DOI: 10.3303/CET25120059 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Paper Received: 21/04/2025; Revised: 10 September 2025; Accepted: 11 October 2025 
Please cite this article as: Hang J., Li J., Liu P., Zhang G., Liu H., 2025, Techno-economic and Environmental Feasibility of Grid Integrated 
Wind Power for Energy-Intensive Industry Under Policy and Market Uncertainties, Chemical Engineering Transactions, 120, 349-354  
DOI:10.3303/CET25120059 
  

 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 120, 2025 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Bing Shen How, Viknesh Andiappan, Denny K.S. Ng, Hon Loong Lam, Petar S. Varbanov 

Copyright © 2025, AIDIC Servizi S.r.l. 

ISBN 979-12-81206-21-2; ISSN 2283-9216 

Techno-economic and Environmental Feasibility of Grid-

integrated Wind Power for Energy-intensive Industry Under 

Policy and Market Uncertainties 

Jihong Hanga, Jinze Lia,*, Pei Liub, Guosheng Zhanga, He Liua 

aResearch Institute of Petroleum Exploration and Development, Beijing 100083, China 
bState key Lab of Power System Operation and Control, Tsinghua BP Clean Energy and Education Centre, Department of  

 Energy and Power Engineering, Tsinghua University, Beijing 100084  

 lijz2022@petrochina.com.cn 

Considering the increasing energy costs and decarbonization requirements of the energy sector, economical 

and sustainable power supplies have gained significant attention for the long-term development of energy-

intensive industries. With advancements in wind power generation technology, the integration of local wind 

resources present a viable solution for providing clean power for industrial production while reducing electricity 

costs, grid dependence, and emissions. This study aimed to develop an assessment method to evaluate the 

techno-economic feasibility and environmental benefits of a large-scale grid-integrated wind power plant for 

industrial applications. In this study, a case study of oilfield electrification in Northeast China was conducted. 

The internal rate of return (IRR) was used as the primary indicator for techno-economic evaluations. Additionally, 

a sensitivity analysis was conducted to investigate the impact of wind curtailment and carbon price variations 

on the IRR of the proposed power plant. The results indicated that despite the wind curtailment challenge, the 

wind power plant maintained an IRR exceeding 6%, with carbon benefits of approximately 32,000 t CO2 

reduction per year and nearly $440,000 in annual revenue, demonstrating the economic viability and 

sustainability of large-scale wind power plant deployment for energy-intensive industrial applications. 

1. Introduction 

Given the global energy structure's accelerating transition towards low carbonization, the construction of clean 

energy facilities connected to existing grids has become an integral component in the development of a modern 

energy system that is characterized by safety, efficiency, and environmental sustainability (Li et al., 2025). 

According to the IEA report, industrial energy consumption accounts for >70% of the total energy consumption 

globally, and carbon emissions from the energy sector comprise 85% (IEA, n.d). Given its status as the primary 

domain of energy consumption and the predominant contributor to greenhouse gas emissions, the industrial 

sector is currently grappling with dual challenges: the need to manage energy costs and the mandate to reduce 

carbon emissions. Against this background, exploring a green development path that considers both energy 

cost optimization and carbon emission reduction synergy has become a key issue for the energy transition of 

the industrial sector. 

In recent years, renewable energy sources, particularly wind and solar power, have notably increased. 

According to statistics from the International Renewable Energy Agency (IRENA), the new installed capacity of 

renewable energy in 2024 reached 585 GW globally, accounting for 92.5% of the new power installed capacity. 

Photovoltaic power and wind power contributed 451.9 GW and 113 GW, respectively (IRENA, 2025). Despite 

the continuous growth in installed capacity, the development of renewable energy is encumbered by systemic 

challenges. On the one hand, the lagging development of grid infrastructure results in inadequate capacity for 

absorbing new energy, with a significant portion of new energy unable to be connected to the grid 

(Farrokhabadi et al., 2020). On the other hand, the carbon trading market has a substantial positive impact on 

the development of new energy. However, the cooperative development between the current carbon market 

mechanism and renewable energy projects is incomplete, and the value of environmental rights has not been 

349



effectively internalized into project economic benefits, thereby exacerbating investment uncertainty (Xu and 

Yang, 2024). The present technical and economic evaluation system does not adequately account for these 

practical constraints, resulting in deviations in life-cycle assessment. 

A comparison of wind power generation with other renewable energy sources reveals several distinctive 

advantages. These include a reduction in land use and a decrease in costs due to technological advancements, 

such as increased single-unit capacity, enhanced output stability, and improved adaptability to specific 

conditions (Enevoldsen and Xydis, 2019). According to data from IRENA, the global onshore wind power unit 

installation cost decreased by 49% (from $2,272 to $1,160 per kW) and the levelized cost of electricity (LCOE) 

decreased by 70.3% (from $0.111 to $0.033 per kWh) between 2010 and 2023 (IRENA, 2024). Currently, grid-

integrated wind turbine units have become the prevailing configuration as they can reduce energy loss and 

enhance power supply reliability (Farrokhabadi et al., 2020). Nevertheless, the translation of cost benefits into 

viable investment opportunities is encumbered by two primary constraints. First, wind power curtailment due to 

physical grid limitations is a risk. Second, environmental benefits cannot be reflected owing to the absence of a 

carbon market pricing mechanism. These challenges result in deviations from traditional cost-benefit analyses, 

particularly in the context of the rapid growth of carbon trading on the carbon market. 

