JP4577232B2 - Power plant operation plan creation device and method - Google Patents

Description

  The present invention creates a power plant operation plan such as a thermal power plant, a pumped storage power plant, etc., and creates a start / stop plan for a thermal power plant that becomes a combination problem, thereby providing a balance between supply and demand, reserve power, fuel consumption constraints, The present invention relates to a method and apparatus for creating a power plant operation plan that satisfies constraints such as dam water level constraints and tidal current constraints and minimizes power generation costs.

  In order to maintain the reliability of the power system, it is necessary to create a start-up / shutdown plan for the generator that ensures reserve power while matching the power demand with the supply capacity of the generator. However, since the predicted power demand is used in the planning stage, it involves a prediction error. In order to perform economic operation at the same time as reliability, it is necessary to create a start-up / stop plan for the generator so that the power generation cost is minimized in consideration of this prediction error. As for the power plant operation plan problem, the thermal power plant start / stop plan is a combination problem, and the generator output is a nonlinear programming problem. As described above, it is a nonlinear mixed integer programming problem, and at the same time, considering the number of generators and the number of planning points, the problem is very large, and therefore it is difficult to optimize in practice. For this reason, a plan corresponding to each of various demand pattern scenarios is created as in JP-A-2004-274956, and the cost distribution for each scenario is calculated. In Japanese Patent Laid-Open No. 2005-12912, the number of operating units is determined in consideration of a demand error for generators having the same characteristics.

Japanese Patent Laid-Open No. 2004-274958 JP 2005-12912 A

Since the thermal power plant startup / shutdown plan is a combination optimization problem, for example, the total number of startup / shutdowns for 24 hours with 10 thermal power generators is 10 to the 72nd power. Even if one plan can be evaluated in 1 microsecond, it takes 10 59 years to evaluate all plans, and it is impossible to find the optimal solution by checking all combinations in practice. It is. For this reason, it is virtually impossible to determine the optimum generator output of the thermal power plant and the pumped-storage power plant at the same time as creating the startup / shutdown plan of this thermal power plant. Therefore, the problem of combined explosion can be avoided by relaxing the start / stop planning problem of a thermal power generator from a combination problem to a problem of real variables and solving it using a quadratic programming method and a linear programming method. By relaxing to the real number problem in this way, it is possible to obtain an optimal solution while simultaneously taking into consideration constraints that can be expressed by linear constraints such as fuel consumption constraints, power flow constraints, or dam water level constraints. However, there arises a problem that an uncertain state (for example, 0.3) in which the start / stop variable of the thermal power generator cannot be determined to start (1) or stop (0) occurs. For this reason, it is possible to start by correcting the objective function and constraint conditions so that the larger the start / stop variable value and generator output obtained during the repeated convergence calculation, the easier it is to start and the smaller it is, the easier it is to stop. The value of the stop variable can be confirmed to start or stop. Furthermore, since the power demand to be used uses a predicted value, there is an error from the actual demand. This error can estimate how much error distribution is based on past demand prediction results and actual demand. Since this demand error always occurs, it is necessary to prepare an operation plan for the power plant taking this into account. By formulating a problem for multiple demands and using quadratic programming or linear programming, it is possible to determine the values of startup and shutdown variables of a thermal power plant and at the same time determine the output to the optimal thermal generator or pumped-storage generator .

  In Japanese Patent Application Laid-Open No. 2004-274956, since a plan is created for each demand, an average cost for the average demand is obtained. However, considering the demand forecast error, the larger the demand, the larger the power generation cost, and the expected value of the power generation cost shifts to the larger one than the average power generation cost. Not done. Japanese Patent Application Laid-Open No. 2005-12912 targets generators having the same characteristics, but the characteristics of thermal power generators operated in the power system can be appropriately adapted to demand fluctuations, for example, base thermal power, middle thermal power , Since generators with different characteristics such as peak thermal power are introduced, the method of controlling the number of generators with the same characteristics cannot minimize power generation costs.

