WO2023049942A1

WO2023049942A1 - Process of determining engine power using renewable energy.

Info

Publication number: WO2023049942A1
Application number: PCT/VN2022/000007
Authority: WO
Inventors: Huy Toan VU; Minh Tuan CAO; Van Thong NGUYEN
Original assignee: Construction Machinery And Industrial Works Coninco Joint Stock Company
Priority date: 2021-09-23
Filing date: 2022-09-12
Publication date: 2023-03-30

Abstract

The present invention relates to a process of determining engine power using renewable energy characterized in that, instead of using the concept of "rated power" P _rated as the basis for calculating the electricity production of a project, the process according to the invention uses the total annual production as a parameter of the highest reliability among the parameters of wind turbine, which is corresponding to the greatest probability that accounts for 90÷95 percentage of the total probability of the wind occurrence in the year, i.e. much closer to the actual operation of wind turbines in particular and other forms of renewable energy in general, so as to determine the annual average power P _average instead of the rated power P _rated. Moreover, the most important thing is to facilitate the change in the power coefficient C _p by changing the coefficient kp > 1 of blades for the purpose of enabling the wind turbine to work at a wind velocity close to the annual average velocity V _average while substantially maintaining most of the existing wind turbine structure and only replacing blades thereof with those having surface width that is 2÷3 times larger, thereby increasing the power coefficient C _p _. As a result, the excess equipment power can be reduced while the actual efficiency of the project will be doubled in comparison with the original in the Feasibility Study Report of the project.

Description

PROCESS OF DETERMINING ENGINE POWER USING

RENEWABLE ENERGY

Technical field of the invention

The invention relates to the field of converting renewable energy into electric energy in order to serve the needs of civil life, production activities, and so on. More specifically, the invention relates to a process of determining engine power using unstable renewable energy such as the energy from wind, solar radiation, tide, ocean wave, etc...

Technical background

In the past 30 years, renewable energy electricity such as wind electricity, solar electricity, tidal electricity, ocean wave electricity, etc., have made a huge breakthrough. According to a research by the International Energy Agency (IEA), by 2025, renewable energy will become the main source of electricity production providing a third of the electricity amount of the world. It is estimated that the total capacity of wind electricity and photoelectricity would exceed the capacity of gas by 2023 and the capacity of coal by 2024. The common feature of these forms of renewable energy is the instability characterized by probability distributions.

To make it more clearly, in this invention, the inventors used wind electricity as a specific example since it is the most popular form of renewable energy these days. Although using the wind electricity is just for illustration, the conclusions drawn therefrom are related to all forms of unstable renewable energy, but with some differences depending on the degree and the way of handling different parameters according to the characteristics of each form. The process of converting wind energy into electric energy is performed by wind engines, also known as wind turbines, whereby the turbine power, as indicated in the non-patent literature 1, is P_turbin presented by the following equation:

wherein: p is the air density;

S is the cross section area of blades;

V is the wind velocity.

The equation (1) can be written as: with:

wherein C_P i s the power coefficient of the wind turbine.

The rated annual electricity production A_rated can be calculated by multiplying the rated power P_rated obtained from the equation (1) and the annual electricity generation time t_rated

where t_rated is usually chosen by wind electricity consultants or is equal to roughly one third of the total annual electricity generation time. In another approach, the rated annual electricity production A_rated can be calculated by multiplying the average annual power P_average obtained from the cumulative Rayleigh distribution and the total time in a year (8760 hours):

