# Investment Efficiency Assessment Model for Pumped Storage Power Plants Considering Grid Operation Demand under Fuzzy Environment: A Case Study in China

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## Abstract

**:**

## 1. Introduction

## 2. Literature Review

#### 2.1. Pumped Energy Storage

#### 2.2. Investment Efficiency Assessment

#### 2.3. Findings of Literature Review

## 3. Efficiency Factor Identification and Index System Establishment

#### 3.1. Identification of Efficiency Factors

#### 3.2. Power Restructuring Demand Level

- (1)
- Proportion of installed nuclear power capacity (A1): It means the proportion of nuclear power installed capacity in the total installed capacity about the regional power grid, but nuclear power is subject to its own economic and technical safety constraints; its frequent participation in peak load regulation increases the maintenance costs of equipment. Otherwise, investment in pumped storage power plants can improve the efficiency of nuclear power. This way can avoid the cost increase of nuclear power units per unit during the bimodal hours and also can meet functional needs of the grid.Therefore, the installed nuclear capacity in the regional grid enables the support function of pumped storage power plants to be used as a means of increasing the efficiency of the plant.
- (2)
- Proportion of installed wind power capacity (A2): It means the proportion of wind power installed capacity in the total installed capacity of the regional power grid. Wind power generation has randomness and uncertainty; pumped storage power plants can play a positive effect on the maintenance of wind power. Therefore, investing in pumped storage will provide better efficiency.
- (3)
- PV installed capacity ratio (A3): It means the proportion of PV installed capacity to the total installed capacity on the regional power grid. The power quality and instability of photovoltaic power generation are similar to wind power, and also have an impact on safe performance. Pumped storage power plants can not only guarantee the smooth output of photovoltaic power generation systems through peak and frequency regulation but can also improve the grid friendliness and power quality of photovoltaic power generation. Therefore, the increase in PV capacity can also guarantee pumped storage power station efficiency.
- (4)
- Proportion of installed hydropower capacity (A4): It means the proportion of hydropower installed capacity to the total regional power grid installed capacity. Due to the influence of natural conditions, the generation of hydropower units varies considerably during the high and low water periods. The former uses abandoned water for peaking and the latter means reduced peaking capacity due to reduced operating capacity. On the one hand, pumped storage power plants can alleviate the peaking demand of hydropower during the abundant period, and on the other hand, they can reduce the output pressure of hydropower units during the dry period and lower the unit generation cost of the peaking cost in the system, thus improving the efficiency of hydropower unit operation.
- (5)
- Proportion of installed cogeneration capacity (A5): It means the installed CHP units of the total installed capacity in the regional grid proportion. Insufficient peaking capacity of the system will appear when the heating demand is high. Because pumped storage power plants have a peaking effect, the effectiveness of building pumped storage power plants will be guaranteed.
- (6)
- Proportion of incoming power to the system (A6): It means the proportion of incoming power in the regional power grid to the total power consumption. Due to the unbalanced development of natural resources and economy, the share of incoming power in the eastern region of the grid is also gradually increasing. Renewable energy sources do not provide enough peaking capacity for incoming power, and the power variation further increases the regulation capacity of the grid at the receiving end. The deployment of pumped storage power plants in the receiving grid can effectively improve the peaking pressure of the receiving grid. Therefore, this indicator can measure the benefits of pumped storage power plants.

