Research On Dual-Carbon Services Based On Electric Vehicles And Pumped Energy Storage To Stabilize Power Fluctuations.

Based on the research of electric vehicle energy storage stabilization, stochastic, adjustable, robust optimization, wind-solar complementary intelligent water pump system service double carbon,Which aims at: (1) In order to promote the consumption of wind power and photovoltaics in the grid, and reduce the pressure on the load of the distribution network; （ 2) Consider wind power and photovoltaic output fluctuations and electric vehicle cluster energy storage systems, and use multiple electric vehicle clusters to coordinate and smooth tie-line power fluctuations. The model includes: (1) a load monitoring terminal; (2) a server for storing, processing and mapping all collected electrical energy data; (3) a set of user-centric electrical energy management visualization and prediction services. (4) A set of photovoltaic water pumps, pumped energy storage systems and electric vehicles for supplying water to impoverished areas . Experimental data and practical applications show that because the wind and wind have a certain degree of complementarity, but are greatly affected by the climate, pumped energy storage and electric vehicles can reduce the volatility of the system. The research results show that photovoltaic and wind power have great volatility, and the current investment and operating costs of energy storage systems are relatively high. Large-scale deployment of energy storage systems will seriously affect the economics of and solves the problem of safe drinking water for 11,590 people and 3140 large livestock in Jiangyi


Introduction
As we all know, energy transformation is one of the most powerful measures to solve carbon emissions, Because a large amount of carbon dioxide emissions can lead to the greenhouse effect. Despite the increasing awareness of citizens and governments,Policymakers also recognize the importance of reducing carbon dioxide emissions, At present, China's greenhouse gas emissions are about 14 billion tons, and energy related carbon dioxide emissions account for 73% of all greenhouse gas emissions. It still fails to meet the requirements of China's carbon peak before 2030 and carbon neutralization before 2060(outline of China's 14th Five -year plan). Therefore, It is very important for us to actively transform energy's type to strengthen carbon emission reduction. To devise such strategies, We need to improve the effectiveness of the energy management system to reduce energy consumption and improve energy efficiency continuously. We will continue to reduce energy consumption and carbon dioxide emissions by building a green energy management system, promoting renewable energy to replace traditional energy, and developing technology and energy conservation management. that is, We will conduct on-the-spot investigation on the current energy structure and energy management mode. In 2020, the number of electric vehicles in my country will reach 5×10^6, and large-scale electric vehicles will be connected to the network, and the impact capacity will be very considerable. In practical applications, the forecasts of wind power and photovoltaics can be updated at any time in the actual situation. Nevertheless, in order to obtain high-quality prediction data, a high-precision prediction algorithm is required. According to the Copula theory, the reliability and stability of the system are guaranteed(Sklar，1959).
As part of the National Natural Science Foundation of China, the main contribution of the current research is to solve the problem of drinking water and energy waste in impoverished areas and improve the utilization of idle land resources in impoverished areas. Improved and optimized the robustness of wind power and photovoltaics. Increased the economic output of crops in impoverished areas. Reduce the large amount of carbon dioxide emissions caused by thermal power units. By collecting the local weather forecast data, combined with the historical power generation and power load data, the prediction optimization is carried out. Ensure that the energy utilization of the system is maximized and the robustness of the system is guaranteed. The core of the research is to enhance the safety and reliability of the power grid and improve the utilization of wind and light energy, However, different from most studies now, our research is mainly aimed at poor and remote areas. Our system needs to be able to supply power to local residents in extreme weather conditions. Wind power grid integration increases the spinning reserve capacity to compensate for the uncertainty of wind power output, so this paper introduces spinning reserve penalty costs. The extreme penetration of wind power often causes abandonment of wind farms, resulting in waste of resources and low wind power utilization. Therefore, this paper introduces the cost of abandonment penalty.
