1. An assembly for mounting a plurality of photovoltaic modules over an installation surface, the assembly comprising:
a rigidly interconnected array of PV modules laid up on top of a roof without penetration into the roof where the array is large enough in horizontal area for weight of the array to be high enough to resist wind uplift based only on area and weight of the array, without additional ballast and without any roofing penetration
2. The assembly of claim 1 wherein the module weight is at least 16 kgm2, with a minimum area of 25 square meters and a minimum lowest dimension of 5 meters in the x or y axis, with a maximum weight of the array not to exceed 32 kgm2.
3. The assembly of claim 1 wherein module weight to module area is at least 16 kgm2, with a minimum area of 36 square meters and a minimum lowest dimension of 6 meters in the x or y axis, with a maximum weight of the array not to exceed 32 kgm2.
4. The assembly of claim 1 wherein theto area is at least 16 kgm2, with a minimum area of 36 square meters and a minimum lowest dimension of 6 meters in the x or y axis, with a maximum weight of the array not to exceed 32 kgm2.
5. The assembly of claim 1 wherein the module weight to area is at least about 50% of the weight of the entire array.
6. The assembly of claim 1 wherein the module weight to area is at least about 40% of the weight of the entire array.
7. The assembly of claim 1 wherein the minimum horizontal area is at least 5 m\xd75 m.
8. The assembly of claim 1 wherein the minimum horizontal area is at least 6 m\xd76 m.
9. The assembly of claim 1 wherein the minimum weight of the modules is at least 14 kgm2.
10. The assembly of claim 1 wherein the array has a configuration that resists wind uplift at lateral winds of up to 80 mph.
11. The assembly of claim 1 wherein the array has a configuration that resists wind uplift at lateral winds of up to 100 mph.
12. The assembly of claim 1 wherein the array comprises of the PV modules, a support grid beneath the PV modules, and non-roof penetrating grid supports for lifting the support grid above the roof.
13. The assembly of claim 1 wherein the modules are mounted over junction points of elongate elements in the grid to provide rigidity to the grid by rigidly coupling the module over the grid to use the module as a stiffening member
14. The assembly of claim 1 further comprising angled flaps that minimize wind flow to the underside of the modules.
15. The assembly of claim 1 wherein a downward pressure is created in about a center 70% area of the array.
16. The assembly of claim 1 wherein a downward pressure is created in about a center 60% area of the array.
17. The assembly of claim 1 wherein overall maximum edge deflection during wind load is less than about 10 degrees from horizontal.
18. The assembly of claim 1 wherein overall maximum edge deflection during wind load is less than about 5 degrees from horizontal.
19. An assembly for mounting a plurality of photovoltaic modules over an installation surface, the assembly comprising:
a rigidly interconnected array of PV modules laid up on top of a roof without penetration into the roof where the array has a horizontal area of at least 25 square meters with a minimum of 5 meters in both the x and y axis, and weight of the array to be at least 3.3 lbsft2 to resist wind uplift based only on area and weight of the array, without additional ballast and without any roofing penetration, total weight not to exceed 6.6 lbsft2.
20. An assembly for mounting a plurality of photovoltaic modules over an installation surface, the assembly comprising:
a support grid defined by a plurality of elongate members;
a plurality of non-roof penetrating grid supports configured to elevate the support grid above the installation surface;
wherein the support grid when coupled to the photovoltaic modules, creates a stiffly interconnected block of PV modules in a non-bending geometry in winds of up to 85 mph that prevents wind up lift.
21. The assembly of claim 20 wherein:
the supports are positioned at locations where the elongate members cross or intersect;
wherein the support grid is configured to receive the PV modules at locations where the elongate members are joined whereby when the grid is coupled to the photovoltaic modules, creates a stiffly interconnected block of PV modules in the non-bending geometry in winds of up to 85 mph that prevents wind up lift;
wherein the modules weigh more that the support grid, total weight not to exceed 4 lbsft2.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A plant controlling device having an operation signal generator for generating an operation signal to be given to a plant, which is a control target, the plant controller comprising:
a model for predicting the value of a measured signal obtained when an operation signal is given to the control target; a target model output value determining device for determining a target model output value by using the measured signal obtained from the control target and a measured signal limit value set in advance; and a learning device for learning a method of generating a model input so that a model output, which is a prediction result yielded by the model, satisfies the target model output value; wherein the operation signal generating device generates an operation signal with reference to a database that stores results of learning obtained by the learning device.
2. The plant controlling device according to claim 1, further comprising: a database for storing measured signal limit values set in advance; an external input interface for fetching measured signals from the control target; a measured signal database for storing the values of the fetched measured signals; and a function for determining the target model output value by using the measured signal limit values and at least one of an average, a maximum value, or a minimum value that are calculated from the measured signals stored in the measured signal database; wherein the learning device is used for learning so as to attain the determined target value.
3. The plant controlling device according to claim 2, wherein
the function for determining the target model output value subtracts the average of the measured signals from the maximum value of the measured signals and further subtracts the absolute value of the subtraction result from the measured signal limit value to determine the target model output value.
4. The plant controlling device according to claim 2, further comprising an evaluated value calculating device for calculating an evaluated value used for the learning; wherein when the target model output value is attained, the evaluated value calculating device yields a positive or negative evaluated value; the learning device learns an operation method in which an expected value of the evaluated value is maximized or minimized.
5. The plant controlling device according to claim 2, further comprising a user interface for accepting the measured signal limit values.