For common types of electricity plants such as thermoelectric plants, hydroelectric plants, liquefied gas- electric plants, etc., with stable input energy, determining the electricity generation power and the electricity production as the equation (4) is completely normal, as it is proactive to get the electricity generation time as well as the electricity generation power. However, the wind electricity in particular, and some other forms of renewable energy electricity in general, can be affected by unpredictable factors such as the wind velocity which is a completely random quantity. Therefore, the Weibull probability distribution function for wind velocity in the year (see Figure 1) or the Rayleigh cumulative distribution function (see Figure 2) should be used for calculation. Thus, the use of the concept of “rated power” P_rated for the renewable energy forms characterized by the random probability is a conceptual flaw, because probability is merely probability, so P_rated cannot represent the electricity generation power of the wind turbine for the whole year. The same goes for solar electricity, ocean wave electricity, tidal electricity, geothermal electricity, etc... This leads to a misjudgment in the direction of excess in the wind turbines’ installed power compared to their actual power, causing a great waste in the wind electricity investment, which is inherently the top high one and giving difficulties to the policy management and planning agencies on the national electricity structure in general!

Ironically, this is also reflected even in the calculation results on the WindPRO software (see the non-patent literature 3), as the calculation basis still relies on the Weibull distribution or Rayleigh distribution (see non-patent literature 4) for the probability of wind velocity occurrence in the year. However, using the Weibull distribution to calculate the annual electricity production A_rated gives a calculation result approximately 1.4 times lower than using the Rayleigh distribution which is the cumulative probability distribution applied in the International Standard IEC 61400- 12-1 while in both cases, the wind engine power is calculated by the same equation (1), i.e. is proportional to the cube of the velocity! Is it not a defect? Moreover, in that Standard, it is considered that the power coefficient Cp is a function depending on at least the cube of velocity (based on the graphs in Figure 4 and Figure 5 of the Standard). Thus, after putting the said coefficient in the Equation (1), the power will have a sixth- order velocity dependence. Is it not unreasonable?

On the other hand, with regard to the use of the Weibull distribution, only the concept of “rated power” P_rated determined by the wind turbine manufacturer is put in the Equation (4), which is essentially the possible maximum electricity generation power (P_max) of wind turbine and 2.6 times larger than the average annual power actually generated. Meanwhile, with regard to the use of the Rayleigh distribution, in addition to the concept of “rated power” P_rated, there is also the concept of “average annual power” P_average to multiply by the total time in one year (8760 hours) in order to calculate the annual production A bated using the Equation (5). This is a more precise improvement. However, the calculation of “average power” P_average is limited by the rated wind velocity V_rated, which is initially selected and usually equals to roughly two times of V_average. Thus, the production is still not representative of all wind velocity levels in the year. Especially it is unclear in terms of physics. In all calculations, is it true if the fact that not using the wind velocity of more than 11 m/s as in the Weibull distribution would mean a default acceptance of a deviation (>5%) which is not less than a series of to-be-standardized parameters such as temperature, pressure, air density, etc., according to the instruction in the said International Standard? The improvements made so far have mainly focused on blades, such as shape, texture, quantity, etc., which leads to an improvement in the wind turbine’s efficiency of just around ±10% (see the non-patent literature 5). For example, in the patent literature 1, the inventor considered the problem related to the wind turbine blade’s disadvantage to be very serious, nonetheless, if the rated wind velocity is not brought up to 16 m/s, all efforts to improve the blades will be for nothing. Was he unaware of the fact that even in the International Standard according to the non-patent literature 4, the wind velocity of more than 11 m/s has been removed? That is, in fact, the electricity generation power expected by the inventor decreases by (16/11)³ ≈ 3 times. This is related to a concept unknown to the inventor that the wind velocity must be evaluated by the distribution probability of the wind velocity in the year. From the wind velocity of 1 1 m/s and above, this probability is very small, just under 5%, with not only the onshore wind but also the offshore wind. Obviously, accurately determining the efficiency and the rated power of the wind electricity is not simple at all, because as mentioned above, it is the result of an uncertain process, but not a deterministic one. Therefore, investing in wind turbines is facing difficulties not only in terms of the technology but also the understanding of the physical process nature, as well as the calculation method which, unfortunately, have not been mentioned in official documents so far. In fact, it is known that investment consultants still use the WindPRO software in wind electricity calculations around the world. This waste on material will lead to environmental consequences related to greenhouse gas emissions that have not been taken into account in the production, transportation, and installation of wind turbines.