Although the idea of wind-solar hybridization was developed by Xinjiang TBEA New Energy Company to build my country's first large-scale wind-solar hybrid power station of 100 megawatts(2013), But these early solutions did not involve energy management. Our research also included electric vehicles and photovoltaic water pumps. Its mission is to collect historical weather, electricity energy data, People's Daily habits and typical load, to provide people with a set of energy efficiency maximization, revenue maximization, stable and reliable quality electricity service.Our research aims to improve local residents' fossil energy easily depleted and the resulting air pollution and greenhouse effect damage our living environment. Therefore, the research on the energy management system of the household energy management system with random adjustable robust optimization wind-solar complementary intelligent water pump helps people in poverty-stricken areas to change their behaviors and arrange daily electricity consumption according to the prompts of the electric energy data management system, which not only greatly improves our lives The environment, income from drinking water, agriculture, and animal husbandry for local residents have also been significantly improved and increased. In addition, the system also allows residents to determine the online time for the generated energy based on the peak, flat, and valley electricity prices, so as to maximize the benefits for local residents.
How to improve the ecological environment, quality of life, drinking water in povertystricken areas, and increase energy efficiency are the main concerns of this research.
In summary, the system we studied provides a novel and practical solution for energy management and drinking water in poor areas, reducing the emissions of carbon dioxide and toxic gases produced by thermal power plants and fossil fuels.
Together with a set of practical photovoltaic water pumping system, it can solve the water problem of people, livestock and crops in poor areas. The chapter structure of this article is arranged as follows. In the second section, the stochastic adjustable robust optimization wind-solar complementary intelligent water pump family energy management system is described. Section 3 presents the results and verifies the system in a set of field experiments. Finally, the fourth part summarizes the conclusions and proposes future work directions.

Proposed system
2.1. System architecture The energy management system proposed in this paper is a hierarchical, distributed intelligent system, whose purpose is to make a power generation plan, electricity use plan, water use plan, and energy storage plan in advance based on local weather forecasts to optimize energy utilization. To provide citizens in poverty-stricken areas with intuitive electricity consumption planning, integrate these data together, and cultivate a more scientific way of electricity consumption. In order to achieve these goals, the system is divided into three layers, as shown in Figure 1: The energy management system is responsible for collecting all electric energy data and local weather data, predicting and using them, , make a reasonable power consumption plan for local residents. The wind solar complementary robust optimal scheduling model based on Copula theory is adopted to ensure the robustness of the system. The problem of water for people, livestock and crops in poor areas has been solved. Make an accurate prediction and reasonable power consumption and generation plan by using historical power consumption and generation data, weather forecast, water consumption and electric vehicle travel. The energy storage system can control the active power output by the wind power generation. The energy storage system can not only be used for power peak shaving, smooth the power output of the wind farm, and make the wind unit operate as a dispatch unit unit, but also has the ability to provide frequency control to the power system. Auxiliary service functions such as fast power response, taking full consideration of the mobile energy storage characteristics of electric vehicles, using electric vehicle internal battery supercapacitors, combined with pumped energy storage technology, can not only provide high-quality electrical energy to the grid, but also increase wind power and photovoltaics The operating efficiency of the wind power and photovoltaic power in the energy market will be improved.
Photovoltaic power generation and wind power generation have natural complementarity and show weak nonlinear correlation. It is very difficult to determine the relationship between them by using the traditional probability theory. The introduction of Copula theory provides a new method to solve this problem.In practice, the output of wind farms and photovoltaic power stations in the same region are complementary. Therefore, the characteristic Frank copula function of negative correlation structure is selected as the connection function of the joint probability distribution of wind farm and photovoltaic power station. The distribution function and density function of Frank copula function are: In the formula, uv 、 the output of wind farm and photovoltaic power station is respectively represented,  which is a relevant parameter. At that time 00   ， , u 、v it represents the output and shows a positive correlation; At that time 0   , u 、 v it means output and tends to be independent; At that time 0   , u 、 v it means output and negative correlation.

Economic Cost of Wind Farm
As a representative of new energy, wind power has the characteristics of no pollution and no coal consumption, but the intermittent nature of wind farms will seriously affect the safety and reliability of the power grid. The grid-connected wind power increases the spinning reserve capacity to make up for the uncertainty of wind power output [8]，Therefore, this article introduces the penalty cost of spinning reserve。 The extreme penetration of wind power often causes abandonment of wind farms, resulting in waste of resources and low wind power utilization. Therefore, this paper introduces the cost of abandonment penalty. Most of the costs of wind farms are in the Where j Respectively n Number of wind farms， . On the basis of considering environmental pollution and fuel loss, combined with the formula (5)～(11)The objective function of minimizing the total power generation cost per unit cycle is proposed.