Considering these issues, this study developed an economic feasibility assessment method for renewable 

energy grid-integrated power generation projects. This assessment method incorporated carbon market benefit 

and policy change considerations. The internal rate of return (IRR) was employed as a pivotal indicator for 

economic analysis, and sensitivity analysis was performed to consider the impact of feed-in tariffs and on-grid 

energy on IRR. The effectiveness and reliability of the method were demonstrated through a case study of a 

large-scale wind power project connected to the grid in a specific oilfield in Northeast China. This study provided 

quantitative support and a practical reference point for the economic analysis of renewable energy grid-

integrated power generation projects in energy-intensive industrial scenarios. 

2. Methodology 

The interaction between wind turbine units and the grid was obtained, as well as equipment maintenance 

records through on-site tracking investigation. Several key technical and economic parameters were acquired, 

including equipment purchase costs and full life cycle operation and maintenance costs. Utilizing feed-in tariffs 

and on-grid energy, the revenue of wind turbine units throughout their life cycle was calculated. The IRR is a 

pivotal indicator in economic feasibility analyses. When constructing the discounted cash flow model for the full 

life cycle, the carbon benefits were also considered. The dynamic carbon benefits that the wind farm could 

obtain were calculated based on the CO2 reduction of the project and the dynamic carbon price on the carbon 

market. Furthermore, a sensitivity analysis was performed to assess the impact of policy alterations on the 

economic viability of the project, with the feed-in tariff and on-grid energy serving as the primary sensitivity 

analysis variables. 

The IRR was defined as the discount rate that resulted in a net present value of zero for the project. This formula 

demonstrated the net value changes at each timeline throughout the entire life cycle of the project. The net 

value change was defined as the net cash inflow of each period minus the net cash outflow of each period. The 

net cash inflow encompassed the project's alternative electricity income, output tax, and carbon emission 

reduction income. The specific calculation formula is as follows: 

∑
𝐶𝑡

(1 + 𝐼𝑅𝑅)𝑡

𝑛

𝑡=1

− 𝐶0 = 0 (1) 

where C0 ($) is the initial investment and construction cost, Ct ($) is the net cash flow change in period t, and n 

is the time of the project. IRR (%) is the internal rate of return of the project, which is the interest rate that 

causes a net present value of zero. Ct ($) includes the project's net cash inflow, Ci(t), and outflow, C0(t), and the 

specific formula is: 

𝐶𝑡 = 𝐶𝑖(𝑡) − 𝐶0(𝑡) (2) 

where the formula for Ci(t) is: 

𝐶𝑖(𝑡)  =  𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠𝑒𝑙𝑙𝑏𝑎𝑐𝑘  +  𝑇𝑎𝑥𝑣𝑎𝑡,𝑜𝑢𝑡𝑝𝑢𝑡  +  𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝐶𝑂2
 (3) 

The formulas for the revenue from returned electricity, Revenuesellback; output tax, Taxvat,output; and carbon 

emission reduction income, 𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝐶𝑂2
, were: 

350



𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠𝑒𝑙𝑙𝑏𝑎𝑐𝑘 = 𝑃𝑟𝑖𝑐𝑒𝑠𝑒𝑙𝑙𝑏𝑎𝑐𝑘 × 𝐸𝑠𝑒𝑙𝑙𝑏𝑎𝑐𝑘 (4) 

𝑇𝑎𝑥vat, output = 𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠𝑒𝑙𝑙𝑏𝑎𝑐𝑘 × 𝑟𝑣𝑎𝑡,𝑜𝑢𝑡𝑝𝑢𝑡  (5) 

𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝐶𝑂2
= 𝑃𝑟𝑖𝑐𝑒𝐶𝑂2

× 𝑀𝐶𝑂2
 (6) 

where Pricesellback is the feed-in tariff, Esellback is the on-grid energy, rvat, output is the output tax rate (set at 13%), 

𝑃𝑟𝑖𝑐𝑒𝐶𝑂2
 is the carbon price which changes dynamically over time, and 𝑀𝐶𝑂2

 is the carbon emission reduction 

quantity. 

 

The specific formula for the net cash outflow C0(t) was: 

𝐶0(𝑡)  =  𝐶𝑔𝑜𝑜𝑑𝑠  +  𝑉𝑖𝑛𝑝𝑢𝑡  +  𝑇𝑎𝑥𝑣𝑎𝑡  +  𝑇𝑎𝑥𝑐𝑖𝑡  +  𝑇𝑎𝑥𝑜𝑡ℎ𝑒𝑟 (7) 

Cgoods represents operating costs, while Vinput represents input VAT, Taxvat represents value-added tax, Taxcit 

represents corporate income tax, and Taxother represents other taxes. 