Non-patent literature: 1. Betz' law. https://en.wikipedia.org/wiki/Betz%27s_law).

2. Vu Huy Toan. Calculation of the efficiency of the wind engine.

Reported at the 7th National Conference on Applied and Engineering Physics (CAEP), 2021.

3. WindPRO 3.3.294 Software.

4. International Standard IEC 61400-12-1, First press 2005-12.

5. Nguyen Ngoc Tan. Wind electricity industry, Ho Chi Minh city, 2012. https://tailieu.vn/docview/tailieu/2015/20151016/nhasinhaoanh_08/ c3_cong_nghiep_dien_gio_2012_do_ngoc_tan_6866.pdf?rand=^:813561.

Patent literature:

1- Method of determining and controlling the inclination of wind turbine blades with fixed rotational speed. Patent No. 19142, 2018.

Summary of the invention

The purpose of the process of determining engine power using renewable energy according to the present invention is to overcome the disadvantages stated in the technical background of the invention. In particular, in an embodiment, the invention proposes a process comprising:

(i) preliminary preparation step including: selecting a wind engine with a rated power P_rated and a wind velocity V_rated suitable for a project; creating a statistical table for project parameters including wind velocity V_i, probability p_i, wind turbine power P_i, and wind electricity production A_i in the column order in an Excel spreadsheet, wherein in the row order in the Excel spreadsheet, the wind velocity V_i corresponds to each 0.5 m/s bin defined by the International Standard; determining the value X for the project using the equation X =

determining the wind turbine power P_i at each specific wind velocity V_i according to the Weibull distribution using the equation P_i = then filling these values P_i in the statistical table;

identifying among the power values P_i a power value PN that is closest to the rated power P_rated to set that value PN for all indexes i > N; determining the wind electricity production A_i corresponding to the power P_i and the probability P_i that the wind velocity occurs in the range from the minimum wind velocity that can generate the electricity to the maximum wind velocity K_max; determining the total annual wind electricity production A_N from all A_i corresponding to the total occurrence probability of wind velocity in the range from

comparing the value A_N with the rated production value A_rated of the wind turbine technical document, if the deviation is not more than ±10% then moving onto file next steps, otherwise replacing the Weibull distribution with the Rayleigh distribution and following the instructions in the International Standard IEC 61400-12-1 to determine the average power P_average in order to get the rated production A'_rated (also known as “annual energy production” - AEP) and take the next step; determining the production difference coefficient:

>1;

(ii) power determination step including: a) re-determining the rated wind velocity V'_rated equal to or greater than 3÷4 bins of the annual average wind velocity V_average; b) determining the power P'_i at each specific wind velocity V_i according to the Weibull distribution using the equation and it

is necessary to change values k_p > 1 until at the newly chosen rated wind velocity V'_rated, the corresponding power value P_M reaches approximately the value P_rated then stop, thereby the blade area will increase in proportion to that coefficient k_p; c) setting this power value P_M for all power values with the index i

>M d) determining the wind electricity production A'_i corresponding to the power P'_i and tiie probability p_i that the wind velocity occurs in the range from V_min to V_max; e) determining the total annual wind electricity production A"_rated from all At corresponding to the total occurrence probability of the wind velocity in the range from V_min to V_max, f) multiplying the coefficient k_A by A"_rated to get a new total annual electricity production A_ratedM to be generated; g) dividing this total electricity production by the total expected electricity generation time T_expected according to the total probability of wind velocity distribution in the year p_N to get the wind turbine’s annual average power value P_average, which is the actual electricity generation power value of the project.

The characteristics of the process according to the invention are as follows.

