阅读说明：本技术 一种可参与电网辅助服务的集中式云储能运行决策方法 (Centralized cloud energy storage operation decision method capable of participating in power grid auxiliary service ) 是由 张宁 刘静琨 王毅 康重庆 于 2019-11-28 设计创作，主要内容包括：本发明涉及一种可参与电网辅助服务的集中式云储能运行决策方法。本方法利用模型预测控制模型,该模型以最小化集中式储能设施在当前时段产生的运行成本与其预计在设定时间范围内产生的运行成本的总合作为目标函数,以充放电功率和集中式储能设施电量作为约束条件；云储能服务提供商根据从电网调控中心获取的当前时段运行参数和根据历史数据预测的运行参数利用上述模型求解出当前时段集中式储能设施用于向云储能用户提供云储能服务的充、放电功率和其用于向电网提供辅助服务的充、放电功率,得到集中式储能设施的控制指令。本发明通过响应电网调控中心发出的充电和放电命令实现对电网调频调峰辅助服务的参与,可提高集中式储能设施的利用率。(The invention relates to a centralized cloud energy storage operation decision method capable of participating in power grid auxiliary service. The method utilizes a model prediction control model, the model takes the sum of the operation cost generated by the minimized centralized energy storage facility in the current time period and the operation cost predicted to be generated in the set time range as a target function, and takes the charge-discharge power and the electric quantity of the centralized energy storage facility as constraint conditions; and the cloud energy storage service provider utilizes the model to solve the charging and discharging power of the centralized energy storage facility in the current period for providing cloud energy storage service for the cloud energy storage users and the charging and discharging power of the centralized energy storage facility for providing auxiliary service for the power grid according to the current period operating parameters acquired from the power grid regulation and control center and the operating parameters predicted according to historical data, and obtains a control instruction of the centralized energy storage facility. The invention realizes the participation of the power grid frequency modulation and peak regulation auxiliary service by responding to the charging and discharging commands sent by the power grid regulation and control center, and can improve the utilization rate of the centralized energy storage facility.)

1. A centralized cloud energy storage operation decision method capable of participating in power grid auxiliary service is characterized by comprising the following steps:

1) establishing a model predictive control model as follows:

1-1) setting an objective function of the model predictive control model as:

the objective function represents the sum of the operation cost generated by the centralized energy storage facility in the current time period and the operation cost expected to be generated in the set time range; in the formula (I), the compound is shown in the specification,

(·)⁺and (·)^-Defined as taking the positive and negative parts in parentheses, respectively, i.e.:

delta t is the basic time interval of the model predictive control model;

t is the current time period; tau is any time period within 5min immediately after the current time period t; t is_tIs the set of all time periods within 5min immediately after the current time period t;

λ_twhen the centralized energy storage facility acquires electric energy from the power grid for the period t, the cloud energy storage service provider needs to pay the unit price of the electric charge of the power grid;

θ_twhen the centralized energy storage facility feeds back electric energy to the power grid at the time t, the cloud energy storage service provider obtains the unit price of the electric charge from the power grid;

P_t ^C,CUthe centralized energy storage facility is used for providing charging power of the cloud energy storage service for the cloud energy storage users at the t period;

P_t ^D,CUthe centralized energy storage facility is used for providing discharge power of the cloud energy storage service for the cloud energy storage users at the t period;

cloud energy storage user for t periodSummation of discharge power;

P_t ^C,AScharging power used by the centralized energy storage facility for the t period to provide auxiliary service for the power grid;

P_t ^D,ASdischarge power for the t-period centralized energy storage facility for providing auxiliary services to the power grid;

E_tthe electric quantity of the centralized energy storage facility is at the end of the t period;

E_τthe predicted value of the electric quantity of the centralized energy storage facility at the end of the tau time period;

1-2) setting the constraint conditions of the model predictive control model as follows:

