Weather index insurance for wind energy

1 Introduction

Energy is the driving force for global economic and social development.With industrialization and the rapid growth of economies,the global demand for energy has been increasing.As the dominant energy,fossil energy has been exploited and utilized in large quantities,making resources shortage,environmental pollution,and climate change increasingly prominent and seriously threatening human survival and development [1-3].Therefore,it is imperative to promote global energy transformation [4-7].One fundamental solution is to accelerate the replacement of fossil energy generation with clean energy generation particularly solar and wind energy [8].

In recent years,China has actively developed new energy sources like photovoltaics and wind and has become the world’s largest clean energy-producing country.In 2018,China’s installed capacity of wind and solar power accounted for 32.8% and 36% of the world’s total,respectively.However,with the sustainable development of new energy,the government is gradually abolishing subsidies for transfer payment [9].Moreover,economy has gradually replaced environmental protection and become the focus of new energy enterprises.Because of the characteristics of wind power generation,the core risk that determines their economic feasibility is the weather.Wind power companies experience great fluctuations in profitability due to periodic shortages of wind resources in some areas,with occasional losses.The 2007 China Wind Power Group Annual Report showed that most wind power plants located in Northeast,North,and Northwest China had lower power generation than the national average for that year.In 2011,another large-scale wind shortage occurred in large parts of China.During this time the average wind power utilization of the China Longyuan Power Group Corporation was 2,016 hours,196 hours lower than the same period in the previous year,and the estimated loss was over 800 million yuan.The average utilization of Huaneng Renewables Corporation in 2011 was 1,962 hours,which was 13.4% lower than in 2010,with a total loss over 700 million yuan.The average utilization of Datang New Energy Group was 1,951 hours,down by 8.6% from a year earlier,with an estimated loss of more than 400 million yuan.The weighted average equivalent full load utilization of wind farms belonging to the China Wind Power Group was 1,773 hours,decreasing by 15.9% from 2010,with a loss of more than 270 million Hong Kong dollars.The average utilization of China Suntien Green Energy Corporation fell to 2,048 hours,reducing by 13.2% from 2010,with a loss of more than 170 million yuan.Also,the wind power resources of Jiangsu Zhongdian New Energy Co.,Ltd.in 2011 decreased slightly compared with the previous year,which had an impact on power generation.The group’s net profit for that year was about 196,549,000 yuan,declining by 30% from 2010,with a loss of nearly 100 million yuan.In 2014,a large-scale shortage of wind resources occurred again in northern China.According to the 2014 Wind Power Industry Monitoring issued by the National Energy Administration,the annual average wind speed at 70 meters elevation was about 5.5 meters per second in 2014,which was 8%～12% lower compared to previous years.The average utilization hours of wind power in China in 2014 was 1,893 hours,down 181 hours from the same period in the previous year.The average wind power utilization was the highest in Yunnan,2,511 hours,while the lowest was in Tibet with 1,333 hours.All major wind power groups in China were affected without exception.The 2014 Datang New Energy Annual Report showed that the utilization hours of wind power decreased by 9.9% compared with the previous year,and the total wind-power generation decreased by 4.99% compared with the same period in 2013,resulting in a net loss.

The reduction in the return rate of wind power generation directly affects the return rate of new energy investment.Fortunately,with the improvement in new energy accommodation technology,the phenomena of wind and solar curtailment have been alleviated.More and more wind power enterprises are paying attention to the economic losses caused by weather risks such as the lack of wind.Although weather events bring uncertainty to people’s lives,property,and production and manufacturing activities,the Weather Risk Management Association points out that people can mitigate the economic losses caused by the weather by obtaining insurance or financial services for weather risks [10].

At present,research on new energy mainly focuses on new energy power generation [11],new energy power system planning [12-14],and operation and control technology [16,17].There is a lack of effective weather risk management tools in new energy power generation,which is significantly affected by changes in the weather.Weather risk insurance can be used to reduce the losses caused by weather changes.However,there is very little research on weather index insurance for wind power generation.

Therefore,herein we focus on the weather risks suffered by wind power operation and generation.Through weather index insurance modeling and prediction calculation methods,the wind-speed power index insurance model is built and a weather risk management method suitable for wind power enterprises is proposed to reduce the volatility of wind power enterprise profitability and increase the return on investment.The simulation results show that the weather index insurance proposed herein can effectively avoid economic losses caused by weather risks for wind power enterprises.