Instead of using the concept of “rated power” P_rated as the basis for calculating the electricity production of the project, the process according to the invention uses the total annual production as a parameter of the highest reliability among the parameters of wind turbine, which is corresponding to the greatest probability that accounts for 90 ÷95 percentage of the total probability of the wind occurrence in the year, i.e. much closer to the actual operation of wind turbines in particular and other forms of renewable energy in general, so as to determine the “annual average power” P_average instead of the “rated power” P_rated. Moreover, the most important thing is to facilitate the change in the power coefficient C_p by changing the coefficient k_p > 1 of blades for the purpose of enabling the wind turbine to work at a wind velocity close to the annual average velocity V_average while substantially maintaining most of the existing wind turbine structure and only replacing blades thereof with those having surface width that is 2÷3 times larger. In fact, it is to increase the power coefficient C_p.

The process of determining engine power using renewable energy according to the invention has the following advantages:

First, since such highly reliable quantities as the total actual operation time in a year and the total annual production are used to reversely determine the installed power, the present invention is more practical when facing with uncertain input quantities, such as the wind velocity. Therefore, the current excess installed power for the wind electricity can be reduced by roughly 2 times and the wind electricity cost can also be reduced by the same amount.

Second, since the priority is not given to high wind velocities with a small occurrence probability but a wind velocity close to the annual average wind velocity with a much larger occurrence probability, the equipment power can be utilized at the maximum level while the annual electricity production can be doubled and the load on blades is significantly reduced by approximately 2 times. Third, because the actual electricity generation power can account for roughly 70% of the rated power with a probability much higher than before, the stability of the buyers’ power grid and the efficiency of the investors’ investment capital are increased, facilitating the strategic planners in the electricity system development with the avoidance of the current virtual power phenomenon, especially when the renewable energy is gradually becoming an electricity source equivalent to the coal-fired thermal electricity.

Fourth, according to a preferred embodiment, the rated production is kept unchanged, the wind turbine power can be reduced by 1.5÷2 times, and so can the total investment capital for the project. On the contrary, if the rated wind turbine power is kept unchanged, the annual electricity production can be nearly doubled, that is equivalent to an investment of two more such projects.

Fifth, because only a replacement of blade with a surface width of 3-4 times larger than those of the existing blades is required to increase the power coefficient C_p, the wind turbine reconstruction can be done on a large scale not only for wind turbines that are being or will be manufactured and/or installed, but also for wind turbines that are in use as it is possible for them to be replaced at the time of maintenance. Replacing blades may cost further roughly 10% of the investment expense, but in return, the production of the reconstructed wind turbine will increase around two times, meaning to have another one wind turbine.

Brief description of figures

The purposes, advantages and other aspects of the invention will become clearer with the following detailed description based on the accompanying figures: Figure 1 is a graph of the probability of wind velocity occurrence according to the Weibull distribution.

Figure 2 is a graph of the probability of wind velocity occurrence according to the cumulative Rayleigh distribution.

Figure 3 is a logical diagram of the classical power determination process with predetermined energy forms.

Figure 4 is a logical diagram of the power determination process according to the International Standard.

Figure 5 is a logical diagram of the power determination process according to the first embodiment.

Figure 6 is a logical diagram of the power determination process according to the second embodiment.

Figure 7 is a statistical data table for a project taken from the International Standard as an example.

Figure 8 is a statistical data table for a project of the invention as an example.

Detailed description of the invention

Next is a detailed description of the process of determining the engine power using renewable energy with the reference to the attached Figures 1 - 8. According to the first embodiment - keeping the rated power unchanged, the process comprising:

(i) preliminary preparation step including:

- selecting a wind engine with a rated power P_rated and a wind velocity V _rated suitable for a project;

- creating a statistical table for project parameters including wind velocity V_i, probability p_i wind turbine power A, and wind electricity production A, in the column order in an Excel spreadsheet, wherein in the row order in the Excel spreadsheet, the wind velocity Vi corresponds to each 0.5 m/s bin defined by the International Standard;