Where T Indicates the number of cycles per unit， I、 K Respectively indicate the number of thermal power plants and photovoltaic power plants in the system within a period. The family energy management system is shown in Figure 2. The output combination of wind farm and photovoltaic power station with windsolar complementary independent operation configuration takes advantage of the natural characteristics of wind-solar complementary to a certain extent, and the fluctuations of the power into the network will be improved when the grid is connected. The reliability and security of the grid should be ensured, and the fluctuations of the power into the network should be small [9]. In this paper, the wind-solar complementarity characteristics are fully considered, and the reliability optimization strategy of wind-solar complementarity is adopted to configure the output power and rotary reserve capacity of photovoltaic power stations and wind farms under the condition that the economic cost of the objective function is small.
Wind power generation and photovoltaic power generation are greatly affected by the environment. In order to measure the correlation degree of wind-solar complementarity, the correlation change rate of wind-solar complementarity is defined In this paper, the credibility of wind-solar complementarity is defined by fuzzy opportunity constraint, and the credibility measure of wind-solar complementarity can be solved by possibility measure. For the possibility space, the credibility of the event is expressed as [10][11][12]

Show event A Opposing events。
In order to define the power fluctuation of the wind-solar hybrid grid-connected system, this paper introduces the credibility into the wind-solar hybrid system and defines the confidence level  ，Expressed as： Where  Indicates the minimum acceptable change rate of wind output。 According to formula (22), Figure 1 can be obtained，It can be seen from Figure   1: With the Kendall rank correlation coefficient  With the increase of the negative correlation of the wind and solar hybrid system, the confidence level of the wind and solar hybrid system continues to increase; as the number of power stations M increases, the confidence level of the wind and solar hybrid system also shows a weak increase. coefficient,According to the definition of the robust optimal scheduling model, the expression of the wind-solar complementary robust optimal scheduling model in this paper .It can be seen that the robust optimal scheduling model in this paper is a classic nonlinear quadratic programming problem, and this paper uses optimization dual internal point generation to solve it.

2.2.3Analysis of calculation examples
In order to verify the application of the system in actual scenarios, a simplified power system of 2 wind farms and 2 photovoltaic power plants was used as an example to conduct optimization dispatch analysis and confidence level analysis of wind-solar hybrid power generation system. Use 80MW photovoltaic power plant and 80 MW wind farm. Considering the actual local situation, this paper chooses the study period from 8:00 to 18:00, and the power output forecast is shown in Table 1. Considering the actual local situation, this paper chooses the study period from 8:00 to 18:00, and the power output forecast is shown in Table 1. The robust optimization theory is used to deal with the uncertain variables in the wind-solar hybrid system, which enhances the robustness of the system. It can be seen that with the improvement of confidence level, the power output of wind solar complementary system is more stable. This is because the greater the negative correlation of wind solar complementary system, the more significant the output power of wind power generation and photovoltaic power generation has the characteristics of mutual compensation. Robust optimal scheduling also takes into account the randomness and intermittence of photovoltaic output and wind farm output, making the scheduling results more robust. The effect diagram of different confidence intervals is shown in Figure 4. Next, we combine the optimal dispatch of rural household electricity load to study.
According to the operating characteristics of the household electricity load and its controllability for the household energy management system, the article divides the household electricity load into the following four categories: Basic load , Unschedulable flexible load, schedulable uninterruptible load, temperature control load.
The household energy management system needs to consider the uncertainty of users' electricity consumption behavior in the decision-making process. The model is shown in formula (9): (10) Where Pf(t) for t Unschedulable flexible load power consumption in a time period；PfThe power consumed when the load is running；xf(t) for t The operating status of the load during the time period；tf,start and Lf It is the initial running time and rated running time of a task for this load.
