Operation Management bookmark0 Yitaipu Hydropower Station Hydrogenerator Unit Optimized Dispatch A. Alsace and other identical 700MW hydroelectric generating units. A dynamic programming model has been developed to optimize the total number of generating units operating per hour per day to obtain a total power generation schedule for the plant to operate in the most economical manner. The model emphasizes the coordination between the start and stop of the generator set and the hydropower efficiency, taking into account changes in the tail water level, the loss of the pressure pipe head and the efficiency of the hydroelectric generating unit. The method has been tested on a typical power generation schedule. The results show that the number of hydro-generator units dispatched has an important impact on the efficiency of the entire power station. Therefore, it is a key issue to be considered in the scheduling of hydro-generator units. .
Key words: hydroelectric generating unit operation; turbine efficiency; optimized dispatching; Itaipu hydropower station has caused extensive research on the operation of thermal power units in the past few decades due to the high cost of starting and stopping of thermal power units and many operational restrictions. traitor.
On the other hand, although the start and stop of the hydropower unit is also necessary, the operation of the hydropower unit is rarely noticed. This unequal treatment may be due to the low start-stop costs of hydropower units and the limited operational constraints.
Nilsson submitted an important study on the cost of hydropower start-ups estimated by the Swedish power company. Many factors affect unit start-up costs, but the two most important factors are maintenance costs and reduced unit operating life. It has long been known that the maintenance cost of a generator set is greatly affected by the number of starts of the unit. It is estimated that each time the unit is stopped, the unit with a reduced operating life of 10 to 15 hours and 150 times per year will have a 20% reduction in operating life. Therefore, after long-term observation and analysis, it is found that the starting cost is more important, and it is necessary to study in more detail. Operation problems of the water turbine unit.
This paper studies the optimal scheduling of the generator set of Itaipu Hydropower Station. The plant is the largest hydropower station in operation in the world with an installed capacity of 12.6 GW, shared by Brazil and Paraguay. In 1999, the power generation accounted for 24% and 93% of the power generation of the two countries. The power generation time of the power station from morning to night often changed greatly, requiring the hydropower units to start and stop frequently.
In order to consider the hydropower efficiency in the scheduling model, it is recommended to calculate the power generation loss function, which takes into account the influence of the tail water elevation and the head loss of the pressure pipe on the net head of the hydropower station. On the contrary, the water balance equation is not considered because the water level in the front pool does not change much within 1 h. These model features greatly simplify the problem and its computational techniques compared to other technologies.
1 Hydropower generation efficiency The output of a unit can be expressed by the following formula: P water density is kg*m*3); n* turbine efficiency/%; \* generator efficiency/effective head is determined by the following formula: hp pressure pipe head loss /m. From these equations, the unit output power is related to many variables. The most important variable is the flow rate, while the hydropower efficiency is usually expressed as the output/input ratio, so that the result is related to the effective head, turbine efficiency and generator efficiency. Variety.
One way to express hydroelectric efficiency is to calculate hydropower losses caused by effective head reduction and reduced turbine generator efficiency. In order to represent the power generation efficiency in the power generation loss function, the influence of each variable on the power generation must be ascertained.
11 The water level in the front pool has played a major role in the medium and long-term operation planning of the hydropower system. In the planning period of 1a or many years planned in weeks (or months), it is necessary to optimize the management of reservoir water storage.
In the short-term (one-week) plan in hours, it was observed that the water level in the foreshore was very small, especially for large reservoirs such as Itaipu (19km3) and, in the case considered here, within the planning period of 1d The water level change in the front pool is completely negligible.
The 12 water level is opposite. Due to the change of the total flow of the power station, the tail water level will change greatly in the short term. For some hydropower stations, the tail water level also depends on the water level of the front pool adjacent to the downstream power station. For Itaipu, the tailwater level depends on the flow of the Iguazu River, the main tributary to the Paran River, 24 km downstream. Itaipu's tail water level can be expressed by a special 4th degree polynomial function (). When the number of operating units is constant, the total flow of the power station is increased, and the output power is also increased in terms of power generation efficiency trend. However, due to the elevation of the tail water level, the effective water head is correspondingly reduced, and the increase in power output is relatively small.