- determining the value X for the project using the equation X —

- determining a wind turbine power P_i at each specific wind velocity V_i according to the Weibull distribution for each hour of the year in the range from the minimum wind velocity V_min that can generate the electricity to the maximum wind velocity' V_max using the given equation:

then filling these values P_i in the statistical table;

- identifying among the power values P_i a power value P_N that is closest to the rated power P_rated to set that value P_N for all indexes i > N;

- determining the wind electricity production A_i corresponding to the power P_i and the probability that the wind velocity occurs in the range from V_min to V_max;

- determining the total annual wind electricity production A_N from all A_i corresponding to the total occurrence probability of wind velocity in the range from V_min to V_max;

- comparing the value A_N with the rated production value A_rated of the wind turbine technical document, if the deviation is not more than ±10% then moving onto the next steps, otherwise replacing the Weibull distribution with the Rayleigh distribution and following the instructions in the International Standard IEC 61400-12-1 to determine the average power P_average in order to get the rated production A_rated and take the next step (see Figure 4);

- determining the production difference coefficient:

(ii) power determination step including: a) re-determining the rated wind velocity V’_rated equal to or greater than 3÷4 bins of the annual average wind velocity V_average; b) determining the power P_i at each specific wind velocity V_i according to the Weibull distribution using the equation

and it is necessary to change values k_p > 1 until at the newly chosen rated wind velocity V’_rated, the corresponding power value PM reaches approximately the value P_rated then stop, thereby the blade area will increase in proportion to that coefficient k_p; c) setting this power value PM for all power values with the index i > d) determining the wind electricity production At corresponding to each wind velocity occurrence probability pi at the wind velocity F? in the range from V_min to V_max; e) determining the total annual wind electricity production A "rated from all Ai corresponding to the total occurrence probability of the wind velocity in the range from to V_max; f) multiplying the coefficient

expected to be around 1.4, with A "rated to get the total annual electricity production to be generated, expected to be around g) dividing this total electricity production 2A_rated by the total expected electricity generation time T_expecteci according to the total probability of wind velocity distribution in the year (normally 90%) to get the wind turbine’s annual average power value P_average, which is the actual electricity generation power value of the project (see Figure 5).

According to the probability theory, even if an event i occurs randomly, characterized by a concept called probability < 1, the sum of the probabilities of all events in the range within which the said events are possible to occur is always equal to 1. In this case, it is the wind velocity V_i from 0 m/s to V_max. So, for the greatest reliability, lets start from what is related to this probability range being equal to 1, which is the total time of the wind occurrence with the wind velocity ranging from 0 m/s to V_max for the whole year: 365x24 = 8760 hours. From that, the total actual annual electricity generation time (t_N) in the unit of hours (h) can only be:

Here, the first sum on the right-hand side of the equation is the total time corresponding to the wind velocity less than the minimum designed velocity of the wind turbine to start generating the electricity. The second sum is the total time corresponding to the maximum power P_N that the selected wind engine can generate electricity and since then, even if the wind velocity is higher than the designed velocity the power cannot further increase but always remains equal to the power P_N . That is, must correspond to the total occurrence probability of the wind velocity from V_min to V_max.

Normally, it is possible to choose p_N ~90% which is equivalent to the total actual annual electricity generation time t_N - 90%x8760 h = 7884 h. h) selecting the installed power of the equipment P_installed ⁼ kP_N where k > 1 (the safety coefficient). To characterize the actual electricity generation power of the project, the concept of “annual average power” shall be used as follows:

This power is the one that properly reflects the participation of wind electricity in the national electricity grid.