2 Weather index insurance

Weather index insurance [18-20] (or meteorol ogical index insurance) is a type of insurance for coping with weather changes.The triggering conditions are the meteorological elements (such as wind speed,temperature,rainfall) suffered by the insured object in a specific area.When the triggering conditions are met,the insured object can claim the corresponding insurance compensation.Weather index insurance was first used by North American energy suppliers to avoid losses caused by abnormal weather.At present,more and more scholars believe that weather index insurance is effective for coping with weather changes and natural disasters in developing countries,and it is also an important development direction for agricultural insurance in developing countries [21].Weather index insurance has been strongly supported by many governments and international organizations such as the World Bank.

Weather index insurance research begins with the initial concept,followed by a feasibility study and pilot experience summary,and finally to statistical modeling and precise pricing models.Weather index insurance overcomes the problem of information asymmetry,which reduces adverse selection and prevents moral hazards [22].Insurance prices can be effectively reduced by the following methods:reducing sales costs by designing standardized contracts,reduction of management costs by classifying the risk exposure of the insured,optimization of the compensation process,and reduction of compensation costs by utilizing objective weather data from meteorological stations,rather than estimating the actual losses of policy-holders [23].Weather index insurance is easy to trade and transfer and is suitable for introduction to capital markets.Meanwhile,it can use strong capital markets to diversify agricultural risks,and take advantage of international financial markets to diversify weather systemic risks [24].

Wind-speed power generation index insurance has great advantages,possessing both the characteristics of weather index insurance and the unique characteristics of the wind power industry.Its feasibility is mainly based on the following.First,both wind power and agricultural enterprises need to invest in wind-speed power generation index insurance and agricultural weather index insurance,respectively,in advance,and then produce corresponding products according to weather conditions to earn profits.The difference is that the former produces electricity while the latter produces crops.Second,wind speed weather index insurance can decide whether to settle claims based on objective meteorological data.It has the objectivity and transparency of agricultural weather index insurance.Furthermore,it minimizes subjectivity and arbitrariness.As long as the wind speed reaches a certain trigger point,wind power enterprises can obtain economic compensation from insurance companies,which reduces the cost of claims and disputes.At the same time,it also reduces the moral hazard of wind power enterprises to a certain extent.

Wind-speed power generation index insurance has its own particularities:

(1) the risk of base differences is relatively small.Windspeed power generation index insurance mainly depends on the abundance or lack of wind resources,which is directly linked to weather conditions.The higher the wind speed is,the more electricity will be generated by wind power enterprises,and higher revenue will be produced in the context of relatively stable electricity prices.Therefore,the risk of insurance base differences for the wind speed power generation index is small,ensuring its smooth operation.

(2) Data is more transparent and reliable.Although wind power enterprises have heterogeneity,the energy conversion rate of wind energy is relatively fixed and clear,and the loss of wind power enterprises can be quantified very well,which is conducive to establishing premium rates.Moreover,it is fairer to the contracting parties,and will not lead to difficulties in rate determination or damages for the insurer because of information asymmetry and lack of data.Wind-speed power generation index insurance can accurately measure the size of the loss and provide accurate compensation.

3 Wind-speed generation index insurance model

Wind-speed power generation index insurance is a new energy insurance product which is based on specific meteorological data (wind-speed grade) to calculate the amount of compensation,rather than the possible loss (such as the income loss of wind power generators).The core of the wind-speed power generation index insurance model involves the calculation of the wind speed generation index and insurance pricing.

3.1 Wind-speed generation index model

The wind-speed power generation index is calculated based on the actual wind speed of the insured site and specifies the accounting rules and impact factors.The calculation determines the theoretical power generation during the insurance period of the insured wind power plant in kilowatt-hours.The calculation formula is a function of the average wind speed in the wind farm,generation time,wind speed generation efficiency coefficient,and the conversion rate of wind power to grid.

In equation (1),Iw is the wind-speed power generation index during the insurance period,Qw is the theoretical ongrid power generation during the insurance period of the wind power plant,Vw is the average wind speed during the insurance period of the wind power plant,Tw is the power generation time of the wind power plant during the insurance period,kw is the efficiency coefficient of windspeed power generation,and θw is wind power on-grid power generation conversion rate.