1-2-1) Charge and discharge Power constraints

P_t ^C,CU+P_t ^C,AS≤P^Cap

P_t ^D,CU+P_t ^D,AS≤P^Cap

In the formula, P^CapIs the power capacity of the centralized energy storage facility;

1-2-2) minimum electric quantity constraint of centralized energy storage facility

E^Min＝SOC^Min·E^Cap

In the formula, E^MinMinimum amount of electricity for a centralized energy storage facility; SOC^MinA minimum state of charge for the centralized energy storage facility; e^CapEnergy capacity for a centralized energy storage facility;

1-2-3) electric quantity restriction of centralized energy storage facility

E^Min≤E_t,E_τ≤E^Cap

1-2-4) electric quantity constraint of centralized energy storage facility in adjacent time period

Wherein S is the self-discharge rate of the centralized energy storage facility at each time interval delta t, η^CFor the charging efficiency of a centralized energy storage facility, η^DDischarge efficiency for centralized energy storage facilities; e_t-1The actual electric quantity of the centralized energy storage facility obtained by the sensor at the end of the t-1 time period is set as E₀＝SOC₀·E^Cap，SOC₀An initial state of charge for the centralized energy storage facility;

2) at the beginning of the current decision cycle, the cloud energy storage service provider obtains the operating parameters of the current time period t from the power grid control center, and the method comprises the following steps: when the centralized energy storage facility obtains electric energy from the power grid in t period, the unit price lambda of the electric charge which needs to be paid to the power grid by a cloud energy storage service provider_tAnd the unit price theta of the electric charge obtained by the cloud energy storage service provider from the power grid when the centralized energy storage facility feeds back the electric energy to the power grid in the period t_tT-period power grid auxiliary service requires charging power realized by cloud energy storage service provider

3) The cloud energy storage service provider obtains T according to historical data prediction_tThe operation parameters in the time range comprise predicted values of unit prices of electric charges paid to the power grid by a cloud energy storage service provider when the tau-period centralized energy storage facility obtains electric energy from the power grid

4) Solving the following decision variables according to the operation parameters obtained in the step 2) and the step 3) and the model predictive control model established in the step 1): charging power P for providing cloud energy storage service for cloud energy storage users by t-period centralized energy storage facility_t ^C,CUAnd discharge power P_t ^D,CUCharging power P for providing auxiliary service for power grid by centralized energy storage facility in t period_t ^C,ASAnd discharge power P_t ^D,AS；

5) The cloud energy storage service provider sets the charging power of the centralized energy storage facility in the t period to be P according to the decision variable obtained in the step 4)_t ^C,CU+P_t ^C,ASDischarge power of P_t ^D,CU+P_t ^D,AS(ii) a The centralized energy storage facility works according to the set charging power and the set discharging power;

6) the cloud energy storage service provider acquires an actual value of the electric quantity of the centralized energy storage facility at the end of the t period as a parameter of a next decision cycle through a sensor installed on the centralized energy storage facility; returning to the step 2) and starting the next decision period.

Technical Field

The invention relates to a centralized cloud energy storage operation decision method capable of participating in power grid auxiliary service, and belongs to the field of energy storage technology application in power grids.

Background

With the popularization of distributed power generation technology and real-time electricity prices, users increasingly want to independently select energy storage devices and charging and discharging occasions thereof, and reasonable energy storage resource utilization is achieved. The user's investment in using local physical energy storage devices may face excessive unit costs and also require a significant amount of effort to maintain. The method of replacing the user local entity energy storage device with the shared cloud virtual energy storage is a better alternative, such as the existing cloud energy storage device for residential and small users (Liu J, Zhang N, Kang C, et al cloud energy storage for identification and business communities, A business case study [ J ]. Applied energy.2017,188: 226-. The existing cloud energy storage concept is a shared energy storage technology based on a power grid, so that a user can use shared energy storage resources formed by centralized or distributed energy storage facilities at any time, any place and according to needs, and pay service fees according to the use needs. The existing cloud energy storage system mainly comprises 4 parts, namely a cloud energy storage user, a cloud energy storage service provider, a centralized energy storage facility and a power grid. And the cloud energy storage user and the power grid as well as the centralized energy storage facility and the power grid are respectively electrically connected to realize bidirectional energy transmission. Bidirectional information transmission is realized between the cloud energy storage users and the power grid, between the cloud energy storage users and the cloud energy storage service providers, and between the cloud energy storage service providers and the centralized energy storage facilities in a wired or wireless communication mode, and the power grid transmits information to the cloud energy storage service providers in a unidirectional mode.