#### 3.3. Regional Grid Security and Stable Operation Demand Level

- (1)
- Maximum system load (A7): The maximum load of the regional power grid is closely related to the level of regional economic and production development, and the maximum load needs to raise the peak output of the power system which will increase the reliance on accident reserve capacity. Pumped storage power plants have a good peak shaving effect, can reduce the system’s output pressure, and can effectively supplement the system’s reserve capacity. Therefore, pumped storage power plants can effectively perform their regulating function in regional power grids with high maximum loads and improve their functional performance.
- (2)
- Number of UHV landing points (A8): At present, extra high voltage input can easily lead to regional grid operation facing the safety problems of insufficient frequency support capacity and large system power fluctuations after DC blocking. Now, pumped storage plants can make up the power difference caused by severe failures. Therefore, pumped storage units can give full play to their strategic function of safety and security in the regional grid.
- (3)
- Proportion of electricity consumption by the tertiary industry and residents (A9): It means the proportion of electricity consumption of the tertiary industry with urban and rural residents in the regional power grid to the total electricity consumption of the society. The large difference in electricity consumption between different industries leads to spikes in the power grid, increasing the pressure on the safe and stable operation of the power grid. The increase of the proportion of electricity consumption by the tertiary industry or residents can effectively promote the full play of the function of pumped storage power plants and increase the investment efficiency.
- (4)
- Reliability rate of power supply (A10): It is expressed in terms of the average annual outage time of customers and the accumulated hours of the year, which can characterize the reliability of the regional power grid. Pumped storage power plants have a black start function which enables the regional power grid to restore power supply capacity in the shortest possible time and can be used as emergency backup power. This improves the stability of regional power grid operation.
- (5)
- Frequency crossing time (A11): Fluctuation of the grid frequency will affect the quality of electricity for users, the economic operation of equipment, and regional grid security. Pumped storage power plants are much better than thermal power units and gas turbines in terms of their ability to climb and peak, and their ability to quickly track load changes can help maintain the grid frequency. Therefore, considering the grid frequency crossing time can improve the efficiency of developing pumped storage power plants.
- (6)
- Transmission fault rate (A12): It means the annual number ratio of transmission line failures to the 100 km length of transmission lines in the regional grid. The level of transmission failure rate will affect the investment efficiency of pumped storage power plants in improving the power quality of the regional power grid.
- (7)
- Proportion of flexible power supply (A13): The proportion of the installed capacity of pumped storage, other energy storage and gas power units in the regional power grid to the total installed capacity. The flexible power supply can improve the output volatility of new energy power in the system and enhance the regulation ability of the regional power grid. Pumped storage is the main force of flexible power; if the regional grid has a high proportion of flexible power, it will to a certain extent limit the function of the new pumped storage power plant and reduce the investment efficiency.

#### 3.4. Regional Grid Energy Storage Demand Level

- (1)
- Annual system generation capacity (A14): Pumped storage power plants can store discarded power, which prevents low load operation or shutdown of the units during under load conditions, and allows the units to maintain normal processing conditions as much as possible, increasing their operating time.
- (2)
- Annual power demand of the system (A15): For regional power grids where the power generation is greater than the power demand, the construction of pumped storage power plants can improve the power consumption capacity and ensure the power quality when the power is sent out. Therefore, the system power demand can also be a factor affecting the pumped storage power plant’s efficiency.
- (3)
- Wind turbine utilization rate (A16): It means the ratio of wind turbines’ annual utilization hours to the number of calendar hours, which can characterize the abandonment of wind turbines in the regional grid. The construction of pumped storage power plants can not only improve the system’s peaking capacity, but also store power and largely reduce the wind power abandoned by wind farms.
- (4)
- PV unit utilization rate (A17): It refers to the ratio of annual utilization hours of PV units to the number of calendar hours, which can characterize the abandonment of PV units. Photovoltaic power plant construction scale and regional load level mismatch and market consumption capacity is limited, so the region will appear as “abandoned light” phenomenon. The construction of pumped storage power plants can provide energy storage capacity for the regional power grid, cooperate with the power delivery and consumption of PV power plants, and promote the further development of PV installations.
- (5)
- Nuclear power unit utilization rate (A18): It means the ratio of annual utilization hours of nuclear power units to calendar hours, which can characterize the utilization of nuclear power units. The pumped storage power plant can make the nuclear power units in the system change the pressure load operation to stable power operation. Therefore, the joint operation of nuclear units with pumped storage power plants can increase the operating hours of nuclear units, ensure the full function of pumped storage power plants, and reduce investment efficiency.
- (6)
- Abandoned water power (A19): This indicator mainly includes the amount of peaking abandoned hydroelectricity and installed abandoned hydroelectricity. The former refers to water abandonment that cannot be stored during low load hours, while the latter refers to water abandonment due to power differentials. Pumped storage power plants can use the energy storage characteristics to absorb excess power in the system. When the power demand decreases, hydropower plants can store energy to defense abandon energy. For the existence of abandoned water power, the regional power grid has a positive effect.
- (7)
- Proportion of electricity sent out from the system (A20): It means the proportion of electricity sent out in the regional power grid to the total power generation. At this stage, it is difficult for new energy to be used as an effective capacity of the power market, which will reduce the transmission quality of transmission lines. Pumped storage power plants use the function of energy storage to regulate and compensate for the new energy power on the regional grid. Therefore, the construction of pumped storage power plants can contribute to improving delivered power quality to increase investment efficiency.
- (8)
- Maximum peak-to-valley difference rate of the system (A21): It means the maximum peak-to-valley power difference as a proportion of the maximum system load. The maximum peak-to-valley difference affects the difficulty of power system peaking and directly affects the peaking capacity. The pumped storage power plant can effectively regulate the dynamic balance between peak and trough of regional power grid load through electrical energy storage and discharge. Therefore, the increase or decrease of the maximum peak-to-valley difference of the regional power grid has a significant impact on the pumped storage power plant’s ability to fully perform its energy storage function and improve the power grid functionality.
- (9)
- System peaking capacity ratio (A22): It means the ratio of all forms of operating units’ adjustable operating capacity in the regional grid to all units’ total rated capacity. Thermal power units involved in peaking work but have a minimum output requirement. The peak shaving feature of pumped storage can effectively improve the system peaking capacity ratio and enhance the peaking capacity of the regional grid. Therefore, the system peaking level capacity ratio will influence the pumped storage power plants’ investment efficiency.

