The depth utilization method of condensate system’s energy-storage to improve large turbine generator units’ load response characteristic

Abstract

Load response characteristics of high thermal power units are critical to a safe and efficient grid-connected utilization of large-scale renewable energy with strong randomness. A condensate throttling regulation was reported to improve the units variable load rate. However, it is not verified by tests in different types of units. In the paper, the influence of the storage capacity of the steam generator’s condensate system on the load response characteristics is studied for four subcritical 330 MW heating units by simulation and an experimental test. The result shows the feasibility of the condensate throttling regulation, which is of great value to the practical engineering application in the future. In addition, this paper obtains the condensate regulation potential of units under different power generation load conditions through simulation and actual tests. These real data will help other units of the same type to carry out similar modifications or tests.

Keywords

Turbine generator units condensate system energy-storage utilization throttling governing load response

1. Introduction

Renewable energy represented by wind energy and solar energy is the trend of electric power development. According to the national “14th Five-Year Plan” for electric power development, the new policy puts forward the strategic goal of increasing the proportion of non-fossil energy consumption to 20% by 2030, which is the main breakthrough point of power development at this stage [1, 2, 3]. A comprehensive comparison of gas, fuel oil, hydropower, and nuclear power unable to consume renewable on a large scale, and thermal power generation as the largest power supply is the key to achieving this goal [4, 5, 6]. Therefore, how to improve the load adjustment capability of thermal power units is one of the current research topics in the field of electric power. At present about the load adjustment optimization of existing thermal power units is mainly based on two directions: Firstly, the optimization, improvement, and upgrade of the CCS (Coordination Control System); The second is to carry out the research on units’ energy storage utilization based on the characteristics of the unit’s regenerative heating system.

For CCS, the fast variable load method is mainly achieved through fuel over combustion and throttle throttling. Improving the accuracy of modeling is main aspect of optimization, such as the optimization of the control object model of 2 input and 2 output based on the original PID (Proportion Integration Differentiation) control in literature [7] to improve the accuracy of coordination adjustment; Real-time, literature [8] on the basis of the combination of neuron-free model controller and traditional PID controller, proposed a multi-variable system intelligent control method, this improved method is simple in structure and has good robustness; In order to further improve the real-time control, some scholars have established an inverse model of load and main steam pressure characteristics by using a feed-forward neural network with time-delay input and time-delay output feedback to replace the original PID adjustment [9]; Advanced methods such as predictive control, adaptive control, and big data are used in coordinated signal processing and model reconstruction to achieve rapid load changes of thermal power units [10, 11, 12, 13]. By above-mentioned, significantly improved the units’ large lag and large delay characteristics under certain circumstances, and get same effect on the units’ regulation performance to quickly change the load. However, fuel over combustion is likely to cause large parameter fluctuations, the fly ash carbon content exceeds the standard for a short time, and the valve throttle is more obviously brings energy loss [14]; meanwhile, most of the advanced methods are based on the ideal state or simulation environment. Turbine units often brings much calculation of the control system with too sensitive signals and too frequent adjustment, which reduces the method Implement ability.

Therefore, in view of the above problems, many scholars study the energy storage of units themselves, and the utilization of the energy storage reduces units’ over-regulation and energy loss to a certain extent. It mainly includes the adjustment of main reheat desuperheater, extraction heating throttling and condensate throttling, among which the mature research is turbine units’ rapid load adjustment based on condensate throttling, which mainly establishes the static and dynamic model of condensate throttling through mechanism analysis and obtains the main parameters of adjustment through simulation [15, 16], or condenses units under various working conditions based on historical data the quantitative analysis of the capacity of water junction and throttling, and the combination of this method and the coordinated control of the units to quickly activate its own energy storage [17, 18, 19]; at the same time, in order to ensure the safety of the operation of the condensate throttling system, by reasonably simplifying the basic physical laws of the system, the field experimental data and the established nonlinear control model data are identified, so as to improve the feasibility of the condensate throttling technology [20, 21, 22]. In addition researchers [23] have quantified performance indicators in the research, and proposed that the extraction of throttling high-pressure heater is the most possible choice to improve operation flexibility, The maximum value of maximum output power increment and maximum exergy storage change rate are 71.11 MW and $-$ 89.84 MW, respectively. This method can realize the rapid load adjustment of thermal power units without over adjustment, and maintain units’ overall parameter stability to a certain extent, which has high practical value. However, there are many types of units in China, and the equipment performance is different, the operation conditions are complex and diverse. This method lacks test verification in different types of units.