The power loss caused by the increase in the tail water level can be calculated by the following formula: the total flow rate when the unit is running.
Since the units of the Itaipu power station are the same, the total flow of the power station will be evenly distributed to each unit in operation to minimize the total power loss function, ie qn=n*q. However, when the units are not identical, The total discharge capacity of the power station can be distributed among the units using conventional economic dispatching algorithms. This method is similar to the algorithm used in thermal power plants.
13 pressure pipe head loss pressure pipe head loss is related to the friction of water on the pressure pipe, is a quadratic function of the flow, hP = kq2, k is a constant indicating the characteristics of the pressure pipe (2 / m5) can be used to press the pipe head Loss (m) is converted to pressure pipe work 14 Turbine and generator efficiency Turbine efficiency is the ratio of the generated mechanical energy to the potential energy of water. Similarly, generator efficiency is the ratio of electrical energy produced to mechanical energy. Turbine efficiency is often expressed as a function of effective head and flow, often referred to as the efficiency curve. The efficiency curve of the Itaipu turbine is plotted. It should be noted that as the flow rate increases, the turbine's output and efficiency increase accordingly until the efficiency reaches a maximum value and then begins to decrease. In order to avoid vibration and cavitation, the efficiency curve of each effective water Itaipu turbine is reduced by the efficiency of the turbine. The current pool water level can be used as a reference point and estimated by the highest efficiency point. The operation of the turbine at other points can cause loss of power generation, expressed as: nmax turbine maximum efficiency, both are n generator sets operating.
For the Itaipu power station, the minimum and maximum flow ranges depend on the head, which are approximately 400m3/s and 720m3/s respectively. Within this range, the turbine efficiency is 70% to 95%. This large change indicates the turbine efficiency. It is an important variable for optimal scheduling of hydropower units.
Generator efficiency can be expressed by the function n = n (p), P is the power of the generator end. Indicates the efficiency curve of the Itaipu generator.
Since generator efficiency is a function of the power output itself, consideration will be given to calculating the total power generation loss.
For Itaipu, the total efficiency of the hydroelectric generating unit is n=n*\, which can be considered as 0.67. Calculate q=qn/n to calculate the head loss of the pressure pipe. According to the current front water level, calculate the effective head h/D according to the current effective head, and determine the allowable range of flow, ie qmi* if the current flow Within the allowable range, go to the next step. If the flow is less than qmin, go to step (2). If the flow is greater than qmax and the flow is based on the current flow and the effective head, the efficiency of the turbine is determined by the efficiency curve. Using (6) and n = n(p), the power loss due to tail water level, pressure pipe head loss, and turbine-generator efficiency is determined. The total power generation loss is: the following expression is used to determine the range of power generation allowed in the current front pool water level. Pmin and Pmax are the minimum and maximum power generation when n units are running: using the least square error technique to adjust the quadratic function of power loss and power generation, and get the power loss function P of n units during operation to draw Itaipu The total power loss function of the 14 units of the hydropower station during operation. For all possible units, the quadratic function adjusted to the power loss function will be one of the objective functions that need to be minimized in the optimized scheduling model. Other goals are considered in the next section. 2 Unit start-stop costs The impact of power generation loss on the operation of 14 units. However, the estimates of these costs seem to be very complicated. Nilsson met with major Swedish power producers to find out the main cost factors associated with the start and stop of power plant units, their cost and their impact on short-term operational planning. The result is that the cost per stop is $3/MWL for the Itaipu unit, and the stand-alone capacity of 700 MW is $2,100 per start-up and downtime. Hara and Viana estimate the cost associated with start and stop of the unit by predicting the wear and tear of the generator insulation. According to their research, a generator set with an estimated operating life of 60a will start and run once a day, which will reduce the operating life by 10a. These seminars show that the economic operation of the unit operation schedule requires consideration of reducing the unit start and stop. frequency. In the next section, the scheduling relationship is optimized, and the minimum number of starts and stops of the generator set is combined with the minimization of power generation