  The present invention has been made in response to the above points, and its objective is to consider not only generator operation constraints, generator characteristics, fuel consumption constraints, pumping dam water level constraints, but also power demand prediction errors. It is an object of the present invention to provide a power plant operation plan creation method and apparatus that can minimize power generation costs.

  According to the main feature of the present invention, by inputting a plurality of demand curves based on the prediction error and relaxing the start / stop variable of the thermal power generator to a real variable, one start / stop plan problem and each demand Applying quadratic programming or linear programming to load distribution planning problems as real variable problems, and taking into account fuel consumption constraints, pumping dam water level constraints, etc., and optimal power plant operation plan creation method and equipment minimize power generation costs Start / stop plans and load distribution plans can be created.

  According to the present invention, even if a power demand error occurs, a start / stop plan and a load distribution plan that can reduce power generation costs in consideration of fuel consumption constraints, pumping dam water level constraints, generator operation constraints, and the like. Can be created.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a calculation processing flow of a power plant operation planning method to which the first embodiment of the present invention is applied, FIG. 2 is a schematic overall configuration diagram of a power plant supply and demand operation plan creation device 1, and FIG. The detailed block diagram of an apparatus is shown.

  The power plant supply and demand operation plan creation device 1 includes a central processing unit (CPU) 2, a main storage device 3, an input / output device 4 and an external storage device 5.

  FIG. 3 is a detailed functional configuration diagram of the power plant supply and demand operation plan creation apparatus according to the present invention. The power plant supply and demand operation plan creation device 1 includes the input device 6, the display device 7, the database 9, the reading device 10, and the operation plan creation processing unit 20. The operation plan creation processing unit 20 is realized by the CPU 2 executing a program that is stored in advance in the storage medium of the external storage device 5 and read into the main storage device 3 via the reading device 10. The present invention is not limited to such a programmed general purpose processor. For example, the operation plan creation processing unit 20 can be configured by a combination with a specific hardware device including a wired logic that executes each processing of the present invention.

The input / output device 4 includes an input device 6 having a keyboard and a mouse shown in FIG. 3 and a display device 7 as an output device. The input / output device 4 may be provided with an input device such as a pointing device or a touch sensor, or an output device such as a liquid crystal display device, a printer, or a speaker instead of or in combination with these. As the external storage device 5, a hard disk device, an FD device, a CD-ROM (compact disc-read only memory) device, a DAT (digital videotape) device, a RAM (randam access memory) device, a DVD
A (digital video disc) device, a non-volatile memory, or the like can be used. The external storage device 5 includes a mass storage device for holding the database 9 shown in FIG. 3, a storage medium for holding a processing program, and a reading device 10 for reading information held in the storage medium. Although used, both the database and the processing program can be held in one external storage device. As the storage medium, FD, CD-ROM, magnetic tape, optical disk, magneto-optical disk, DAT, RAM, DVD, nonvolatile memory, and the like can be used.

The input device 6 accepts selection of options displayed on the display device 7, input of data, and the like, and transmits them to the operation plan creation processing unit 20. The display device 7 displays the data sent from the input device 6. The operation plan creation processing unit 20 generates the power plant based on the data transmitted from the input device 6, the data read from the database 9, the processing program read from the reading device 10, and the data transmitted from the power system 11. Create a supply and demand plan. The power system 11 includes a database (not shown). The power system 11 monitors and controls the power system 12.

  The processing result of the operation plan creation processing unit 20 is sent to the display device 7 for display and stored in the database 9. In addition, when an operation plan creation under the conditions set by the operation / planning system and control system of the power system 11 is requested, the plan and evaluation result created by the operation plan creation processing unit 20 are also notified to the power system 11. Is done. Upon receiving this notification, the power system 11 outputs an output control signal of a generator, which is one of the supply powers, to the power system 12 based on the notified plan, and controls the generator. Data is fetched, and the fetched data and data created in a planning system (not shown) are stored in an internal database (not shown).