To sum up, based on the above research, the paper establishes the theoretical model of steam turbine and condensate system, simulates and analysis the influence of condensate throttling on units’ variable load characteristics, and conducts experimental research on four subcritical 330 MW heating units, which has important practical engineering value.

2. Turbine condensate throttle adjustment mechanism analysis and modeling and simulation

2.1 Mechanism analysis

The use of condensate throttling to adjust the variable load change rate of the turbine is essentially a comprehensive utilization of units’ energy storage; in the condenser system, the heater of the regenerative system has a certain self-balance ability, so the condenser can be controlled. The system is optimized to make units improve their load response performance under the conditions of improving or not reducing units’ operating economy and safety, thereby improving units’ AGC (Automatic Generation Control) adjustment performance. As shown in Fig. 1, when a positive load deviation occurs, the condensate throttling system immediately reduces the amount of condensed water, causing the waterside to heat up, and at the same time, the steam side pressure rises. This pressure change is directly related to the extraction pressure difference, which in turn reduces extraction steam. The reduced amount of steam can be immediately used for work, making up for the hysteresis of AGC load adjustment caused by the large inertia of the boiler. When a negative load deviation occurs, its adjustment principle and process are similar.

Figure 1.

Adjustment schematic of condensate throttling.

The main influencing factors of units’ condensate throttling adjustment capability are the characteristics of the condensate system itself and units’ load level. Among them, the maximum and minimum flow rate of the condensate pump in the condensate system and the pump outlet pressure first have a hard limit on the condensate adjustment capacity, and there is no room for research and optimization under the premise of ensuring safe operation; therefore, for the change of units’ load The resulting change in the ability to regulate condensate throttling is currently the main direction of research. According to the analysis of the current application value of this technology, it is mainly to compensate for the lag of coal-fired units and to cope with the increasing frequency of thermal power participation in power grid regulation. Therefore, the duration of condensate throttling and short-term load regulation are the main research goals.

2.1.1 Duration of condensate adjustment

The condensate throttling adjustment time is not only limited by the amount of throttling water and the return water rate, but is also largely restricted by the amount of energy stored in the deaerator, so the condensate adjustment time $T$ can be obtained by various system parameters.

Since the adjustment process is carried out dynamically, and its parameters are constantly changing, the amount of water that the deaerator can participate in the adjustment in the whole process is an integration process, which can be obtained by the following formula:

$\displaystyle M=\int_{0}^{\frac{\Delta D_{w}}{R_{w}}}{({\Delta D_{w}+R_{w}t})}dt$ (1)

In the formula, $\Delta D_{w}$ is the amount of change in flow rate, $R_{w}$ is the return speed of condensate, and $t$ is time.

Based on Eq. (1), the volume limit of the deaerator is now quantified to obtain the throttling adjustment time, which can be obtained:

$\displaystyle\frac{\rho({V_{L}-V_{N}})-M}{\Delta D_{w}}\leqslant T\leqslant% \frac{\rho({V_{H}-V_{N}})-M}{\Delta D_{w}}$ (2)

In the formula, $V_{N}$ , $V_{L}$ and $V_{H}$ are the normal water volume (volume), the minimum water volume and the maximum water volume of the saturated water that can participate in the regulation in the deaerator, respectively, which is the saturated water density.

2.1.2 Condensate adjustment load depth

Under certain working conditions, the amount of condensate that units can use for load regulation belongs to the energy storage capacity of the condensate system. Therefore, due to the influence of the deaerator, steam pressure, units’ inertia, etc., the condensate system storage and units’ load are negative Related, so now the relationship between the load change and the condensate flow rate change is described by the power gain coefficient $k_{\Delta}$ :

$\displaystyle k_{\Delta}=\frac{dN}{dD_{w}}$ (3)

The above results are based on the analysis of the basic principles of condensate regulation and ideal conditions. Therefore, this article conducts modeling and field experiments for other of types units under the above theoretical guidance.

2.2 Modeling simulation and result analysis

This article selects four subcritical 330 MW heating units as the object of modeling, simulation, and experimental research. The units are equipped with subcritical, primary intermediate reheat, single shaft, three cylinders, dual exhaust, the impulse produced by the French general ALSTHOM steam turbine plant. Type, condensing steam turbine, model T2A-330-30-2F1080. The condensate and units’ reheating heating system are shown in Fig. 2.

Figure 2.

Units’ condensate system and regenerative heating system.