The average value of the theoretical active power of wind power plants varies with the change of wind speed.The ordinary least squares (OLS) model can be used for describing the linear relationship between wind speed and the average value of the theoretical active power.The linear model can be expressed as follows:

In equation (2) Qav,w is the average value of the theoretical active power of wind power plant.

3.2 Insurance pricing model of the wind-speed generation index

For practical applications,some scholars have proposed three different weather index insurance pricing methods from the perspective of risk dispersion,risk hedging,and maximal utility:actuarial pricing [25],derivative pricing [26],or undifferentiated pricing [27].In countries and regions where the development of a weather index insurance was successful,the actuarial pricing method is the most widely used,especially the classical combustion analysis method.The actuarial pricing method can work simply based on limited historical data and is suitable for our model.In addition,from the perspective of risk diversification,the actuarial pricing method can easily calculate the pure insurance rate with relatively low pricing costs.This method can effectively fill in the voids for insurance in the energy generation industry.Therefore,the actuarial pricing method was chosen to establish the insurance pricing scheme for the wind-speed power generation index developed in this paper.

3.2.1 Actuarial pricing method

The classical combustion analysis method is the most commonly used actuarial pricing method in weather index insurance pricing.It assumes that the probability distribution of future loss is consistent with that of historical experience,and takes the expected value of historical data compensation value as the optimal estimate of pure premium [25].The calculation of pure premium is as follows:

In equation (3),Ii represents the weather index in the ith year,W(Ii) represents the economic loss in the ith year,n represents the total number of observed years,and e-r(T-t) represents the risk-free discount factor.The exponential model method improves the classical combustion analysis method.First,this method performs the distribution probability fitting on historical empirical data.Then,the maximum likelihood estimation method is used to estimate the model parameters.Finally,the expected payout value,which is the pure premium,is calculated.

3.2.2 Calculation of insurance premiums for the wind-speed generation index

The wind-speed index needs to set a trigger value, QTR.Only when the wind-speed index is lower than the trigger value will the insurance company have to pay the corresponding compensation to the insured.The compensation formula can be expressed as:

Equation (4) is intended to illustrate the compensation situation obtained by the insurer based on the actual risk wind-speed power generation index,after insurance.P(Iw,m) represents the compensation value of the mth month, QTR,m represents the trigger value of the mth month,Iw,m represents the wind-speed generation index of the mth month,and Cw is the on-grid wind power price.In practice,the insurance period is usually one year,therefore the weather index insurance is calculated monthly.According to the actuarial pricing method,the pure premium of the wind-speed index insurance is calculated.Because of the limited interest rate data and short insurance period,the risk discount factor is often neglected in practical application,and is simplified as follows:

In equation (5),Fw is the pure premium of the wind-speed power generation index and m is the total number of months during the insurance period.

4 Profit analysis method for wind power enterprises

Without considering weather index insurance,the profits of wind power enterprises mainly come from selling electricity.The profit is expressed follows:

In equation (6),Cpro represents the profit of wind power enterprises without considering weather index insurance and qw,m is the actual power generation of the wind power plant in the mth month.

When wind power enterprises consider purchasing weather index insurance,the profit calculation formula is as follows:

In equation (7) Cpro,after represents the profit of wind power enterprises after purchasing weather index insurance.

After purchasing weather index insurance,the increase in income ΔCpro for wind energy enterprises is:

5 Case study

5.1 Data source

The on-grid price and power generation capacity of a wind power producer is greatly influenced by the local wind power resources.Hence,we need to determine the nature of the insurance premium and the premium amount according to the characteristics of the insured.This section takes 2017 data provided by a wind power enterprise in Xinjiang as an example to illustrate the principle of setting the applicable wind-speed index insurance premium.Fig.1～4 show the time-varying curves of the average monthly wind speed,monthly power generation hours,power generation,and theoretical active power,respectively,of the selected wind power plant in 2017.The wind speed hours is the sum of the time periods when the wind speed exceeds 3.5 m per second per month,that is,the number of generating hours per month.

Fig.1 Monthly average wind speed curve of the wind farm

5.2 Insurance premium decisions for windspeed power generation index insurance

The conversion rate of the wind farm on-grid power generation is the ratio of the theoretical power generation to the actual grid power.It is determined by consultation between the insurer and the insured according to actual situations.The assumed conversion rate here is 0.65.According to the average monthly wind speed and theoretical active power of wind power plant provided in Section 4.1 and utilizing the OLS model proposed in Section 2.1,the wind-speed generation efficiency coefficient can be obtained,kw = 217.61.