  The operation plan creation processing unit 20 includes a control unit 21, a plan creation condition setting unit 22, a data reading unit 23, a formulation unit 24, a plan calculation unit 25, a start / stop variable upper / lower limit modification unit 26, an objective function modification unit 27, and a calculation. A result processing unit 28 is provided. In addition, the operation plan creation processing unit 20 is connected to an external power system 11 via a communication line 31, and the power system 11 is connected to a power system 12 that is an actual transmission and substation facility. The power system 11 includes a system for planning / operation and control of the power system 12, a power system 12 and a database (not shown) for holding information indicating the state of the power system 12, and the like. The state of the power system 12 is detected by a relay, a sensor, or the like, notified to the power system 11 via the communication line 32, and stored in a database (not shown) of the power system 11.

  The control unit 21 processes and processes data for smoothly transmitting and receiving data and processing programs between the power system 11 and each of the processing units 22 to 28, and controls the transmission and reception of the entire system. Make the process work properly.

  The plan creation condition setting unit 22 reads and displays the default conditions for creating the operation plan, which are held in the storage medium of the database 9 and / or the reading device 10 via the control unit 21, and displays these conditions. The condition is displayed on the display device 7 to change the condition. Further, the changed new condition is stored in the database 9 via the control unit 21.

  The data reading unit 23 reads data held in the database 9 via the control unit 21 and transmits these data to the processing units 24 to 28 via the control unit 21. In this embodiment, data is read from the database 9 through the data reading unit 23 unless otherwise specified.

  The formulation unit 24 performs preprocessing and formulation for calculation by the plan calculation unit 25 based on the conditions created by the plan creation condition setting unit 22 and the data from the data reading unit 23 via the control unit 21. carry out.

  The plan calculation unit 25 is a condition created by the plan creation condition setting unit 22 via the control unit 21, or the constraint condition, objective function and data reading unit modified by the start / stop variable upper / lower limit modification unit 26 and the objective function modification unit 27. The calculation processing of the power plant operation plan is executed by the data from 23 or the pre-processing and formulation created by the formulation unit 24.

  The start / stop variable upper / lower limit correction unit 26 repeatedly calculates the upper / lower limit constraint values for the start / stop variable when creating a new plan by repeatedly calculating based on the operation plan created by the plan calculation unit 25 via the control unit 21. Correct it.

  The objective function correction unit 27 repeatedly calculates based on the operation plan created by the plan calculation unit 25 via the control unit 21, and corrects and sets the objective function when creating a new plan.

  The calculation result processing unit 28 stores the plan creation conditions and data set and calculated by each of the processing units 22 to 27, the created operation plan, the transition of the objective function, information for supporting data input from the input device 6, and the like. Is displayed on the display device 7.

  Next, the operation will be described with reference to the processing flowchart shown in FIG.

  In setting the plan creation conditions in step S101, the plan creation condition setting unit 22 reads default plan regeneration conditions from the database 9, displays them on the display device 7, and changes the conditions via the input device 6. The conditions set here include a plurality of power demand prediction curves and their weighting factors, a demand increase time zone, a demand decrease time zone, and the number of repeated calculations. FIG. 4 shows an example of a screen for setting these values. The set value is displayed in a graph. Other items to be set include reserve capacity, consumption restrictions such as LNG, water level restrictions for pumping dams, system configuration, power flow restriction values for transmission lines, and the like. In the plan creation period, power demand forecast data for 24 hours per hour is set here. The demand forecast data is a curve 0 that is predicted by a normal method, curves 1 to 4 are set based on the distribution of past prediction errors, and the probability is set as a weighting factor. The reserve capacity is set based on the demand curve 0. Regarding the fuel consumption restriction, the amount consumed by the final time of the planning period and the upper and lower limits of the fuel consumption amount at each time are set as necessary. For the pumping dam water level, the initial water level, the final water level, and the upper and lower water level at each time are set. Regarding the system configuration, the connection state between the transmission line at each time, the power generation equipment, and the load is set, and the transmission line and reserve capacity at each time are set.

  In step S102, the characteristics of supply power of the generator and the operation restrictions are read from the database 9. Among the supply power, there are thermal generator characteristics such as output upper and lower limits, fuel cost characteristics (secondary function and linear function for output), start-up costs and generator sets that cannot be started simultaneously. The fuel type used by each generator is also read from the database. For pumped storage power plants, there are upper and lower limits and pumping efficiency during power generation and pump load.