loss. 3 Problem Formulation The optimization of the number of operating units based on 1h based on Itaipu Hydropower Station can be expressed by a dynamic discrete optimization model, which is a trade-off between hydropower generation efficiency and start-stop of the generator set, represented by two objective functions. Minimum number of operating units at time t; nt maximum number of operating units at time t; Pn('dt) power loss function for n units operating at time t; power generation schedule for dt at time t; Cp unit generating power Loss cost; N natural number. The formula (1 mountain ~ (12) can be effectively solved by dynamic programming technology. The time period is 1h, the state variable is the number of units running in each period, and the control variable is the number of starts or stops in each period. The state space is The natural number definition between the minimum and maximum number of units for the power generation plan is completed by each hour. The solutions of equations (10)~(12) can be obtained by solving the following recursive equations: 4 test results The model is tested according to the normal id power generation schedule, and the results highlight the minimum number of starts and stops of the generator set and the power generation. The trade-off between the two goals with the least loss, only the solution that minimizes the number of starts and stops of the unit will result in high power loss, and the solution that minimizes the power loss will result in a significant increase in the number of starts and stops. The power generation schedule is shown, as well as the maximum and minimum number of stages employed in programming the power generation schedule, which minimizes each of the two targets, respectively. It also provides a mid-angle solution considering Cq of $25/MW, and Cap is the cost per start or shutdown, which is 2 100 US dollars. The optimal solution table 1 is a list of the results obtained for each of the three cases considered, which lists the number of starts and stops of the unit and the power loss of the generated power in each case. Table 1 results summary start or down cost / US dollar power loss cost of eight dollars. MW. “li start-stop power loss/MWDh first solution, ie minimum start solution, no need to start any unit within 1d, but cause high power loss. The second angular solution, ie the minimum loss angle solution is greatly reduced The power loss, but greatly increased the number of starts. From the first solution to the second solution, the economic benefit of reducing the power loss is about 80 million US dollars / a third self-solution will combine the two goals, Compared with the second solution, the cost of the starting unit is reduced by about 17%, and the power loss is only increased by 0.3%. It can be seen that at least when estimating the unit cost considered here, the loss minimization index is lower than the shutdown indicator. The effect is even greater. However, in order to find the most economical solution, or to optimize coordination between the two objectives, it is important to identify the actual start-stop costs of the Itaipu hydroelectric generating unit. Simulation results of a fixed power generation loss of $25/MWh and varying start and stop costs are shown. Unsurprisingly, the starting and stopping number of the unit is reduced due to the increase in the starting and stopping costs. Sensitivity analysis only minimizes the number of downtimes of the unit when the cost of the downtime reaches $62,000, which plays a major role in the power loss indicator. 5 Conclusion This paper proposes a dynamic programming model, designed to determine the number of hydroelectric generating units operating in hours id, to minimize the coordination between power generation loss and start-stop costs of generator sets. The model has used the data of the Itaipu power station, the largest hydropower station in operation in the world, as a test study. It is important to consider the characteristics of each hydro-generator set one by one to accurately simulate its efficiency. It also shows that the power loss associated with the power generation system should be considered according to the short-term hydropower and thermal power operation planning model, because they have a great impact on the economic dispatch of hydropower units. In the cost of the unit considered in this research, the trade-offs increase the number of starts and stops of the unit to achieve low power loss. In short, it is important for the Itaipu Hydropower Station to develop a gradual power generation plan, so that optimal scheduling can be achieved, so that the number of starts and stops of the unit is small, and the power loss is low. The determination of the optimal scheduling of hydropower units requires investigation of the real economic costs of the start and stop of the hydroelectric generating units. For Itaipu Hydropower Station, it is estimated that the model will save energy loss. It is estimated that it is 80 million US dollars per year. Ma Yuan is translated from the American Journal of Power System Journal in February 2002.
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