#### 3.5. Establishment of an Efficiency Evaluation Index System

## 4. Methodology for Investment Efficiency Evaluation

#### 4.1. Information Representation—Cloud Model and AHP

#### 4.2. Calculation of Weights

- (1)
- Construct the judgment matrix $A=\left({a}_{ij}\right)$, satisfying ${a}_{ii}=1$, ${a}_{ji}=\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{${a}_{ij}$}\right.$.
- (2)
- Transform matrix A to the compatibility matrix $\mathrm{B}=\left({\mathrm{b}}_{\mathrm{ij}}\right)$, where ${b}_{ij}=\sqrt[n]{\prod _{k=1}^{n}{a}_{ik}\xb7{a}_{kj}}$, and $B$ satisfies ${b}_{ii}=1$, and ${b}_{ji}={b}_{ik}\xb7{b}_{kj}$.
- (3)
- Calculate the weights ${\omega}_{i}$$${\omega}_{i}=\frac{{c}_{i}}{{\sum}_{k=1}^{n}{c}_{k}}\left(i=1,2,3,\cdots n\right)$$

- (1)
- Data standardization: In practice, the units of different pumped storage power plant investment efficiency evaluation indicators are inconsistent, so in order not to let the units of indicators have an impact on the final evaluation results, it is necessary to carry out the dimensionless processing of investment efficiency evaluation indicators, and the normalized sample of indicators is recorded as ${\mathrm{r}}_{\mathrm{ij}}^{*}$.
- (2)
- Based on the normalized data matrix ${\mathrm{r}}_{\mathrm{ij}}^{*}$ to calculate the weight ${\mathrm{p}}_{\mathrm{ij}}$ from $\mathrm{j}$ indicator under $\mathrm{i}$ evaluation object:$${p}_{ij}={r}_{ij}^{*}/{\displaystyle \sum}_{i=1}^{m}{r}_{ij}^{*}$$
- (3)
- Calculate the entropy value, calculate the entropy value of the $\mathrm{j}$ entropy value of the evaluation indicator ${\mathrm{e}}_{\mathrm{j}}$.$${e}_{j}=-\frac{1}{\mathrm{ln}\left(m\right)}{\displaystyle \sum}_{i=1}^{m}{p}_{ij}\xb7\mathrm{ln}{p}_{ij}$$If ${\mathrm{p}}_{\mathrm{ij}}=0$, then make ${\mathrm{p}}_{\mathrm{ij}}\xb7\mathrm{ln}{\mathrm{p}}_{\mathrm{ij}}=0$ thus making $0\le {\mathrm{e}}_{\mathrm{j}}\le 1$.
- (4)
- Calculation of the coefficient of variation, calculation of the coefficient of variation of the $\mathrm{j}$ coefficient of variation of the evaluation indicator ${\mathrm{g}}_{\mathrm{j}}$.$${g}_{j}=1-{e}_{j}$$
- (5)
- Calculate the weights, then the weight ${\mathsf{\omega}}_{\mathrm{j}}$ of the $\mathrm{j}$ evaluation index can be obtained from the coefficient of variation of each evaluation index.$${\omega}_{j}={g}_{j}/{\displaystyle \sum}_{j=1}^{n}{g}_{j}$$