  In process S103, formulation is performed using an objective function and constraint conditions. Here, the general formulation will be described first, then the formulation when considering a plurality of demands, and finally the formulation used in the present invention.

The objective function TC in the general formulation is Equation (1). This equation is for a single demand curve. The start / stop variable indicates the state of the generator i and the time t with u _{it. When the} variable is 0, it is stopped and when it is 1, the operation is stopped. The fuel cost function F _i (P _it ) is a quadratic function of the generator output P _it . The start-up cost SUC _i is incurred when stopping at the minimum demand time n and operating at the maximum demand time p. Therefore, the start / stop variables u _in and u _ip of the minimum demand time n and the maximum demand time p are used. A function excluding a constant term in the fuel cost function is defined as f _i (P _it ).

Equation (2) shows the output upper and lower limits of the thermal power generator, the pumped power generation of the pumped storage power plant, and the output of the pump. Since the start-stop variable u _it thermal generator is 0 or 1, becomes 0 both the output on the lower limit of the thermal power machine when 0, P _i is set to _1, the _min P _i, and _max.

Formula (3) is a formula for supply and demand balance. Demand of the time t is D _t.

Equation (4) is a reserve force constraint. The reserve force required at time t is R _t . Here, the reserve capacity of the pumped storage power plant is considered, but it may be only thermal power.

  Equation (5) shows the same central simultaneous prohibition constraint. Older control devices take into account that when starting two generators, only one can be started per day. Equation (5) shows an example when the thermal power generator i and the thermal power generator (i + 1) have the same central constraint.

  Expression (6) is a constraint that the total power generation amount LNG of the generator with LNG as the fuel is within the upper and lower limit range even in the thermal power generator.

Equation (7) shows the water level constraint of the pumping dam. η indicates the pumping efficiency. The dam water level WL _t converted to the power generation amount is a constraint that the dam water level is within the upper and lower limits of the dam water level.

  It is common to create a power plant start / stop plan based on the above objective function and constraints, and then create a load distribution plan based on this start / stop plan.

Next, a case ^where there are a plurality of demand forecast curves D _t ^k will be described. Equation (8) is the objective function. This is the sum of the expected power generation costs for each demand curve. Equation (1) is multiplied by a weighting factor α ^k corresponding to the demand occurrence probability. At this time, the sum of the weighting factors α ^k is 1 as shown in equation (9). In equation (8), the thermal power generator output is P _it ^k, and it can be seen that the output varies with the demand curve k even at the same generator and the same time. On the other hand, _it can be seen that the start / stop variable does not depend on u _it and the demand curve k. That is, if a curve that takes into account a demand prediction error is used for one start / stop plan, the output of the generator differs in each demand curve, and the power generation cost changes. For this reason, the expected value is calculated using the probability of occurrence of the demand curve as a weighting factor, and a plan that minimizes this is created.

As shown in equation (10), the supply-demand balance constraints need to hold each demand curve D _t ^k.

Equation (11) shows the reserve power constraint. Here, D ⁰ _t contemplates reserve only when the reference demand curve. Here, the demand curve 0 is used as a reference demand curve.

  For the constraints of Equation (5), Equation (6), and Equation (7), the generator output at the time of the reference curve is used.

Finally, the formulation of the present invention will be described. In the present invention, the objective function of Expression (12) is adopted. For the original equation (8), β and q, r are introduced as an example in order to converge the start / stop variables. In order to converge the start / stop variable, the objective function or the constraint condition may be modified so that the start / stop variable close to 0 is close to 0 and that close to 1 is close to 1. Here, the reason for correcting only the constant term part in the fuel cost function is that it has a direct influence on the start / stop variable and that the linearity of the generator output and the second order term maintain the optimal load distribution. This is to maintain the condition of equal λ distribution. Further, the latter q and r are each for approaching 1 or approaching 0. Here, the constants used are set on the screen of FIG. The tabular items are set directly. Also, either “Correction of objective function coefficient” or “Correction of constraint” is selected. It is assumed that this selection is performed at the time of processing S101. When the former “Correction of coefficient of objective function” is selected, the coefficient of the objective function of Expression (12) is corrected by the value of the start / stop variable u _it obtained during the repeated calculation. When the latter “correction of constraint” is selected, the constraint of equation (14) that appears later is corrected and the coefficient of the objective function of equation (12) is also corrected.