The cloud energy storage service provider controls the energy storage device to meet the charging and discharging requirements of cloud energy storage users, and meanwhile, energy storage resources are utilized to the maximum extent. Available energy storage resources are shared by a plurality of cloud energy storage users, and are dynamically distributed to corresponding cloud energy storage users according to charging and discharging requirements. The system operation efficiency is improved by optimizing the coordination control of the plan and the energy storage facility. Cloud energy storage changes the original trend by charging and discharging from a distribution feeder. The cloud energy storage user and the energy storage facility are in the same power distribution network. When a cloud energy storage user charges its allocated energy storage resource, the energy storage facility charges by drawing energy into the grid. When a cloud energy storage user discharges his cloud battery to use the stored energy, the energy storage facility releases energy to the grid to compensate for the load of the corresponding user.

The cloud energy storage service provider can utilize complementarity and non-simultaneity of charging and discharging requirements among massive distributed users to realize that the energy capacity and the power capacity of the energy storage facilities built by the cloud energy storage service provider are respectively lower than the energy capacity requirement sum and the power capacity requirement sum of all distributed users in a cloud energy storage system. Energy and information communication technology are increasingly deeply integrated nowadays, so that software and hardware support is provided for building a cloud energy storage system. The current cloud energy storage system does not consider applying a centralized energy storage device corresponding to cloud energy storage to power grid auxiliary service during decision making, only considers how to utilize energy storage resources to serve cloud energy storage users, and does not exert the value of energy storage resources to the maximum extent.

In addition, a Model Predictive Control (MPC) theory (see the following papers: Liu Zhijie, Confucian soldier, Power industry Complex System Model Predictive Control-the present situation and development. Chinese Motor engineering bulletin, 2013,33(05):79-85.) is an optimization Control theory, which was introduced in the last 70 th century, mainly aims at the Control problem with optimization requirements, and has been successfully applied to complex industrial Control. According to the theory, the control strategy is optimized and solved only by adopting the control strategy at the current moment according to the information which can be obtained at the current moment and the information for future prediction, and the real-time control strategy is obtained through rolling optimization. The theory can be used for deciding parameters in a power system scheduling model, such as unit output.

At present, a cloud energy storage system capable of participating in power grid auxiliary service and a related report for making a decision of participating in the power grid auxiliary service by using an MPC method are not introduced in detail.

Disclosure of Invention

The invention aims to overcome the limitation that the existing centralized cloud energy storage system is only used for meeting the charging and discharging requirements of users, and provides a centralized cloud energy storage operation decision method capable of participating in power grid auxiliary services. On the basis, a model prediction control theory is also applied, and a cloud energy storage service provider operation decision model and a method are provided, so that support is provided for the cloud energy storage service provider to actually participate in auxiliary services.

