Research on the capacity allocation optimization of micro-grid considering wind-PV-ES

To achieve the goal of “2030 carbon peak and 2060 carbon neutralization” and optimize the form of multi-energy utilization in the industrial park, it is very important to fully exploit distributed clean energy and micro-grid energy system in the park. In view of the economy of micro-grid investment, the capacity proportion of wind, solar and energy storage is the key point in the planning and design stage. A capacity allocation optimization strategy of micro-grid considering wind/solar/thermal/energy storage is proposed. The model takes the minimum total cost of the system as the objective function. As the characteristics of load in the industrial park has a poor adjust ability, the energy storage is added to the integrated energy allocation system as a flexible adjustable power supply. The energy capacity allocation of micro-grid in a cement plant park in China is analysed and calculated in this paper. The results show that after the completion of wind power, photovoltaic and thermal power, the annual power generation of the project will increase by about 105540 MWh, save about 31000 tons of standard coal per year, and reduce about 84000 tons of carbon dioxide emissions. As the cost of renewable energy will be further reduced under the sustainable development of clean energy and the trend of future technology development, establishing a clean energy micro-grid in the industrial park can bring considerable economic benefits. This study can provide a reference for the capacity allocation of the energy system in the industrial park at the planning stage.


Introduction
The gradual depletion of fossil energy has led to the intensification of global energy shortage.The issue of carbon emissions from fossil fuels has also received increasing attention.Industrial production activities in the industrial park are one of the sources of carbon emissions.Building a comprehensive energy system for the industrial park, integrating clean and pollution-free renewable energy such as scenery for power supply, reducing the cost of power grid purchase, and reducing carbon emissions are very promising development directions.
In view of the economic optimization of the integrated energy system, the current research has done relatively comprehensive research on the energy supply side and the demand side respectively.The characteristics of the energy supply and storage equipment and their impact on the economic benefits are considered in Literature [1].The environmental benefits of the renewable energy power grid connection and the system operation and maintenance costs are considered in Literature [2].To achieve the goal of efficient use of energy and improving the overall benefits of both supply and demand, it has been analyzed through the time scale translation of the scheduled load in Literatures [3][4][5].The carbon trading mechanism and the EV charging load adjustment ratio are considered in Literature [6] for the optimal scheduling of energy systems.However, there are still few studies on integrated energy system aiming at the characteristics of industrial parks, especially for the planning and design stage.The traditional planning and design method mostly consider the safety and reliability, so the design margin of power supply and power grid is relatively large.The biggest difference between the industrial park and the general scenario is their load characteristics.Most of the loads are used for industrial production which are non-adjustable loads with low volatility and strong regularity [7][8].There are few flexible loads that can be flexibly adjusted.Therefore, the energy system of industrial park is not applicable to the model proposed for traditional energy systems.With the promotion and application of micro-grid in the power system, the traditional planning and design method is not conducive to the promotion of distributed power generation.

MEIE-2023
This paper takes the energy system of industrial parks as the background to build an integrated energy system considering wind/solar/thermal/energy storage and optimizes the capacity allocation of the system.The energy storage can be used as the raw material of the fuel cell to compensate for part of the load shortage when the power is insufficient and can be realized in the period of excess power and valley power.The energy capacity allocation of micro-grid in a cement plant park in China is analyzed and calculated in this paper.The results show that the cost of renewable energy will be further reduced under the sustainable development of clean energy and the trend of future technology development.Establishing a clean energy micro-grid in the industrial park can bring considerable economic benefits.This study can provide a reference for the capacity allocation of the energy system in the industrial park at the planning stage.

Capacity allocation optimization model of micro-grid considering wind/PV/ES
The integrated energy system constructed in this paper includes thermal power, wind power, photovoltaic (PV), energy storage (ES) and industrial load.When the system power is insufficient or there is surplus power generated, the system can interact with the outside power grid.
The capacity allocation optimization model of integrated energy system includes objective function and constraints.

Objection function
The goal is to optimize the economic benefits of the park: Among them, wind a is annual operating cost of unit wind power.wind b is the fixed unit investment.
  t wind P is the wind power at t time.N w ind P is the rated output power.

Energy balance constraints.
The energy balance of the park can be expressed as follows: Among them, ci v is the cut-in wind speed.x v is the wind speed at the inflection point.n v is the rated wind speed.co v is the cut-out wind speed.N w ind P is the rated output power.2) Mathematical model of PV output [8] The actual PV power   t solar P can be described by Formula (5).
Among them, Nsolar P is the rated power of the PV in the standard environment.

 
t solar W is the irradiation amount at t time. is the PV conversion efficiency, taking 44%.

3) ES restraints
The battery is selected as the main ES element, which has the advantages of fast response and fast charging and discharging time.Its charge storage model is as follows [9][10] Among them, Nbty P is the rated power of the battery.