  The coefficient β shown in FIG. 5 is used in equation (13). The values of a, b, c, d, e, and f in FIG. 5 are set in order to converge the start / stop variables. When the start / stop variable is close to 0, the value is 0. It shall be set so that it approaches.

  In equation (14), the start / stop variable is 0 or 1, but it is relaxed to a real variable from 0 to 1 in order to formulate it by a quadratic programming method.

Finally, equation (15) is set in order to maintain increased demand time slot of FIG. 4, the temporal continuity of u _it was relaxed to real variables by using the lower demand times. That is, it is to prevent repeated start and stop every hour. For example, when setting is made as shown in FIG. 4, the start and stop are each performed once a day at most, and can be the same as the actual operation. However, although it is rare, a small-scale gas turbine or the like may start and stop twice a day.

  For example, if the constraint condition of Expression (15) is set for the demand curve 0 in FIG. 4, the start / stop variable does not decrease during the demand increase time period, and the start / stop variable does not increase during the demand decrease time period. Further, once the generator is stopped, the minimum continuous stop time needs to be continuously stopped. Similarly, once activated, the minimum continuous operation time must be continuously operated. Normally, the change in the start / stop variable is set to zero between the time when the demand is high and the minimum continuous operation time, centering on the time of the maximum demand, and the time of the minimum continuous stop time from the time when the demand is low, centering on the time of the minimum demand. During this time, the change in the start / stop variable is set to zero. As a result, the final start / stop variable becomes 0 or 1, but since this start / stop variable is relaxed to a real variable, the start / stop variable is as shown in FIG. 5-1, depending on the generator. ing.

  4 and 5 can be individually set by an operator or the like by the input device 6.

  The above constraints are added and formulated. The first iterative calculation is the processing S103.

  In the process S104, the plan calculation unit 25 uses the quadratic programming method and the linear programming method, and the objective function and the constraint conditions set in the process S103, the process S107, and the process S108. , The optimum solution of the pumped generator output is obtained simultaneously. However, the start / stop variable of the thermal power generator does not necessarily converge to 0 or 1. For this reason, by repeating the processing S107 and the processing S108, all the start / stop variables are fixed to the stop 0 or the operation 1. An error message is displayed when a plan that satisfies the constraint conditions cannot be created.

  In process S105, the calculation result processing unit 28 displays the calculation result in process S104 on the display device 7. The calculation result is stored in the database 9. The stored items include thermal generator start / stop variables, thermal power and pumped-storage generator output, power generation cost, fuel cost, startup cost, constraints used, objective function, and the like. Examples of screen display are shown in FIGS. FIG. 6 shows the values of the start / stop variables. The horizontal axis direction is the time axis. The vertical axis direction is the unit number of the thermal power generator. The numerical values in the table indicate the start / stop variables of the thermal power generator at the target time. In addition to stop 0 or operation 1, there are some that have not been confirmed to start or stop, such as 0.6. In addition, the fixed rate at which start / stop is fixed for the same unit is displayed. For example, although the determination rate at 1 o'clock is 80%, the start / stop variable of 8 units among the 10 units is 0 or 1. Similarly, the fixed rate of starting and stopping at each time is also displayed. At the top of the table, the overall start / stop decision rate of 78.4% is displayed. When start / stop is confirmed, the confirmation rate becomes close to 100%. Normally, it is often impossible to determine the start / stop of one unit at the same time. FIG. 7 shows the output of the thermal power generator when the start / stop variable is that shown in FIG. Similar to FIG. 6, the horizontal axis represents time, and the vertical axis represents the number of the thermal power unit. This output may also be smaller than the output lower limit constraint of the original thermal power unit.