In order to achieve the purpose, the invention adopts the following technical scheme:

the invention provides a centralized cloud energy storage operation decision method capable of participating in power grid auxiliary service, which is characterized by comprising the following steps of:

1) establishing a model predictive control model as follows:

1-1) setting an objective function of the model predictive control model as:

the objective function represents the sum of the operation cost generated by the centralized energy storage facility in the current time period and the operation cost expected to be generated in the set time range; in the formula (I), the compound is shown in the specification,

(·)⁺and (·)^-Defined as taking the positive and negative parts in parentheses, respectively, i.e.:

delta t is the basic time interval of the model predictive control model;

t is the current time period; tau is any time period within 5min immediately after the current time period t; t is_tIs next to the currentA set of all time periods within 5min after time period t;

operating costs for a centralized energy storage facility during time T and its prediction at T_tA total of operating costs incurred over a time horizon;

λ_twhen the centralized energy storage facility acquires electric energy from the power grid for the period t, the cloud energy storage service provider needs to pay the unit price of the electric charge of the power grid;

when the centralized energy storage facility acquires electric energy from the power grid for the period tau, the cloud energy storage service provider needs to pay the predicted price of the electricity fee unit of the power grid;

θ_twhen the centralized energy storage facility feeds back electric energy to the power grid at the time t, the cloud energy storage service provider obtains the unit price of the electric charge from the power grid;

when the tau-period centralized energy storage facility feeds back electric energy to the power grid, the cloud energy storage service provider obtains a predicted value of unit price of the electric charge from the power grid;

P_t ^C,CUthe centralized energy storage facility is used for providing charging power of the cloud energy storage service for the cloud energy storage users at the t period;

the charging power prediction value of the cloud energy storage service is provided for the cloud energy storage user by the tau period centralized energy storage facility;

P_t ^D,CUthe centralized energy storage facility is used for providing discharge power of the cloud energy storage service for the cloud energy storage users at the t period;

is a period of tau concentrationThe energy storage facility is used for providing a predicted value of the discharge power of the cloud energy storage service for the cloud energy storage user;

summing the discharge power of the cloud energy storage users in the t period;

a predicted value of the sum of the discharge power of the cloud energy storage user in the period tau;

the method comprises the steps that a sum of charging power of local distributed energy resources is used for a cloud energy storage user in a t-period;

using a predicted value of the sum of the charging power of the local distributed energy for the tau-period cloud energy storage user;

P_t ^C,AScharging power used by the centralized energy storage facility for the t period to provide auxiliary service for the power grid;

a predicted value of charging power used by the τ period centralized energy storage facility to provide auxiliary services to the grid;

P_t ^D,ASdischarge power for the t-period centralized energy storage facility for providing auxiliary services to the power grid;

a predicted value of discharge power for the τ period centralized energy storage facility to provide auxiliary services to the grid;

auxiliary service requirements for t-period power gridCharging power to be implemented by a cloud energy storage service provider;

a predicted value of charging power, which is realized by a cloud energy storage service provider, is needed for the tau-period power grid auxiliary service;

the discharge power realized by a cloud energy storage service provider is needed for the auxiliary service of the power grid in the period t;

a predicted value of discharge power, which is realized by a cloud energy storage service provider, is needed for the tau-period power grid auxiliary service;

the charging power of the cloud energy storage service provider in the t period can not meet the auxiliary service requirement of the power grid, namely

The unit price of punished electric charge which needs to be paid to the power grid;

charging power for tau period cloud energy storage service providers cannot meet grid auxiliary service requirements, i.e.

The predicted value of the unit price of the punished electric charge to be paid to the power grid;

the discharge power of the cloud energy storage service provider in the t period can not meet the auxiliary service requirement of the power grid, namely

The unit price of punished electric charge which needs to be paid to the power grid;

the discharge power of the cloud energy storage service provider for the period tau cannot meet the auxiliary service requirement of the power grid, namely

The predicted value of the unit price of the punished electric charge to be paid to the power grid;

the charging power of the cloud energy storage service provider in the t period meets the auxiliary service requirement of the power grid, namely

And a unit energy reward obtained from the grid;

charging power for tau period cloud energy storage service providers meets grid auxiliary service requirements, i.e.

And the predicted value of the unit energy reward obtained from the power grid;

the discharge power of the cloud energy storage service provider in the t period meets the auxiliary service requirement of the power grid, namely

And a unit energy reward obtained from the grid;

for tau period cloud energy storage service providersThe discharge power meets the grid auxiliary service requirements, i.e.