A simulation model of the effect of units’ condensate throttling is established in this paper. The main idea of modeling is to influence the heat balance of the low-pressure heater when adjusting the condensate throttling, and the distribution of steam at each extraction point the regenerative system is divided into four stages with a regenerator, which can be modeled separately. Figure 2 shows a simplified model of one regenerator stage group, which is mainly composed of four groups: stage group 1, extraction space, regenerator, and extraction steam flow calculation.

Figure 3.

Regenerative heating stage set.

The steam flow in front of the $G$ group in the figure above $G_{c}$ is the extraction steam flow of the group, the model of the group in the figure is modeled according to the D extraction port, and the corresponding steam destination is #4 low-pressure heater as shown in Fig. 2. Therefore, the modeling mainly calculates the steam flow of the stage group based on the known pre-stage pressure temperature, flow characteristic coefficient, stage group efficiency and post-stage pressure parameter, and uses the isentropic enthalpy drop method to solve the post-stage steam temperature and enthalpy; The steam space model uses the extraction space as a control body to calculate the steam state at the extraction point by using the law of conservation of mass and energy, and at the same time combines the extraction flow calculation and the stage group flow calculation to solve the steam flow distribution problem at the extraction point.

Taking #1 steam turbine units as an example, modeling and simulation are carried out. The values of each parameter are as follows.

Table 1

Level group related parameters

Number	Parameter	Numerical
1	Front stage set flow characteristic	6.1269E-4 kg/s/Pa
2	Post stage set flow characteristic	0.0013 kg/s/Pa
3	Check valve flow characteristic constant	2.5742
4	Front stage set efficiency	0.9292
5	Cold end volume of regenerator	13.885 m ${}^{3}$
6	Hot end volume of regenerator	13.885 m ${}^{3}$
7	Product of coefficient and area of regenerator	1.7606E6W/K

Under THA (Turbine Heat Acceptance) condition, the condensate flow is reduced from 216.84 kg/s to 215.84 kg/s and 1 kg/s in 400 s, and units’ power changes are shown in the figure below.

Figure 4.

Power response curve under THA condition.

Figure 5.

Condensate throttling test (THA condition).

As shown in the above figure, under this condition, the load change amount with the condensate flow rate is changed as a single independent variable, when it is only reduced by 1 kg/s, the adjustment time lasts about 95 s, compared with the conventional adjustment load response time of about 30 s, The condensate throttling under this condition fully meets the requirements of rapid regulation; similarly, at a reduced 1 kg flow rate, the load change can reach 0.16 MW. Combined with the recuperation volume in Table 1, the load change value can reach more than 20 MW. It can fully respond to the normal load regulation of 1%, and the results of other working conditions are consistent with the analysis. The above simulation results verify the analysis of condensate characteristics, and at the same time illustrate the effectiveness of condensate throttling under ideal conditions, so to further illustrate the practicability of this method, field experiments are now being conducted on turbine units.

3. Test and result analysis of turbine units

Condensate throttling can be used to improve units’ AGC performance, but in view of the unique operating status of each set of units, even the same type units have a large difference in performance due to long-term accumulation due to different operating conditions. In order to ensure the above-mentioned optimized design is targeted and implementable, a targeted test should be performed for each set of turbine units, and the effective data of the condensate water and the regenerative system under units’ working condition should be used to condense units. Water throttling adjustment capability is evaluated to obtain the adjustment depth of each load section. The design idea of the test scheme: Obtain data of changes in parameters such as extraction steam and condensate by changing the operating conditions to evaluate the regulation potential of units under each load section. Taking an actual T2A-330-30-2F1080 turbine as an example, the THA operating condition, 75% THA operating condition, 50% THA operating condition, and 30% THA operating condition are selected for the testing; among them, the THA operating condition refers to them under the steam inlet parameters, the rated back pressure, the regenerative system is in normal operation, the water supply rate is zero, and the power can be continuously emitted. Moreover, many factors are considered, and the test load may deviate from the preset value.

