lower limit of wind power output during period t; is the lower limit of photovoltaic output during period t; are the minimum and maximum values ​​of the safety range at the end of period t-1 respectively; and E t-1 are the upper and lower bounds of the energy level of the energy storage system at the end of period t-1, respectively; min and max are the minimum and maximum functions, respectively; h(·) is an auxiliary function.

10. A microgrid self-dispatching system with energy storage equipment that provides active backup, characterized in that: include: System module, building a system framework for microgrid self-dispatching technology with energy storage equipment that provides active backup; The data module analyzes the dispatching process of the microgrid with energy storage equipment that provides active backup in the system framework of the microgrid self-dispatching technology with energy storage equipment, establishes a decision-dependent uncertainty set for the uncertainty of positive and negative backup demand; and establishes a renewable energy and load demand uncertainty set based on the historical information of random factors obtained; Function module, which obtains the key parameters of the microgrid system, constructs the objective function with the goal of minimizing the operating cost under the expected scenario, and constructs a multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup based on the obtained renewable energy and load demand uncertainty set; The optimization module uses the obtained multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup to establish a scheduling plan that meets the feasibility and safety requirements of the microgrid system in each period by using its constraint structure characteristics; The scheduling module establishes a mixed integer programming day-ahead scheduling model for a microgrid with energy storage equipment that provides active backup based on the obtained multi-stage robust optimization model of the microgrid with energy storage equipment that provides active backup and the obtained scheduling scheme, solves the decision feasibility range, optimal positive and negative backup capacity and optimal power injection curve of the microgrid system, and realizes self-scheduling of the microgrid based on the obtained results.

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