And the predicted value of the unit energy reward obtained from the power grid;

E_tthe electric quantity of the centralized energy storage facility is at the end of the t period;

E_τthe predicted value of the electric quantity of the centralized energy storage facility at the end of the tau time period;

1-2) setting the constraint conditions of the model predictive control model as follows:

1-2-1) Charge and discharge Power constraints

P_t ^C,CU+P_t ^C,AS≤P^Cap

P_t ^D,CU+P_t ^D,AS≤P^Cap

In the formula, P^CapIs the power capacity of the centralized energy storage facility;

1-2-2) minimum electric quantity constraint of centralized energy storage facility

E^Min＝SOC^Min·E^Cap

In the formula, E^MinMinimum amount of electricity for a centralized energy storage facility; SOC^MinA minimum state of charge for the centralized energy storage facility; e^CapEnergy capacity for a centralized energy storage facility;

1-2-3) electric quantity restriction of centralized energy storage facility

E^Min≤E_t,E_τ≤E^Cap

1-2-4) electric quantity constraint of centralized energy storage facility in adjacent time period

Wherein S is the self-discharge rate of the centralized energy storage facility at each time interval delta t, η^CFor the charging efficiency of a centralized energy storage facility, η^DDischarge efficiency for centralized energy storage facilities; e_t-1The actual electric quantity of the centralized energy storage facility obtained by the sensor at the end of the t-1 time period is set as E₀＝SOC₀·E^Cap，SOC₀An initial state of charge for the centralized energy storage facility;

2) at the beginning of the current decision cycle, the cloud energy storage service provider obtains the operating parameters of the current time period t from the power grid control center, and the method comprises the following steps: when the centralized energy storage facility obtains electric energy from the power grid in t period, the unit price lambda of the electric charge which needs to be paid to the power grid by a cloud energy storage service provider_tCloud energy storage service provider for feeding back electric energy to power grid by t-period centralized energy storage facilityPrice of electricity rate theta obtained by supplier from electric network_tT-period power grid auxiliary service requires charging power realized by cloud energy storage service providerAnd discharge powerPunishment electricity fee unit price paid to power grid when charging power of t-period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Punishment electricity fee unit price paid to power grid when discharge power of t-period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Unit energy reward obtained from power grid when charging power of t-period cloud energy storage service provider meets auxiliary service requirement of power grid

Unit energy reward obtained from power grid when discharge power of t-period cloud energy storage service provider meets auxiliary service requirement of power grid

The method comprises the steps of collecting and measuring the total discharge power of the cloud energy storage user in a t-period in real time through an application program installed on the portable equipment of the cloud energy storage user

Summation of charging power of cloud energy storage users using local distributed energy resources in t period

3) The cloud energy storage service provider obtains T according to historical data prediction_tOperating parameters over time, including τ time period, centralized energy storage facilityPredicted value of unit price of electric charge paid to power grid by cloud energy storage service provider when power grid obtains electric energy

Predicted value of unit price of electric charge obtained by cloud energy storage service provider from power grid when tau time period centralized energy storage facility feeds back electric energy to power grid

Predicted value of total discharge power of tau-period cloud energy storage user

Predicted value of total charging power of tau-period cloud energy storage users by using local distributed energy

Charging power prediction value realized by cloud energy storage service provider is needed for tau-period power grid auxiliary service

And predicted value of discharge power

Predicted value of punishment electricity fee unit price paid to power grid when charging power of tau period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Predicted value of punishment electricity fee unit price paid to power grid when discharge power of tau period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Predicted value of unit energy reward obtained from power grid when charging power of tau-period cloud energy storage service provider meets auxiliary service requirement of power grid

Cloud storage at period of tauPrediction value of unit energy reward obtained from power grid when discharge power of service provider meets auxiliary service requirement of power grid