Table 2
Parameters related to extraction, condensate, and drainage of turbine’s high-pressure heaters, deaerator, and steam exhaust under THA working conditions

Extraction steam direction	Extraction steam (t/h)	Extraction specific enthalpy (KJ/kg)	Outlet condensate flow (t/h)	Outlet condensate specific enthalpy (KJ/kg)	Drain flow (t/h)	Drain specific enthalpy (KJ/kg)
#1 HP heater	48.53	3360.7	963	1112.7	48.53	2931
#2 HP heater	88.74	3050.3	963	1091	88.74	924.5
#3 HP heater	48.53	2931	963	895.1	137.27	801.9
Deaerator	36.56	3154.8	963	748.3	0	0
#5 LP heater	60.66	3001.4	789.17	627.5	60.66	464.9
#6 LP heater	22.84	2739.9	789.17	432.5	22.84	273.9
#7 LP heater	30.73	2633.8	674.94	354.5	30.73	365.4
#8 LP heater	35.18	2502.3	674.94	251.3	35.18	262
Exhaust steam	602.23	2326.7	–	–		–

Table 3

Parameters related to extraction, condensate, and drainage of turbine’s high-pressure heaters, deaerator, and steam exhaust under 75% THA working conditions

Extraction steam direction	Extraction steam (t/h)	Extraction specific enthalpy (KJ/kg)	Outlet condensate flow (t/h)	Outlet condensate specific enthalpy (KJ/kg)	Drain flow (t/h)	Drain specific enthalpy (KJ/kg)
#1 HP heater	31.71	3371.1	696	1029.9	31.71	2908.3
#2 HP heater	57.78	3013.6	696	1008.8	57.78	857
#3 HP heater	31.71	2908.3	696	829.8	89.49	745.9
Deaerator	24.55	3164.4	696	693.9	0	0
#5 LP heater	41.41	3009.8	581.96	581.7	41.41	430.3
#6 LP heater	16.12	2748	581.96	398.1	57.53	354.6
#7 LP heater	21.23	2639.4	503.2	322.9	21.23	333.7
#8 LP heater	19.98	2506.8	503.2	135.5	19.98	236.3
Exhaust steam	602.23 (478.91)	2326.7 (2355.3)	–	–		–

Table 4

Parameters related to extraction, condensate, and drainage of turbine’s high-pressure heaters, deaerator, and steam exhaust under 50% THA working conditions

Extraction steam direction	Extraction steam (t/h)	Extraction specific enthalpy (KJ/kg)	Outlet condensate flow (t/h)	Outlet condensate specific enthalpy (KJ/kg)	Drain flow (t/h)	Drain specific enthalpy (KJ/kg)
#1 HP heater	17.59	3383.8	467	928.5	17.59	2877.8
#2 HP heater	33.07	3009.5	467	909.4	33.07	776
#3 HP heater	17.59	2877.8	467	751.3	50.66	684.1
Deaerator	15.26	3186.3	467	634.1	0	0
#5 LP heater	26.13	3029.2	401.08	530.6	26.13	390.7
#6 LP heater	10.37	2763.6	401.08	358.7	36.5	319.3
#7 LP heater	13.63	2652.3	350.94	287.6	13.63	298.4
#8 LP heater	8.96	2519.1	350.94	196.2	8.96	206.9
Exhaust steam	324.09	2396.5	–	–		–

Table 5

Parameters related to extraction, condensate, and drainage of turbine’s high-pressure heaters, deaerator, and steam exhaust under 30% THA working conditions

Extraction steam direction	Extraction steam (t/h)	Extraction specific enthalpy (KJ/kg)	Outlet condensate flow (t/h)	Outlet condensate specific enthalpy (KJ/kg)	Drain flow (t/h)	Drain specific enthalpy (KJ/kg)
#1 HP heater	9.45	3390.7	289	827.9	9.45	2845.5
#2 HP heater	17.51	3010.9	289	810.1	17.51	691.9
#3 HP heater	9.45	2845.5	289	669.6	26.96	611.6
Deaerator	8.54	3193.2	289	563.8	0	0
#5 LP heater	14.91	3039.3	253.51	470.2	14.91	343.4
#6 LP heater	6.04	2769.6	253.51	311.6	20.95	277
#7 LP heater	7.89	2657.7	224.67	245.4	7.89	256.1
#8 LP heater	1.99	2526.6	224.67	161.1	1.99	171.8
Exhaust steam	210.72	2464.6	–	–		–

Table 6

Units’ variable load capacity corresponding to its condensate change

Operating conditions	Condensate flow change (t/h)	Change rate of condensate flow (%)	Load variation (MW)	Load change rate (%)
THA	584.81	86.6	24.29	7.4
75% THA	442.02	87.8	16.02	4.9
50% THA	313.51	89.3	9.53	2.9
30% THA	204.33	90.9	4.77	1.4

Four set of units were tested under multiple operating conditions, and one of them was selected for analysis. Among them, the parameters of the condensate system and the regenerative system under THA conditions are shown in Fig. 5(1) and (2). The above Fig. 5(1) shows the changes in the unit’s condensate flow and deaerator water level when units’ load command changes. While Fig. 5(2) shows the subsequent parameter changes of each heater.