Capacity allocation optimization process
In this paper, particle swarm optimization (PSO) algorithm is used to calculate and solve the capacity allocation optimization model.The Process of capacity allocation optimization is shown in Figure 1.
The main steps are as follows: 1) Calculate the main production load in the park and predict the 8760-hour load curve of the target year.
2) According to the wind turbine and PV design parameters, the predicted 8760-hour wind power and PV output curve is calculated.
3) Input the capacity range of wind power, PV, thermal power and ES that can be developed in the park.
4) Input the local electricity price and other economic parameters.5) Execute capacity allocation optimization calculation.The parameter initialization is carried out, and the variables of the power economic optimization parameters are given initial values.The wind/PV/thermal/ES capacity are taken as the population individuals.Set the maximum number of iterations 300, the number of particles 600, and set a fixed weight coefficient of 0.8.After the boundary treatment of the constraint conditions, the next iteration optimization is carried out.Use PSO algorithm to optimize the optimal capacity.6) Output the calculation results.

Example simulation
This paper takes the production park of a cement plant in China as an example to calculate the optimal capacity allocation.

Capacity optimization analysis of micro-grid
Calculation results of capacity optimization configuration are shown in Table 2.It can be seen from the calculation results that according to the configurable resources in the park, 18000kW thermal power, 13500kW wind power and 11480kW PV power are recommended to be allocated in 2025.10 percent of the ES is allocated according to the wind and solar capacity.Statistical table of electricity calculation results are shown in Table 3.Compared with 2022, the annual production of power generation increases by 105540 MWh, the electricity purchase decreases by 50170 MWh.Statistical table of economic results are shown in Table 4.It has significant economic benefits as the annual power purchase costs decrease by 24.04 million yuan and the annual economic benefits can save 25.76 million yuan.
Figure 4 shows the 24-hour operation curve of April 19.From 0pm to 14pm, the raw material mill, kiln system and cement mill are all working, and the power load is large.The installed capacity in the plant is not enough to meet the power demand, so it is necessary to purchase power from the power grid.The ES is charged at the low price and discharged at the high price.From 14pm to 23pm, only the kiln system is left to work.The heat, wind power and PV output are greater than the total load in the plant area, so the plant area transmits power to the outside.

Economic and environmental benefits
After the completion of wind power, PV and thermal power, the annual power generation of the project will increase by about 105540 MWh.As all of them are clean power, about 31000 tons of standard coal will be saved each year based on 300g/kWh coal consumption, about 84000 tons of carbon dioxide emissions will be reduced, about 600 tons of sulfur oxides will be reduced, and about 200 tons of nitrogen oxides will be reduced.It can effectively reduce the total carbon emissions and pollutant emissions in the region and provide supports for building a low-carbon, energy-saving and green ecological park.

Conclusions
This paper evaluates the load of the industrial park and uses the PSO algorithm to optimize the capacity ratio of the park energy system considering wind/PV/ES.The following conclusions can be summarized: (1) This paper proposes an optimization model of microgrid capacity allocation considering wind power/PV/ES.With the reference data of regional wind speed, irradiation and load power, the global optimal location can be obtained by taking the maximum economic profit as the objective function, and the actual installed capacity ratio of energy in the micro-grid can be calculated.
(2) The energy capacity allocation of microgrid in a cement plant park in China is analysed and calculated in this paper.The results show that after the completion of wind power/PV/thermal/ES, the annual power generation of the project will increase by about 105540 MWh, save about 31000 tons of standard coal per year, and reduce about 84000 tons of carbon dioxide emissions.As the cost of renewable energy will be further reduced under the sustainable development of clean energy and the trend of future technology development, establishing a clean energy microgrid in the industrial park can bring considerable economic benefits.
(3) Based on the wind and solar resource conditions and calculation results of the industrial park, it is recommended to give priority to the use of roofs and open spaces in the industrial park for wind power and PV construction and allocate a certain amount of ES.The model used in this paper has been verified by an actual project in an industrial park of a cement plant.The data fits the reality, providing theoretical and practical reference for the micro-grid capacity allocation optimization of the industrial park.
(4) In the next step, we want to further improve the model, study the optimal scheduling of the daily operation cost model and consider the impact of electric vehicle and interruptible load.Besides, we will compare the common optimization algorithms and select the better ones.

Figure 1 .
Figure 1.The process of capacity allocation optimization.

Figure 2 .
Figure 2. Typical daily wind speed curve of each season.

Figure 3 .
Figure 3.Typical daily irradiation curve of each season.
is the output of wind power at t time.is the output of PV power at t time. is the output of thermal power at t time.  t bty P is the output of ES at t time.grid P is the power exchanged between the park and the external grid. P : the state of charge of the battery, which is the ratio of the current battery capacity to the battery capacity.
  t SOC is 2.2.3.Electricity price model for settlement with external power grid.Electricity price model for settlement with external power grid can be expressed as follows:

Table 1 .
Load characteristic curve.The micro-grid system in the park should consider the impact of load and local environment.Firstly, the power load and working conditions of the park are counted.The load statistics are shown in Table1.Load statistics.Wind and PV output curve.The wind power and PV power are affected by the weather.The project sets up small meteorological monitors around the park to collect data.Typical daily wind speed and irradiation curve of each season are shown in Figures2 and 3.

Table 2 .
Calculation results of capacity optimization configuration.

Table 3 .
Statistical table of electricity calculation results.

Table 4 .
Statistical table of economic results.