4) Solving the following decision variables according to the operation parameters obtained in the step 2) and the step 3) and the model predictive control model established in the step 1): charging power P for providing cloud energy storage service for cloud energy storage users by t-period centralized energy storage facility_t ^C,CUAnd discharge power P_t ^D,CUCharging power P for providing auxiliary service for power grid by centralized energy storage facility in t period_t ^C,ASAnd discharge power P_t ^D,AS；

5) The cloud energy storage service provider sets the charging power of the centralized energy storage facility in the t period to be P according to the decision variable obtained in the step 4)_t ^C,CU+P_t ^C,ASDischarge power of P_t ^D,CU+P_t ^D,AS(ii) a The centralized energy storage facility works according to the set charging power and the set discharging power;

6) the cloud energy storage service provider acquires an actual value of the electric quantity of the centralized energy storage facility at the end of the t period as a parameter of a next decision cycle through a sensor installed on the centralized energy storage facility; returning to the step 2) and starting the next decision period.

The invention has the characteristics and beneficial effects that:

aiming at the problem that the existing cloud energy storage system cannot participate in the auxiliary service of the power grid, the invention improves the decision model of the cloud energy storage service provider, so that the cloud energy storage service provider can participate in the auxiliary service of the power grid, and the participation of the auxiliary service of frequency modulation and peak regulation of the power grid is realized by responding to the charging and discharging commands sent by the power grid regulation and control center. In order to improve the accuracy of the decision, the operation decision of the cloud energy storage service provider adopts the idea of model predictive control, and the current charging and discharging instructions of the centralized energy storage facility are determined according to the existing and predicted information in a rolling mode.

The method can widen the sources of auxiliary service participants of the power grid, provide beneficial support for auxiliary service requirements of frequency modulation, peak shaving and the like of the power grid, and further improve the utilization rate of a centralized energy storage facility in the cloud energy storage system. The cloud energy storage service provider can utilize more predicted parameters, so that the operation decision of meeting the requirements of the cloud energy storage user on charging and discharging and power grid auxiliary service is more scientific and reasonable.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only.

The invention provides a centralized cloud energy storage operation decision method capable of participating in power grid auxiliary service, which comprises the following steps:

1) establishing a model predictive control model as follows:

1-1) setting an objective function of the model predictive control model as:

the objective function represents the sum of the operation cost generated by the centralized energy storage facility in the current time period and the operation cost expected to be generated in the set time range; in the formula (I), the compound is shown in the specification,

(·)⁺and (·)^-Defined as taking the positive and negative parts in parentheses, respectively, i.e.:

Δ t is a basic time interval of the model predictive control model, and is set to 2s in the embodiment;

t is the current time period; tau is any within 5min immediately after the current time period tA period of time; t is_tIs the set of all time periods within 5min immediately after the current time period t;

operating costs for a centralized energy storage facility during time T and its prediction at T_tA total of operating costs incurred over a time horizon;

λ_twhen the centralized energy storage facility acquires electric energy from the power grid for the period t, the cloud energy storage service provider needs to pay the unit price of the electric charge of the power grid;

when the centralized energy storage facility acquires electric energy from the power grid for the period tau, the cloud energy storage service provider needs to pay the predicted price of the electricity fee unit of the power grid;

θ_twhen the centralized energy storage facility feeds back electric energy to the power grid at the time t, the cloud energy storage service provider obtains the unit price of the electric charge from the power grid;

when the tau-period centralized energy storage facility feeds back electric energy to the power grid, the cloud energy storage service provider obtains a predicted value of unit price of the electric charge from the power grid;

the centralized energy storage facility is used for providing charging power of the cloud energy storage service for the cloud energy storage users at the t period;

the charging power prediction value of the cloud energy storage service is provided for the cloud energy storage user by the tau period centralized energy storage facility;

for centralized energy-storage facilities during t time periodProviding the discharging power of the cloud energy storage service for the cloud energy storage user;