Washing machines, dryers, dishwashers, etc. are schedulable and uninterruptible loads with fixed working cycles and a certain degree of flexibility in running time. They can be scheduled by the home energy management system. After startup, they must run continuously until the task is completed. The model is not schedulable. The form of the flexible load model is the same. Scheduling this type of load will not significantly restrict users' daily life behaviors.
Generally speaking, as the distance from the operating point increases, the prediction accuracy of photovoltaic power generation output gradually decreases. The short-term forecast of photovoltaic power output (0~72 h) has an error of 5%~25%, mostly concentrated in 10%~20%, while the error of ultra-short-term forecast (0~4 h) can be less than 1% [19][20][21]. Unlike wind power, the photovoltaic power generation system only generates electricity during the day and the output power at night is 0.
Therefore, when HEMS formulated the scheduling strategy for the second day the night before, the forecast of the output of the distributed home grid-connected photovoltaic system on the second day was obtained. The value has a large uncertainty, and the  The system scheduling period in the article is T=24 h, which is equally divided into N=96 time periods, and each time period is Δt=15 min. In the example system, the distributed power supply includes a distributed photovoltaic power generation system with a total capacity of 2.5 kW and an energy storage system with a total capacity of 10 kW·h. The remaining parameters of the energy storage system are shown in Table 1 The predicted expected value and fluctuation range of photovoltaic power generation output on the next day and outdoor temperature are shown in Figure 1 and In this paper, the CPLEX solver is called to solve the MILP problem through the YALMIP toolbox in MATLAB.
If an adjustable robust optimization method is used to formulate a scheduling strategy for the entire scheduling cycle (ie 0-24h), the total operating cost of the system Improve the economic efficiency of household electricity.

2.2.3Pumped energy storage unit model and constraints
The power generation of a pumped energy storage power station in operation is not only related to the number of generating units and each output, but also needs to be less than the reservoir energy storage (in MW·h) that the power station can provide, as shown in equation (11). The pumping mode unit runs at rated power PpN, and the total pumping power needs to be less than the wind power during this period and the energy storage corresponding to the remaining water storage space of the pumped energy storage power station, as shown in equation (12). The unit cannot be in the state of pumping water and generating electricity at the same time, and the design constraints are shown in equation (13). In addition, the total number of pumped generator sets N remains unchanged, and the number of start and stop units can be calculated according to the number of units N0t in shutdown conditions at each time period, as shown in equations (14), (15) and (16).
= 0 = + + 0 = max ( −1 0 − 0 , 0) = max ( 0 − −1 0 , 0) In the formula, and are the power generation and pumping power of the pumped-storage unit in period t, respectively; is the power generated by the wind turbine in period t, And are the minimum and maximum power generation of a single unit, respectively, in MW; and are the number of units in power generation and pumping conditions during the t period, respectively; is the energy storage of the upper reservoir at the beginning of the t period, MW·h; ηp and ηg are the pumping and power generation efficiency of the unit respectively; , Respectively the number of units starting and stopping during t period; and are the minimum and maximum energy storage available in the pumped storage power station reservoir, MW·h. With the goal of minimizing the cost of the combined operation of wind power and pumped energy storage, considering the start-up and shutdown costs of the generator set in the pumped energy storage power station, the objective function is: In the formula, and are the number of units starting and stopping; f(i) is the fuel cost of a conventional unit. The constraints are as follows: System power balance constraints.
In the formula, is the total number of wind farms; is the total output of all units in the wind farm k during period t; is the load value during period t; is the number of pumped energy storage units; is the total number of pumped energy storage units j for all units during period t The total output; Ni is the total number of thermal power units; is the output power of the thermal power unit i in the period t. This article does not consider the network loss and network restrictions, and believes that the system is capable of accepting a certain percentage of wind power into the grid in full. System standby constraints.
In the formula, , i is the maximum output power of thermal power unit i; , j is the maximum output power of hydropower station j; kd and kw are the coincidence fluctuation coefficient and the wind power fluctuation coefficient, respectively, taking 10% and 15%. The system requires the reserve capacity to meet the random fluctuations of wind power and load.