Tables 2 to 5 show the extraction, condensate, and hydrophobic parameters of the high-pressure heater, deaerator, and exhaust steam of the turbine under different operating conditions; Table 6 shows the relationship between the change in condensate flow and load in the Dalate power plant. From the table above, it can be seen that: under THA conditions, units can quickly change the power of 24.29 MW, which accounts for 7.4% of units’ rated load. This data can meet the grid’s requirements for power plants to change the load to participate in frequency regulation. Similarly, under the constant pressure 75% load condition, the power changed by units through throttling of condensed water accounts for 4.9% of units’ rated power, which can basically meet the requirements of units’ load change rate under the AGC mode, but it is more than THA operation It is down. Under a constant load of 50% and 30% load conditions, the power that can be changed by units is further reduced. And with the reduction of units’ load, the amount of condensate that can be used for throttling gradually decreases, and units’ heat storage release brought by the throttling of the condensate also decreases. Moreover, as units’ load decreases, the lower the condensate flow rate that units can change, the lower the maximum load change due to condensate throttling; and when the condensate flow rate of the same size is changed, the larger the load, the load changes The larger the amount. In addition, the larger the load conditions, the better the effect obtained by using condensate throttling. In other words, under the condition that other conditions do not change, the higher units’ load, the greater the load change caused by condensate throttling, which is sufficient to meet the grid’s requirements for units to participate in frequency regulation. But at the same time, many deficiencies in condensate water throttling are also exposed to the calculation results. For example, it causes large-scale fluctuations in the water level of the deaerator. If it is not properly controlled, it may affect units’ safe operation; on the other hand, the method of regulating the load by throttling condensate can only maintain a short time range.

4. Conclusions and outlook

In this paper, the simulation and experimental research of improving units’ load response characteristics by throttling the condensate of the steam turbine are carried out. The conclusions are as follows:

(1)

After the condensate flow changes, units’ load can respond within 5 to 10 s. The load reaches its peak in about 30 s under 75% of the rated load and the peak in the 50 s under 90% of the rated load. Maintain for 1.5 $\sim$ 3 min;

(2)

Under different load conditions, the gain of the condensate flow rate change to units’ load change is in the range of 0.035 $\sim$ 0.045, and the gain becomes larger as the load increases; the higher the load, the condensate throttling load adjustment capacity The stronger; as units’ load decreases, the amount of condensate available for throttling gradually decreases, and units’ heat storage release caused by the throttling of the condensate also decreases;

(3)

When the flow of condensate changes in the range of 150 $\sim$ 250 t/h, the water level of the deaerator changes between 120 mm $\sim$ 230 mm, and the water level of the condenser changes between 70 $\sim$ 130 mm, the larger the saturated water capacity in the deaerator, the longer the condensate throttling dynamic response duration;

(4)

When the water level of the deaerator is within 300 mm, and the condenser water level is changed within 200 mm, it can ensure the safe and stable operation of thermal system equipment such as deaerator, condenser, etc., while making full use of the condensate and the heat storage system. Yes, this is related to the volume of the deaerator.

(5)

The actual condensate adjustment potential of units under different power generation load conditions is obtained. And the accuracy of the data will help improve the overall coordinated control performance, and also provide safe data references for other units of the same type.

This paper has a certain reference value for obtaining the dynamic characteristics of condensate water throttling under different loads and the potential of load adjustment.

Footnotes

Acknowledgments

This work was funded in part by the Key R&D Project of China under Grant 2017YFB0902101, the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (Grant No. LAPS19012), Zhejiang Energy Group Science and Technology Project (NO. ZNKJ-2017-075) and CERNET Innovation Project (No. NGIICS20190801).

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The depth utilization method of condensate system’s energy-storage to improve large turbine generator units’ load response characteristic

Abstract

Keywords

1. Introduction

2. Turbine condensate throttle adjustment mechanism analysis and modeling and simulation

2.1 Mechanism analysis

Table 2 Parameters related to extraction, condensate, and drainage of turbine’s high-pressure heaters, deaerator, and steam exhaust under THA working conditions

Footnotes

Acknowledgments

References

Table 2
Parameters related to extraction, condensate, and drainage of turbine’s high-pressure heaters, deaerator, and steam exhaust under THA working conditions