the discharge power prediction value of the cloud energy storage service is provided for the cloud energy storage user by the tau period centralized energy storage facility;

summing the discharge power of the cloud energy storage users in the t period;

a predicted value of the sum of the discharge power of the cloud energy storage user in the period tau;

the method comprises the steps that a sum of charging power of local distributed energy resources is used for a cloud energy storage user in a t-period;

using a predicted value of the sum of the charging power of the local distributed energy for the tau-period cloud energy storage user;

charging power used by the centralized energy storage facility for the t period to provide auxiliary service for the power grid;

a predicted value of charging power used by the τ period centralized energy storage facility to provide auxiliary services to the grid;

discharge power for the t-period centralized energy storage facility for providing auxiliary services to the power grid;

a predicted value of discharge power for the τ period centralized energy storage facility to provide auxiliary services to the grid;

charging power realized by a cloud energy storage service provider is needed for the auxiliary service of the power grid in the period t;

a predicted value of charging power, which is realized by a cloud energy storage service provider, is needed for the tau-period power grid auxiliary service;

the discharge power realized by a cloud energy storage service provider is needed for the auxiliary service of the power grid in the period t;

a predicted value of discharge power, which is realized by a cloud energy storage service provider, is needed for the tau-period power grid auxiliary service;

the charging power of the cloud energy storage service provider in the t period can not meet the auxiliary service requirement of the power grid, namely

The unit price of punished electric charge which needs to be paid to the power grid;

charging power for tau period cloud energy storage service providers cannot meet grid auxiliary service requirements, i.e.

The predicted value of the unit price of the punished electric charge to be paid to the power grid;

the discharge power of the cloud energy storage service provider in the t period can not meet the auxiliary service requirement of the power grid, namely

The unit price of punished electric charge which needs to be paid to the power grid;

the discharge power of the cloud energy storage service provider for the period tau cannot meet the auxiliary service requirement of the power grid, namely

The predicted value of the unit price of the punished electric charge to be paid to the power grid;

the charging power of the cloud energy storage service provider in the t period meets the auxiliary service requirement of the power grid, namely

And a unit energy reward obtained from the grid;

charging power for tau period cloud energy storage service providers meets grid auxiliary service requirements, i.e.

And the predicted value of the unit energy reward obtained from the power grid;

is t period cloudThe discharge power of the energy storage service provider meets the grid auxiliary service requirements, i.e.

And a unit energy reward obtained from the grid;

meet grid auxiliary service requirements for discharge power of tau period cloud energy storage service providers, i.e.

And the predicted value of the unit energy reward obtained from the power grid;

E_tthe electric quantity of the centralized energy storage facility is at the end of the t period;

E_τthe predicted value of the electric quantity of the centralized energy storage facility at the end of the tau time period;

1-2) setting the constraint conditions of the model predictive control model as follows:

1-2-1) Charge and discharge Power constraints

P_t ^C,CU+P_t ^C,AS≤P^Cap

P_t ^D,CU+P_t ^D,AS≤P^Cap

In the formula, P^CapIs the power capacity of the centralized energy storage facility;

1-2-2) minimum electric quantity constraint of centralized energy storage facility

E^Min＝SOC^Min·E^Cap

In the formula, E^MinMinimum amount of electricity for a centralized energy storage facility; SOC^MinA minimum state of charge for the centralized energy storage facility; e^CapEnergy capacity for a centralized energy storage facility;

1-2-3) electric quantity restriction of centralized energy storage facility

E^Min≤E_t,E_τ≤E^Cap

1-2-4) electric quantity constraint of centralized energy storage facility in adjacent time period