#### 4.3. Integration

## 5. Case Analysis

#### 5.1. Background Information

#### 5.2. Benefits Assessment

#### 5.3. Investment and Development Advice

## 6. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A

- (1)
- Interrelationship analysis of investment risk benefit

- (2)
- Hierarchical level division of investment efficiency factors

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Scale Values | Meaning |
---|---|

1 | Both indicators have the same importance compared to each other |

3 | One of the two metrics is slightly more important than the other |

5 | One of the two metrics is clearly important compared to the other |

7 | One of the two indicators is strongly important compared to the other |

9 | One of the two indicators is extremely important compared to the other |

2, 4, 6, 8 | If the comparison of two indicators is in between, the middle value of the adjacent judgment is taken |

Countdown | If the indicator $i$ the ratio of the indicator to the $j$ ratio of importance is ${a}_{ij}$ then the indicator $j$ and the ratio of the importance of the indicator $i$ The ratio of the importance of the elements is ${a}_{ji}=\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{${a}_{ij}$}\right.$ |

North China Region | Northeast China Region | East China Region | Central China Region | Northwest China Region | Southern China Region | |
---|---|---|---|---|---|---|

X11 | 0.31% | 3.11% | 6.07% | 0.00% | 0.00% | 5.30% |

X12 | 13.69% | 19.96% | 4.47% | 4.71% | 18.44% | 5.83% |

X13 | 10.75% | 7.09% | 10.48% | 7.18% | 16.64% | 4.08% |

X14 | 2.04% | 5.71% | 8.38% | 41.84% | 12.86% | 38.78% |

X15 | 6.27% | 2.69% | 12.83% | 9.00% | 1.76% | 4.15% |

X16 | 2.33244 | 0.663 | 2.5132 | 1.4178 | 0.90816 | 1.64565 |

X21 | 5.115 | 0 | 0.3 | 4.08 | 0 | 3.105 |

X22 | 26.39% | 29.78% | 31.83% | 37.33% | 19.71% | 34.57% |

X23 | 99.83% | 99.79% | 99.89% | 99.81% | 99.71% | 99.79% |

X24 | 1.46% | 1.17% | 2.91% | 1.41% | 0.28% | 2.65% |

X31 | 25.06% | 25.50% | 26.85% | 23.65% | 21.99% | 26.51% |

X32 | 11.69% | 16.49% | 10.93% | 10.58% | 13.66% | 9.18% |

X33 | 3.13% | 7.76% | 0.00% | 7.88% | 18.61% | 13.02% |

X34 | 39.04% | 34.92% | 44.36% | 39.21% | 34.01% | 40.50% |

X35 | 33.61% | 33.20% | 40.58% | 62.56% | 35.00% | 61.08% |

I | II | III | IV | V | |
---|---|---|---|---|---|

X11 | (4.25%, 5.30%) | (3.19%, 4.25%) | (2.12%, 3.19%) | (1.06%, 2.12%) | (0.00%, 1.06%) |

X12 | (14.87%, 17.61%) | (12.13%, 14.87%) | (9.39%, 12.13%) | (6.64%, 9.39%) | (3.91%, 6.64%) |

X13 | (12.32%, 14.51%) | (10.13%, 12.32%) | (7.93%, 10.13%) | (5.74%, 7.93%) | (3.55%, 5.74%) |

X14 | (29.89%, 36.92%) | (22.87%, 29.89%) | (15.84%, 22.87%) | (8.82%, 15.84%) | (1.79%, 8.82%) |

X15 | (9.28%, 11.21%) | (7.34%, 9.28%) | (5.41%, 7.34%) | (3.47%, 5.41%) | (1.54%, 3.47%) |