Electric vehicle cluster energy storage unit model and constraints
According to the owner's travel and electric vehicle SOC, three control modes are formulated: travel mode, regulation mode, and standby mode.
(1) Travel mode: electric vehicles are charged when the state of charge is lower than 90% SOC, and participate in grid regulation or wait when the state of charge is higher than 90% SOC; (2) Regulation mode: the electric vehicle is charged when the state of charge is lower than the preset SOC, and participates in grid regulation or waiting when the state of charge is higher than the preset SOC, as shown in Figure 2: Where , is the chargeable storage capacity of electric vehicles, , is the dischargeable energy storage capacity of electric vehicles, and is the total capacity of electric vehicles. Under constraints: If ( )= ( ), then: If ( )< ( ), then: Determine the target change value of the total output of the electric vehicle cluster Therefore, the total output power of electric vehicle cluster energy storage is: = , cluster energy storage system The energy management coordination control strategy is mainly divided into three modes to allocate energy, Large-scale disorderly electric vehicles entering the grid not only did not play a good role in shaving the peak and filling valleys of the original load, but aggravated the fluctuation of the load to a certain extent. After the electric vehicles entered the grid, the overall electricity load of the urban distribution network was increased. It poses higher challenges to the reliability, economy, and safety of the distribution network.

Photovoltaic water pump
The basic structure of the photovoltaic water pump system. The photovoltaic water pump system is a system that integrates "light, machine, electricity, materials" and other multidisciplinary high-tech systems. It is not only applied to traditional technologies such as photovoltaic materials, solar energy harvesting, power electronic conversion, and motor drive control. The results will be applied to super management systems such as the Internet of Things and cloud platforms in the near future. Photovoltaic water pump systems have high practical value in domestic water, seawater desalination, desert management, agricultural irrigation, grassland animal husbandry, scenic fountains, sewage treatment, etc. The core technology of photovoltaic water pump system lies in two parts: AC and DC power conversion and water pump motor drive control.
According to the working characteristics of the photovoltaic water pump, by adjusting the rotation speed of the load of the water pump, the working point of the photovoltaic array can be controlled, so that the system can output the maximum power stably. For an asynchronous motor, the rotation speed can be adjusted by changing the voltage and frequency. From the above-mentioned T-type equivalent circuit of the asynchronous motor, the voltage of each phase of the stator of the three-phase asynchronous motor can be obtained. As long as U1 and f1 are controlled, the magnetic flux can be controlled. Three-phase asynchronous motor variable voltage frequency conversion speed regulation has the following characteristics: (1) Speed regulation from the base frequency downwards, keeping the magnetic flux constant, which is a constant torque speed regulation method; from the fundamental frequency upwards, the magnetic flux and The frequency decreases in inverse proportion, which is approximately a constant power speed regulation mode; (2) The motor frequency f can be continuously adjusted. The three-phase asynchronous motor is a non-linear, multivariable, strong coupling, multi-parameter system, which is difficult to accurately control by simple external control signals.
When the temperature is constant, the maximum output power of the photovoltaic array increases with the increase of the light intensity. Since the power of the water pump in the photovoltaic water pump system is approximately proportional to the cube of the speed, and the speed is proportional to the frequency, adjusting the output frequency of the inverter power supply is equivalent to adjusting the power of the load motor. The controller adopts an optimized sliding mode control strategy, a fixed duty cycle control in the steady state of MPPT, and an optimized sliding mode control in the tracking state. This control strategy can effectively reduce power chattering. The power chattering curve of the optimized sliding mode control method is smoother than that in the literature, and the chattering is smaller. Through the simulation data, we can know that the optimized sliding mode control MPPT technology can quickly track the maximum power point. When the external light intensity changes suddenly, it not only has a faster dynamic response speed, but also has a smaller chattering.