Wherein S is the self-discharge rate of the centralized energy storage facility at each time interval delta t, η^CFor the charging efficiency of a centralized energy storage facility, η^DThe discharging efficiency of the centralized energy storage facility is set according to the model of the centralized energy storage facility and is a known value; e_t-1The actual electric quantity of the centralized energy storage facility acquired by the sensor at the end of the t-1 time period is startedThe electric quantity of the centralized energy storage facility is E₀＝SOC₀·E^Cap，SOC₀An initial state of charge for the centralized energy storage facility;

2) at the beginning of the current decision cycle, the cloud energy storage service provider obtains the operating parameters of the current time period t from the power grid control center, and the method comprises the following steps: when the centralized energy storage facility obtains electric energy from the power grid in t period, the unit price lambda of the electric charge which needs to be paid to the power grid by a cloud energy storage service provider_tAnd the unit price theta of the electric charge obtained by the cloud energy storage service provider from the power grid when the centralized energy storage facility feeds back the electric energy to the power grid in the period t_tT-period power grid auxiliary service requires charging power realized by cloud energy storage service provider

And discharge power

Punishment electricity fee unit price paid to power grid when charging power of t-period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Punishment electricity fee unit price paid to power grid when discharge power of t-period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Unit energy reward obtained from power grid when charging power of t-period cloud energy storage service provider meets auxiliary service requirement of power grid

Unit energy reward obtained from power grid when discharge power of t-period cloud energy storage service provider meets auxiliary service requirement of power grid

The total discharge power of the cloud energy storage user in the t period is obtained through real-time collection and measurement of an application program installed on the portable equipment of the cloud energy storage userCombination of Chinese herbs

Summation of charging power of cloud energy storage users using local distributed energy resources in t period

3) The cloud energy storage service provider obtains T according to historical data prediction_tThe operation parameters in the time range comprise predicted values of unit prices of electric charges paid to the power grid by the cloud energy storage service provider when the tau-period centralized energy storage facility obtains electric energy from the power grid

Predicted value of unit price of electric charge obtained by cloud energy storage service provider from power grid when tau time period centralized energy storage facility feeds back electric energy to power grid

Predicted value of total discharge power of tau-period cloud energy storage userPredicted value of total charging power of tau-period cloud energy storage users by using local distributed energy

Charging power prediction value realized by cloud energy storage service provider is needed for tau-period power grid auxiliary service

And predicted value of discharge power

Predicted value of punishment electricity fee unit price paid to power grid when charging power of tau period cloud energy storage service provider cannot meet auxiliary service requirement of power grid

Tau-period cloud energy storage service provisioningPredicted value of punishment electricity fee unit price paid to power grid when discharge power of business cannot meet auxiliary service requirement of power grid

Predicted value of unit energy reward obtained from power grid when charging power of tau-period cloud energy storage service provider meets auxiliary service requirement of power grid

Predicted value of unit energy reward obtained from power grid when discharge power of tau-period cloud energy storage service provider meets auxiliary service requirement of power grid

4) Solving the following decision variables through a linear programming solver according to the operation parameters obtained in the step 2) and the step 3) and the model predictive control model established in the step 1): charging power P for providing cloud energy storage service for cloud energy storage users by t-period centralized energy storage facility_t ^C,CUAnd discharge power P_t ^D,CUCharging power P for providing auxiliary service for power grid by centralized energy storage facility in t period_t ^C,ASAnd discharge power P_t ^D,ASElectric quantity E of centralized energy storage facility at end of time period t_tThe calculated value of (which is an intermediate variable of the model);

5) the cloud energy storage service provider sets the charging power of the centralized energy storage facility in the t period to be P according to the decision variable obtained in the step 4)_t ^C,CU+P_t ^C,ASDischarge power of P_t ^D,CU+P_t ^D,AS(ii) a The centralized energy storage facility works according to the set charging power and the set discharging power;

6) the cloud energy storage service provider acquires an actual value of the electric quantity of the centralized energy storage facility at the end of the t period as a parameter of a next decision cycle through a sensor installed on the centralized energy storage facility; returning to the step 2) to start the decision of the next period.

The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by the present invention in the specification, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.