Fig.2 Monthly power generation hours of the wind farm

Fig.3 Monthly power generation of the wind farm

Fig.4 The theoretical active power average of the wind farm

According to Section 2.1,the theoretical on-grid generation capacity of the wind power plant during the insurance period,i.e.wind-speed generation index,can then be calculated.The results are shown in Table 1.

Wind-speed index loss:

(1) When the wind-speed index value is equal to or larger than the trigger point,the wind-speed index loss is equal to zero.

(2) When the wind-speed index value is less than the trigger point,wind-speed index loss is equal to the smaller of the following values:the trigger point minus the windspeed index,multiplied by the price of on-grid electricity and limit of compensation.

It is assumed that the trigger point is 90% of the theoretical on-grid power of the insured wind power station.The price of on-grid electricity is determined by the situation in the insured area.In this case,the on-grid price is 0.58 yuan/kWh.According to the wind-speed generation index,trigger value,and grid price,we can calculate the power generation paid for that period and the compensation expenditure corresponding to the wind-speed generation index,as shown in Table 1.

As can be seen from Table 1,there were seven lowwind-resource months in 2017,with a total compensation of 121,800 yuan for the whole year.According to equation (5),the average monthly compensation can be calculated,that is,the net premium is 102,000 yuan.

Table1 Power generation paid in the experience period and corresponding compensation

Corresponding compensation amount of wind-speed generation index in the experience period (yuan)1 28,320.18 16,425.70 2 40,656.00 23,580.48 3 0.00 0.00 4 7,090.39 4,112.43 5 0.00 0.00 6 0.00 0.00 7 5,165.78 2,996.15 8 0.00 0.00 9 61,602.98 35,729.73 10 0.00 0.00 11 24,413.98 14,160.11 12 42,868.94 24,863.98 Average Value 10,155.72 Month Power generation paid (kWh)

5.3 Wind power enterprises profit analysis before and after purchasing insurance

As discussed in Section 3 of this paper,the profits of wind power enterprises before purchasing insurance is mainly related to the actual power generation capacity of wind power plants and the price of on-grid electricity.In the situation were wind-speed power index insurance is purchased,the profits of wind power enterprises are also related to the amount of compensation and premiums.Table 2 shows the profits of the wind power enterprise in this example before and after insurance,as well as the increase in earnings after purchasing insurance.

Table2 Comparative analysis of profit before and after wind power enterprises insured

Increase in earnings (thousand yuan)Before insurance 5,242.1 0 After insurance 5,353.8 111.7 Scenario Profit of wind power enterprise (thousand yuan)

6 Conclusions

China has strived to aggressively promote new energy,and wind power is bound to be well-developed.At the same time,with the rising energy demand and improvements in wind-power generation technologies,the wind power market will surely expand at a high speed.However,wind power enterprise losses caused by the irregular shortage of wind resources in some areas will also be very significant.Therefore,it is important to study and develop a windspeed power index insurance for stabilizing the return on investment of wind power enterprises and increasing the scale of investments in new energy.The application and promotion of wind power insurance will stimulate the healthy development of wind power.The wind-speed index insurance was developed in this paper in view of the shortage of wind resources faced by the wind power industry.In summary,this study established the following:

(1) Compared with agricultural weather index insurance,the comparability and particularity of wind-speed power index insurance are better.Wind-speed power index insurance for wind power generation is feasible and should be applied.In addition,because of the heterogeneity of indicators,uncertainties can be greatly reduced.

(2) The appropriate calculation methods for the windspeed power generation index and weather index insurance pricing for wind power enterprises were analyzed.The actuarial pricing method was selected,and an efficient weather index insurance model for wind power enterprises was developed.

(3) Using the data from a wind power producer in Xinjiang province,the weather index insurance model for wind power enterprises was simulated and tested.The simulation results show that the weather index insurance proposed in this paper can effectively reduce the economic losses caused by weather risks encountered by wind power producers.

Acknowledgements

This work was supported by the State Grid Science and Technology Project (Research on Transnational Energy Interaction Simulation and Deduction Technologies of Global Energy Interconnection,JS71-17-004).