  In process S106, the plan calculation unit 25 checks whether the start / stop variables of all the thermal power generators have converged to stop 0 or start 1. If all the start / stop variables have converged to 0 or 1, it means that a start / stop plan that satisfies all the constraint conditions has been created, and the process proceeds to step S109. Otherwise, the process proceeds to process S113. First, the case where the processing proceeds to step S113 will be described.

In the process S113, the repeated calculation by the mathematical programming method is counted up. When the number of repetitions exceeds the number set in FIG. 4, in step S107 and step S108, the start / stop is forcibly confirmed using the conditions set in FIG. That is, all u _it satisfying the condition of (4) in FIG. 5 is stopped (0), and other u _it is set to operation (1). Thereby, when it comes to determination process S106 next, it will progress to process S109 of an end direction. When the number of repetitions has not been reached, the constraints set using the conditions set in FIG. 5 and the objective function of equation (12), the constraints of equations (14), (15), and (2) to (7) are used. Correct the condition and objective function. That is, in the process S107, the start / stop variable upper / lower limit correction unit 26 corrects the upper / lower limit constraint of the start / stop variable according to the setting of FIG. In step S108, the objective function correcting unit 27 corrects the objective function according to the setting shown in FIG.

  The constraint conditions and the objective function are corrected by the above processing S107 and processing S108. Based on this corrected result, a plan is created again in step S104. By creating a repetitive plan along this loop, the start / stop variable is converged to stop 0 or start 1.

  If it is determined in the process S106 that all the start / stop variables are 0 or 1, the process proceeds to the process S109.

  Thus, the start / stop variable can be determined to be 0 or 1. Therefore, β, q, and r were introduced in the objective function equation (12) in order to converge the start / stop variable to 0 or 1, but since the original purpose was achieved, the processing was performed to obtain the original objective function. In S109, β = 1, q = 0, and r = 0 are set in the objective function equation (12). Further, the upper and lower limits of the constraint condition expression (14) are changed to 0 or 1. Alternatively, you can stop treating it as a variable and treat it as a constant.

  Based on the objective function and constraints set in step S109, the plan calculation unit 25 is used to satisfy the constraints by mathematical programming such as quadratic programming in step S110, and optimization determines the generator output. .

  Finally, the calculation result processing unit 28 is used to display the calculation result of the process S111 on the display device 7 or output it to the power system 11. FIG. 8 to FIG. 14 show examples of calculation result screen display. FIGS. 8 and 9 are of the same format as FIGS. 6 and 7, and display values when the start / stop variables converge. In FIG. 8, the 0, 1 determination rate is 100%, and it can be confirmed that the start / stop of all the thermal power generators is fixed to 0 or 1. In FIG. 9, when the generator is operating, the range is from the minimum output to the maximum output. FIG. 10 is a screen for confirming the progress of repeated calculations. Click the time button and enter the time you want to increase or decrease, or click on “Display”, and click “Display” to see how it has changed due to repeated calculation of the start / stop variables of all thermal power units at the time selected below. Display as a bar graph. The unit that is black is finally in operation (1), and the height of the bar graph indicates the value of the start / stop variable. The one with the white bar graph indicates that it has finally stopped (0). FIG. 11 shows the transition of power generation cost for each demand curve in each repetitive calculation. The thick line shows the power generation cost when the standard demand curve is shown. FIG. 12 shows the transition of the fixed rate in which the start / stop variable is fixed to 0 or 1 when all the thermal power units and all times are subjected to each repetition calculation. In this example, it can be seen that the values are fixed to 0 and 1 at the fifth time. FIG. 13 shows the power generation cost for each hour of the final result. Similarly to FIG. 10, the power generation cost at the set time can be displayed by setting the time and clicking “Display”. The power generation cost displays a bar graph and a table of power generation cost for each demand curve. Moreover, the bar graph of weighted cost distribution when the probability of a demand curve is considered is shown. The table shows the weighted power generation costs for each demand curve, and the total is the expected cost at that time. FIG. 14 is obtained by adding the power generation costs for each hour in FIG. 13 to all the times in the planning target period. The power generation cost in the table on the lower right is the expected cost for the entire project. The breakdown is fuel cost and startup cost.