From a different aspect, the process according to the second embodiment - where the rated production is kept unchanged (see Figure 6), comprising:

(i) preliminary preparation step similar to those of the first embodiment;

(ii) power determination step substantially similar to those of the first embodiment, except that the sub-steps a) and c) of the latter are respectively replaced with the following: a) determining the value X” for the project using the equation X" =

c) determining the power Pi at each specific wind velocity V_i according to the Weibull distribution using the equation and

it is necessary to change values k’_p > 1 until at the newly chosen rated wind velocity V'_rated, the corresponding power value PM reaches approximately the value 0.5P_rated then stop, thereby the blade area will increase in proportion to that coefficient k_p. Thereby, it can be seen that the production Arated mainly remains unchanged, but the wind turbine power can be reduced by roughly 2 times, which means an approximate 2-time reduction in the total investment capital (see Figure 7 and Figure 8).

Effectiveness of the invention

The process of determining engine power using renewable energy according to the invention allows the determination of the wind turbine power to be closer to reality than the traditional process. This process also allows a change in the power coefficient to enable a two-time increase in the profit margin from wind electricity projects in particular and other renewable energy projects in general.

Claims

1. A process of determining the engine power using renewable energy, the process comprising:

(i) preliminary preparation step including: selecting a wind engine with a rated power P_rated and a wind velocity V_rated suitable for a project; creating a statistical table for project parameters including wind velocity V_i, probability p_i, wind turbine power P_i and wind electricity production A_i in the column order in an Excel spreadsheet, wherein in the row order in the Excel spreadsheet, the wind velocity V_i corresponds to each 0.5 m/s bin defined by the International Standard; determining the value X for the project using the equation X =

determining a wind turbine power P_i at each specific wind velocity V_i according to the Weibull distribution using the equation , then

filling these values P_i in the statistical table; identifying among the power values P_i a power value P_N that is closest to the rated power P_rated to set that value P_N for all indexes i > N; determining the wind electricity production A, corresponding to the power P_i and the probability p_i that the wind velocity occurs in the range from the minimum wind velocity V_min that can generate the electricity to the maximum wind velocity V_max; determining the total annual wind electricity production A_N from all A_i corresponding to the total occurrence probability of wind velocity in the range from V_min to V_max; comparing the value A_N with the rated production value A_rated of the wind turbine technical document, if the deviation is not more than ±10% then moving onto the next steps, otherwise replacing the Weibull distribution with the Rayleigh distribution and following the instructions in the International Standard IEC 61400-12-1 to determine the average power P_average in order to get the rated production A '_rated and take the next step; determining the production difference coefficient:

(ii) power determination step including: a) re-determining the rated wind velocity V'_rated equal to or greater than 3÷4 bins of the annual average wind velocity b) determining the power P'_i at each specific wind velocity V_i according to the Weibull distribution using the equation and it

is necessary to change values k_p > 1 until at the newly chosen rated wind velocity V'_rated, the corresponding power value P_M reaches approximately the value P_rated then stop, thereby the blade area will increase in proportion to that coefficient k_p,' c) setting this power value P_M for all power values with the index i > M; d) determining the wind electricity production A'_i corresponding to the power P'_i and the probability p_i that the wind velocity occurs in the range from V_min to V_max; e) determining the total annual wind electricity production A"_rated from all A_i corresponding to the total occurrence probability of the wind velocity in the range from V_min to V_max; f) multiplying the coefficient k_A by A "_rated to get a new total annual electricity production A_ratedM to be generated; g) dividing this total electricity production by the total expected electricity generation time T_expecfed according to the total probability of wind velocity distribution in the year p_N to get the wind turbine’s annual average power value P_average, which is the actual electricity generation power value of the project.

2. The process according to claim 1. wherein sub-steps a) and c) in the power determination step (ii) are respectively replaced with the following: a) determining the value X" for the project using the equation X" =

c) determining the power P_i at each specific wind velocity V_i according to the Weibull distribution using the equation , and

it is necessary to change values k'p > 1 until at the newly chosen rated wind velocity V'_rated, the corresponding power value P_M reaches approximately the value Q.5P_rated then stop, thereby the blade area will increase in proportion to that coefficient k'_P.