After the bus voltage setting value is compared with the DC voltage measured by the photovoltaic array feedback, the deviation value is passed through the PI regulator to obtain the frequency control signal. The frequency signal is converted into the motor stator reference phase voltage through the voltage-frequency ratio curve, and then pulses are generated by the SVPWM generator Signal to control the duty cycle D of the power switch tube of the IPM module to adjust the output voltage and frequency of the inverter. The algorithm mainly includes the following steps: Step1. Determine the sector where the composite vector is located; Step2. Calculate the action time of two adjacent vectors in real time; Step3. Determine the conduction time of each bridge arm; Step4. Obtain the PWM duty cycle D of each phase; Step5. Update the corresponding register value. After the bus voltage setting value is compared with the DC voltage measured by the photovoltaic array feedback, the deviation value is passed through the PI regulator to obtain the frequency control signal. The frequency signal is converted into the motor stator reference phase voltage through the voltage-frequency ratio curve, and then pulses are generated by the SVPWM generator Signal to control the duty cycle D of the power switch tube of the IPM module to adjust the output voltage and frequency of the inverter. The algorithm mainly includes the following steps: Step1. Determine the sector where the composite vector is located; Step2. Calculate the action time of two adjacent vectors in real time; Step3. Determine the conduction time of each bridge arm; Step4. Obtain the PWM duty cycle D of each phase; Step5. Update the corresponding register value.
The commonly used water pumps in photovoltaic water pumping systems mainly include positive displacement pumps and centrifugal pumps. The working principle of positive displacement pumps is to pump water through periodic changes in the internal volume of the pump; centrifugal pumps use the centrifugal force generated by the high-  accounted for 51.7% of the world's total and CO2 emissions accounted for 28.8% of the world's total. The coal-based energy structure is facing domestic requirements to improve the environment, International pressure to reduce CO2 emissions. In addition, my country has a high degree of dependence on foreign oil and natural gas, and energy security is facing potential threats. Therefore, promoting my country's energy transition and optimizing the energy structure are issues that urgently need to be resolved in the sustainable and coordinated development of energy, economy, and environment. The internal mechanism of the energy revolution promoting the rise of high quality in Central China is shown in Figure 10. Form a multi-energy system such as wind-solar complementation, water-light complementation, etc. In regional energy cooperation, "West-East Gas Transmission", "West-East Electricity Transmission", "North Coal-South Transportation", UHV smart grids, etc., have provided energy structure transformation in the central region. Facilitating conditions; accordingly, a scenario where the energy revolution promotes the transformation of the energy structure in the central region has been constructed (see Table 2).
Table2Energy structure scenarios of the five central provinces Take the scenario of high economic growth as an example (see Figure 2).
By 2035, the rising energy demand in the central region will show an increasing trend without an inflection point, and the energy demand will be about 8.45×10 8 ~1.0×10 9 tce. For example, if the energy revolution is adopted to promote industrial structure optimization and energy efficiency improvement (SE11 path), the energy demand in 2035 will be approximately 9.12×10 8 tce; if the energy revolution cannot promote industrial structure optimization and energy efficiency improvement, the urbanization process will accelerate (SE14 path) ), the energy demand is about 1.0×10 9 tce; if you choose one of the two to promote the upgrading of industrial structure and improve energy efficiency, it is the SE12 or SE13 route, but the energy demand of the SE13 route is 4.55×10 7 lower than that of the SE12 route tce, this shows that the improvement effect of energy technology efficiency is higher than that of industrial structure optimization.  (3) Promote the reform of the energy system and build a multi-competitive market system，The development and growth of new energy is inseparable from market breakthroughs. my country's current "coal-electricity joint operation" and "coalelectricity integration" operating system has actually formed the monopoly of coal power on the grid, and new energy sources such as wind and photovoltaics are basically available in price. Conditions to compete with traditional thermal power. It is recommended to make use of the decentralized characteristics of new energy, combine with the construction of "beautiful villages" and "safe communities", adopt a development path from rural to urban, from life to production, design a competitive market, and better play the decisive role of the market in resource allocation . In view of the regional differences in the distribution of wind and solar energy, it is recommended that the provinces in the central region establish a consultation mechanism, break administrative divisions, and fully strengthen regional cooperation in the use of new energy; promote energy system reform, break institutional constraints and break regional gaps, and advocate renewable energy Prioritize the development and utilization of the environment, and better implement the concept of ecological priority development.