X16 | (1.872, 2.196) | (1.548, 1.872) | (1.233, 1.548) | (0.909, 1.233) | (0.00585, 0.909) |

X21 | (7.2, 9) | (5.4, 7.2) | (3.6, 5.4) | (1.8, 3.6) | (0, 1.8) |

X22 | (29.79%, 32.94%) | (26.64%, 29.79%) | (23.49%, 26.64%) | (20.34%, 23.49%) | (17.19%, 20.34%) |

X23 | (89.74%, 89.77%) | (89.77%, 89.80%) | (89.80%, 89.84%) | (89.84%, 89.87%) | (89.87%, 89.90%) |

X24 | (0.30%, 0.86%) | (0.86%, 1.42%) | (1.42%, 1.99%) | (1.99%, 2.55%) | (2.55%, 3.11%) |

X31 | (22.61%, 23.46%) | (21.75%, 22.61%) | (20.89%, 21.75%) | (20.03%, 20.89%) | (19.18%, 20.03%) |

X32 | (13.24%, 14.55%) | (11.93%, 13.24%) | (10.61%, 11.93%) | (9.30%, 10.61%) | (7.98%, 9.30%) |

X33 | (12.98%, 16.23%) | (9.74%, 12.98%) | (6.49%, 9.74%) | (3.25%, 6.49%) | (0.00%, 3.25%) |

X34 | (36.95%, 38.76%) | (35.13%, 36.95%) | (33.30%, 35.13%) | (31.48%, 33.30%) | (29.66%, 31.48%) |

X35 | (42.14%, 35.81%) | (42.14%, 48.47%) | (48.47%, 54.80%) | (54.80%, 61.13%) | (61.13%, 67.46%) |

I | II | III | IV | V | |
---|---|---|---|---|---|

X11 | (0.047, 0.001, 0.1) | (0.037, 0.001, 0.1) | (0.026, 0.001, 0.1) | (0.015, 0.001, 0.1) | (0.053, 0.001, 0.1) |

X12 | (0.162, 0.005, 0.1) | (0.135, 0.005, 0.1) | (0.094, 0.000, 0.1) | (0.280, 0.005, 0.1) | (0.053, 0.005, 0.1) |

X13 | (0.134, 0.004, 0.1) | (0.112, 0.004, 0.1) | (0.090, 0.004, 0.1) | (0.068, 0.004, 0.1) | (0.146, 0.004, 0.1) |

X14 | (0.334, 0.012, 0.1) | (0.263, 0.012, 0.1) | (0.194, 0.012, 0.1) | (0.123, 0.012, 0.1) | (0.053, 0.012, 0.1) |

X15 | (0.102, 0.003, 0.1) | (0.083, 0.003, 0.1) | (0.064, 0.003, 0.1) | (0.044, 0.003, 0.1) | (0.025, 0.003, 0.1) |

X16 | (2.034, 0.054, 0.1) | (1.710, 0.054, 0.1) | (1.391, 0.054, 0.1) | (1.071, 0.054, 0.1) | (0.457, 0.054, 0.1) |

X21 | (8.100, 0.300, 0.1) | (6.300, 0.300, 0.1) | (4.500., 0.300, 0.1) | (2.700, 0.300, 0.1) | (0.900, 0.300, 0.1) |

X22 | (0.314, 0.005, 0.1) | (0.282, 0.005, 0.1) | (0.251, 0.005, 0.1) | (0.219, 0.005, 0.1) | (0.187, 0.005, 0.1) |

X23 | (0.898, 0.000, 0.1) | (0.298, 0.000, 0.1) | (0.898, 0.000, 0.1) | (0.899, 0.000, 0.10) | (0.898, 0.000, 0.1) |

X24 | (0.006, −0.001, 0.1) | (0.011, −0.001, 0.1) | (0.010, −0.001, 0.1) | (0.023, −0.001, 0.1) | (0.283, −0.001, 0.1) |

X31 | (0.230, 0.001, 0.1) | (0.222, 0.014, 0.1) | (0.213, 0.001, 0.10) | (0.205, 0.001, 0.1) | (0.196, 0.001, 0.1) |

X32 | (0.138, 0.002, 0.1) | (0.126, 0.002, 0.1) | (0.113, 0.002, 0.10) | (0.100, 0.002, 0.1) | (0.056, 0.002, 0.1) |

X33 | (0.146, 0.005, 0.1) | (0.113, 0.005, 0.1) | (0.281, 0.005, 0.10) | (0.149, 0.005, 0.1) | (0.016, 0.005, 0.1) |

X34 | (0.378, 0.003, 0.1) | (0.360, 0.003, 0.1) | (0.342, 0.003, 0.10) | (0.324, 0.003, 0.10) | (0.306, 0.003, 0.10) |

X35 | (0.389, −0.011, 0.1) | (0.453, −0.011, 0.1) | (0.516, −0.011, 0.1) | (0.580, −0.011, 0.1) | (0.643, −0.011, 0.1) |