  Finally, in process S110, these calculation results are stored in the database 9. The stored items are start / stop variables, generator output, power generation cost, fuel cost, start-up cost, and the like.

  According to the embodiment of the present invention, even when there is a demand prediction error, the generation probability of the demand is set as a weighting factor in the power generation cost for each demand, and the objective function for minimizing the sum of the products of both is set. In addition, the start and stop variables of thermal power generators, which are 0 and 1 variables, are relaxed to real variables, and time change constraints of start and stop variables that take into account changes in the demand for power demand prediction as a reference are introduced. It is possible to create a full-time power plant plan that minimizes the power generation cost considering the pumping dam water level constraint.

The second embodiment is a method for taking into consideration that the efficiency of the fuel cost function of the generator varies with temperature or the like. For example, when the thermal power generator is a gas turbine, the efficiency decreases when the temperature rises, and the efficiency improves when the temperature is low. In addition, when the temperature rises in summer, the demand for electric power increases due to an increase in cooling demand. Conversely, in winter, when the temperature rises, the demand for heating decreases and the demand for electric power decreases. Thus, the fuel consumption characteristics and power demand of the thermal power generator change depending on the temperature. For this reason, it is necessary to minimize the power generation cost in consideration of changes in the fuel consumption characteristics and the predicted demand of the thermal power generator for each predicted temperature based on the probability distribution of the predicted temperature. In the first embodiment, there are a plurality of demands and the generator characteristics are fixed, but the second embodiment is an example in which both the demand and the generator characteristics change stochastically with the temperature. Also in this case, an optimum start / stop plan and load distribution plan can be created by processing in the same manner as in the first embodiment. An objective function and constraint conditions can be set. However, it is possible to create optimum start / stop plans and load distribution plans by the same process by setting different coefficients of the fuel cost function of the objective function and setting a weight coefficient for each fuel cost function. Differences from the first embodiment will be described below. In process S101, the setting of the next plan creation condition is newly added. Enter the probability distribution information of the expected temperature. Next, in process S102, the relationship between the temperature and the fuel cost characteristic of the generator is read. Furthermore, the fuel cost characteristic with respect to the expected temperature is determined. Further, in step S103, an objective function is set using the probability distribution of the predicted temperature and the probability distribution of the fuel temperature characteristic of the predicted temperature using the probability distribution of the predicted temperature. The objective function in the first embodiment is expressed by equation (8), whereas the objective function in the second embodiment is expressed by equation (16). In the objective function of the second embodiment, the difference in the predicted temperature is represented by a superscript k of a variable or function, and the superscript k is included in the fuel cost function f _i ^k (P). This is different from the first embodiment.

  Therefore, the formulas (9), (10), (11), (13), (14), and (15) that do not include the fuel cost function are the same in the second embodiment. It may be the same as one embodiment. Further, since the objective function formula (12) used for convergence includes the fuel cost function, the formula (17) is obtained in the second embodiment.

Modify the objective function as described above, by repeatedly calculated as in the first embodiment, satisfy the set constraints, a start-stop variable u _it for each generator can be converged to 0 or 1.

  By the above method, it is possible to create a power plant operation plan that can minimize the power generation cost in consideration of the probability distribution of the predicted temperature and the change probability of the fuel cost function of the generator.

Process flow for creating a power plant operation plan. Overall configuration of power plant operation plan creation device. Detailed configuration of the power plant operation plan creation device. An example of a setting screen such as a power demand curve. Example of a screen for modifying objective functions and constraints. The example of a graph of the time change of a start stop variable. An example of a screen displaying start / stop variables. An example of a screen displaying the generator output. An example of a screen displaying start / stop variables. An example of a screen displaying the generator output. An example of a screen that displays the transition of start / stop variables. The example of the screen which displays transition of the power generation cost of each demand curve. The example of the screen which displays the transition of the fixed rate of the start / stop variable. The example of the screen which displays the power generation cost for every hour of the created plan. An example of a screen that displays the total cost of power generation for the created plan.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Power station supply and demand operation plan preparation device, 2 ... Central processing unit CPU, 3 ... Main storage device, 4 ... Input / output device, 5 ... External storage device, 6 ... Input device, 7 ... Display device, 8 ... Printing Device: 9 ... Database 10 ... Reading device 11 ... Power system 12 ... Power system 20 ... Operation plan creation processing unit 21 ... Control unit 22 ... Plan creation condition setting unit 23 ... Data reading unit
24 ... Formulation unit, 25 ... Plan calculation unit, 26 ... Start / stop variable upper / lower limit correction unit, 27 ... Objective function correction unit, 28 ... Calculation result processing unit.