6. The plant controlling device according to claim 1, further comprising a target model value changing device for increasing or decreasing the target model output value; wherein
the target model value changing device is first used to learn the method of generating a model input so as to attain an initial value of the target model output value, and then the operation signal generation device generates an operation signal with reference to a database that stores results obtained by learning the method of generating a model input to attain the increased or decreased target model output value.
7. The plant controlling device according to claim 1, further comprising: a database for storing measured signal limit values set in advance; an external input interface for fetching measured signals from the control target; a measured signal database for storing the values of the fetched measured signals; a function for determining an initial value of the target model output value by using the measured signal limit value and at least one of an average, a maximum value, or a minimum value that are calculated from the measured signals stored in the measured signal database; and a function for decreasing or increasing the target model output value when the model output satisfies the target model output value; wherein the learning device is used for learning so as to attain the initial value and the increased or decreased target model output value.
8. The plant controlling device according to claim 7, wherein the function for determining the initial value of the target model output value subtracts the average of the measured signals from the maximum value of the measured signals and further subtracts the absolute value of the subtraction result from the measured signal limit value to determine the target model output value.
9. The plant controlling device according to claim 7, further comprising an evaluated value calculating device for calculating an evaluated value used for the learning; wherein when the target model output value is attained, the evaluated value calculating device yields a positive or negative evaluated value; the learning device learns an operation method in which an expected value of the evaluated value is maximized or minimized.
10. The plant controlling device according to claim 7, further comprising a user interface for accepting the measured signal limit values.
11. A thermal power plant controlling device for generating an operation signal so that the value of a measured signal satisfies a target operation value for a thermal power generation plant, which is a control target, the measured signal being obtained when the operation signal is given to the control target, wherein
the controlling device comprising:
a model for predicting the value of a measured signal obtained when an operation signal is given to the control target;
a learning function for learning a method of generating a model input to be given to the model so that a model output, which is a prediction result yielded by the model, satisfies a target model output value;
a function for determining an operation signal to be given to the control target according to a result of the learning;
a database for storing measured signal limit values set in advance;
an external input interface for fetching measured signals from the control target;
a measured signal database for storing the values of the fetched measured signals; and
a function for determining an initial value for the target model output value by using limit values for the measured signals and at least one of an average, a maximum value, and a minimum value that are calculated from the measured signals stored in the measured signal database;
wherein the external input interface fetches at least one of a carbon monoxide concentration or a nitrogen oxide concentration out of measured signals in a thermal power generation plant; an environment limit value of at least one of the carbon monoxide concentrations or the nitrogen oxide concentrations is stored in the database for storing the limit values for the measured signals as the measured signal limit value; the function for determining an initial value of the target model output value determines an initial value of the target model output value of the at least one of the carbon monoxide concentrations and the nitrogen oxide concentrations; the learning function learns a method for generating a model input that satisfies the initial value; the function for determining an operation signal generates an operation signal for at least an opening of an air damper according to a result of the learning.
12. The thermal power plant controlling device according to claim 11,
wherein in the controlling device, the function for decreasing or increasing the target model output value when the model output satisfies the target model output value determines a modified target model output value obtained by decreasing or increasing the target model output value of the nitrogen oxide; the learning function learns a method of generating a model input that satisfies the modified target model output value.
13. A plant control method for generating an operation signal so that the value of a measured signal satisfies a target operation value for a plant, which is a control target, the measured signal being obtained when the operation signal is given to the control target, the plant controlling method comprising steps of:
predicting the value of a measured signal obtained when an operation signal is given to the control target by using a model which predicts the value of the measured signal obtained when the operation signal is given to the control target;
determining a target model output value by using at least one of an average, a maximum value, or a minimum value of measured signals for the control target as well as a measured signal limit value set in advance;
learning a method of generating a model input to be given to the model so that a model output, which is a prediction result yielded by the model, satisfies the target model output value; and
determining an operation signal to be given to the control target according to a result of the learning.
14. The plant control method according to claim 13,
wherein when the model output satisfies the target model output value in the learning a method of generating a model input, the target model output value is decreased or increased so that the decreased or increased target model output value is attained.
15. The plant control method according to claim 13, wherein the target model output value is calculated by subtracting the average of the measured signals from the maximum value of the measured signals and further subtracting the absolute value of the subtraction result from the measured signal limit value.
16. The plant control method according to claim 14, wherein the initial value of the target model output value is calculated by subtracting the average of the measured signals from the maximum value of the measured signals and further subtracting the absolute value of the subtraction result from the measured signal limit value.
17. The plant control method according to claim 13, wherein when the model output satisfies the target model output value and then a positive or negative evaluated value is calculated to learn the method of generating a model input, an operation method in which an expected value of the evaluated value is maximized or minimized is learned.
18. The plant control method according to claim 14, wherein when the model output satisfies the target model output value and then a positive or negative evaluated value is calculated to learn the method of generating a model input, an operation method in which an expected value of the evaluated value is maximized or minimized is learned.
19. A thermal power plant control method in which the plant control method according to claim 13 is applied, the control method comprising the steps of:
setting an environment limit value of at least one of carbon monoxide and nitrogen oxide out of the measured signals as a limit value;
determining an initial value of the target model output value by using at least one of an average, a maximum value, or a minimum value of the measured signals, for which the limit value is set, and the limit value;
learning a method of generating a model input so that the initial value is attained, and
generating an operation signal for at least an opening of an air damper according to a result of the learning.