Indicators | Grade Similarity | ||||
---|---|---|---|---|---|

I | II | III | IV | V | |

X11 | 0.010654 | 0.001795 | 0.073147 | 0.684492 | 0.995311 |

X12 | 0.40558 | 0.988275 | 0.083203 | 8.7 × 10^{−124} | 0.014743 |

X13 | 1.34 × 10^{−17} | 0.780706 | 0.025356 | 0 | 9.03 × 10^{−7} |

X14 | 6.27 × 10^{−43} | 0 | 7.66 × 10^{−27} | 2.28 × 10^{−33} | 0.210901 |

X15 | 1.5 × 10^{−25} | 0.204964 | 0.998678 | 0.086514 | 6.38 × 10^{−6} |

X16 | 1.34 × 10^{−8} | 1.81 × 10^{−26} | 2.2 × 10^{−182} | 7.89 × 10^{−89} | 8.73 × 10^{−34} |

X21 | 3.53 × 10^{−22} | 0.000492 | 0.132746 | 2.65 × 10^{−16} | 1.45 × 10^{−38} |

X22 | 9.13 × 10^{−8} | 0.669467 | 0.845394 | 0.174906 | 1.97 × 10^{−5} |

X23 | 4.53 × 10^{−25} | 2.01 × 10^{−47} | 0 | 5.39 × 10^{−27} | 4.7 × 10^{−117} |

X24 | 0.707498 | 0.839469 | 0.982168 | 7 × 10^{−27} | 0.159179 |

X31 | 0.000116 | 0.010732 | 2.35 × 10^{−25} | 5.26 × 10^{−37} | 8.8 × 10^{−6} |

X32 | 0.712553 | 0.030463 | 0.900881 | 0.457519 | 2.6 × 10^{−179} |

X33 | 0 | 7.9 × 10^{−176} | 0.000878 | 0.512136 | 0.344368 |

X34 | 0.787089 | 8.84 × 10^{−6} | 0 | 0.002778 | 8.21 × 10^{−33} |

X35 | 0.00381 | 1.45 × 10^{−7} | 2.08 × 10^{−10} | 1.8 × 10^{−248} | 0 |

**Table 6.**Investment efficiency level affiliation of pumped storage power plants in each regional grid.

Affiliation | Regional Grids | |||||
---|---|---|---|---|---|---|

North China Region | Northeast China Region | East China Region | Central China Region | Northwest China Region | Southern China Region | |

I | 0.176 | 0.160 | 0.195 | 0.150 | 0.167 | 0.135 |

II | 0.220 | 0.147 | 0.063 | 0.119 | 0.085 | 0.055 |

III | 0.222 | 0.192 | 0.096 | 0.257 | 0.051 | 0.095 |

IV | 0.136 | 0.109 | 0.054 | 0.122 | 0.149 | 0.167 |

V | 0.126 | 0.184 | 0.149 | 0.195 | 0.173 | 0.217 |

$MAX\left(M\left({v}_{i}\right)\right)$ | III | III | I | III | V | V |

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**MDPI and ACS Style**

Lu, Y.; Liu, X.; Zhang, Y.; Yang, Z.; Wu, Y.
Investment Efficiency Assessment Model for Pumped Storage Power Plants Considering Grid Operation Demand under Fuzzy Environment: A Case Study in China. *Sustainability* **2023**, *15*, 8724.
https://doi.org/10.3390/su15118724

**AMA Style**

Lu Y, Liu X, Zhang Y, Yang Z, Wu Y.
Investment Efficiency Assessment Model for Pumped Storage Power Plants Considering Grid Operation Demand under Fuzzy Environment: A Case Study in China. *Sustainability*. 2023; 15(11):8724.
https://doi.org/10.3390/su15118724

**Chicago/Turabian Style**

Lu, Yan, Xuan Liu, Yan Zhang, Zhiqiao Yang, and Yunna Wu.
2023. "Investment Efficiency Assessment Model for Pumped Storage Power Plants Considering Grid Operation Demand under Fuzzy Environment: A Case Study in China" *Sustainability* 15, no. 11: 8724.
https://doi.org/10.3390/su15118724