Claims (10)

Means for storing demand prediction at two or more same times and a weighting factor corresponding to the demand forecast occurrence probability in an accepting storage device;
In the power plant operation plan creation device having means for setting an objective function with a demand coefficient corresponding to the demand prediction occurrence probability and the demand prediction at the two or more same times stored in the storage device,
For each demand, the start / stop plan and load distribution determined through the calculation related to the generator start-up combination problem including the predetermined generator relaxed as a real variable from 0 to 1 and satisfying the supply balance constraint Means for storing the weighting factor of the power generation cost at the time in the receiving storage device;
A power plant operation comprising: means for multiplying the power generation cost for each demand by a weighting factor of the power generation cost with respect to the demand as the objective function, and performing a power plant operation plan based on the objective function Plan creation device. In claim 1,
An apparatus for creating a power plant operation plan, comprising means for optimizing a start / stop plan and a load distribution plan using a mathematical programming method for the objective function. In claim 1,
An apparatus for creating a power plant operation plan, comprising means for receiving a demand increase time zone or a demand decrease time zone in a storage device. The power plant operation plan creation device according to claim 1, further comprising means for receiving and storing in a storage device time constraints of start / stop variables in a demand increase time zone and a demand decrease time zone. In claim 1,
An apparatus for creating a power plant operation plan, comprising means for correcting an upper limit / lower limit constraint value of an objective function or a start / stop variable based on a value of a start / stop variable or a generator output of each generator. In claim 1,
Reserve, the same central simultaneous start prohibition constraints or power plant operation plan creation device, characterized in that you stored in a storage device accepting at least one constraint of fuel consumption restrictions. In claim 1,
Objective function coefficient, objective function correction function, start / stop variable value, generator output value, start / stop decision rate, transition of objective function coefficient with respect to the number of repetitions, transition with respect to the number of repetitions of the start / stop variable, generator A means for outputting and displaying at least one of a transition with respect to the number of repetitions of output, a transition with respect to the number of repetitions of the start / stop fixed rate, a transition with respect to the number of repetitions of fuel consumption, and a transition with respect to the number of repetitions of the dam water level; This is a power plant operation plan creation device. In claim 1,
Means for accepting and storing the probability distribution of the expected temperature in the receiving storage device;
Means for receiving and storing the relationship between the temperature and the fuel characteristics of the generator in a storage device;
Means for creating a fuel cost characteristic for the expected temperature and storing it in a storage device;
An apparatus for creating a power plant operation plan, comprising means for creating an objective function reflecting the fuel cost characteristic with respect to the predicted temperature. Two or more demand forecasts at the same time, and a weighting coefficient corresponding to the demand forecast occurrence probability is stored in an accepting storage device;
In the method for creating a power plant operation plan, comprising the step of setting an objective function by means of a weighting coefficient corresponding to the demand prediction occurrence probability and the demand prediction at the two or more same times stored in the storage device,
For each demand, the start / stop plan and load distribution determined through the calculation related to the generator start-up combination problem including the predetermined generator relaxed as a real variable from 0 to 1 and satisfying the supply balance constraint Accepting and storing the weighting factor of the power generation cost when
Power plant operation, characterized in that a step of performing a power plant operation plan on the basis of a multiplied by the weighting factor of the power generation cost for demand generation cost for each of the demand to the set objective function, the objective function How to create a plan. In claim 9,
A method for creating a power plant operation plan, comprising: a step of optimizing a start / stop plan and a load distribution plan using a mathematical programming method for the objective function.

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