 

The formula for input, VAT Vinput, was: 

𝑉𝑖𝑛𝑝𝑢𝑡 = 𝐶𝑔𝑜𝑜𝑑𝑠 × 𝑟𝑡𝑎𝑥,𝑣𝑎𝑡,𝑖𝑛𝑝𝑢𝑡 (8) 

Where the input VAT rate, rtax, vat, output, was set at 5%. 

 

The formula for the value-added tax amount, Taxvat, was: 

𝑇𝑎𝑥𝑣𝑎𝑡  =  𝑉𝑜𝑢𝑡𝑝𝑢𝑡  −  𝑉𝑖𝑛𝑝𝑢𝑡 (9) 

The formula for the corporate income tax amount, Taxcit, was: 

𝑇𝑎𝑥𝑐𝑖𝑡 = (𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠𝑒𝑙𝑙𝑏𝑎𝑐𝑘 − 𝐶𝑡𝑜𝑡𝑎𝑙) × 𝑟𝑡𝑎𝑥,𝑐𝑖𝑡 (10) 

where Ctotal represents the average annual total cost, and the corporate income tax rate, rtax, cit, was set at 25%. 

 

The formula for other taxes, Taxother, of the project was: 

𝑇𝑎𝑥𝑜𝑡ℎ𝑒𝑟 = 𝑇𝑎𝑥𝑣𝑎𝑡 × 𝑟𝑜𝑡ℎ𝑒𝑟 (11) 

The rate of other taxes, rother, was set at 12%. 

3. Case Study 

3.1 Site description 

The study site is situated within the confines of the oilfield production area (45° to 50° N). The climate in this 

region exhibits distinct seasonal characteristics, featuring high wind speeds in spring and autumn and low wind 

speeds in winter and summer.  

 

Figure 1: Annual Average Wind Speed at Different Heights of Anemometer Towers in 2024 

6.32

6.44

6.56

6.67

6.87
6.93

6

6.2

6.4

6.6

6.8

7

A
n

n
u

al
 a

v
er

ag
e 

w
in

d
 s

p
ee

d
 (

m
/s

)

Height of Anemometer Tower (m)

110 120 130 140 160 166

351



The assessment of wind energy resources in the region revealed the project area was particularly conducive to 

wind energy production. At an altitude of 100 m, the wind power density in this area ranges from 250 to 330 

W/m2, with an average wind speed of 6.1 to 7.0 m/s. The annual average wind speeds measured at different 

heights in 2024 are shown in Figure 1. The annual cumulative hours of effective wind speed (3-25 m/s) in this 

region are greater than or equal to 5,200 h, demonstrating the resource endowment suitable for the construction 

of a large-scale wind farm. 

3.2 Technical and economic parameters of wind turbines and grid conditions 

The technical and economic characteristics of various units, the projected demand, and the accessibility of the 

grid were comprehensively evaluated. Power generation, unit investment, and technical maturity of different 

wind turbine units were considered, and two wind turbine units with a power of 6,250 kW and a hub height of 

160 m were proposed. The technical and economic parameters of the wind turbines are delineated in Table 1. 

Table 1: Technical Parameters of Wind Turbines 

Content Value 

Cut-in wind speed (m/s) 2.5 

Cut-out wind speed (m/s) 20 

Safe wind speed (m/s) 52.5 

Rotational speed (rpm) 361 

Blade diameter (m) 204 

Hub height (m) 160 

Single-unit capacity (Mw) 6.25 

Cost of wind turbine ($/kW) 271 

Number of units 2 

 

The calculated annual theoretical power generation of the project based on the local wind energy resources was 

55.52 GWh. After considering realistic and objective factors, including but not limited to blade contamination, 

wind turbine unit utilization rate, on-site power consumption, line loss, and climate impact, the total reduction 

coefficient was 27 %. The annual on-grid energy was 40.53 GWh, and the equivalent full-load operating hours 

were 3,242 h. The oilfield site of the proposed project has its own power transmission and distribution network 

facilities for production energy use. The electricity generated by the project is transmitted to the substation via 

a 35 kV collection line and subsequently integrated into the grid. Currently, the oilfield is in the nascent stage of 

green power substitution (renewable energy power generation project). The scale of on-grid renewable energy 

remains relatively constrained, precluding the emergence of large-scale wind power curtailment issues due to 

its impact on the grid.  

4. Results and Discussion 

4.1 Feasibility analysis 

An economic feasibility analysis was conducted for the proposed wind power grid-integrated project under the 

base scenario (feed-in tariff of 0.068 USD/kWh and annual on-grid energy of 40.53 × 106 kWh). The initial 

investment was 17.89 × 106 USD, and its annual operating cost was 0.68 × 106 USD. The IRR was projected to 

reach 7.6 %, which exceeded the industry benchmark of 6 % when carbon benefits were not accounted for. 

In addition, the fluctuations in carbon prices in relation to the evolution of the regional carbon trading market 

were examined to calculate the dynamic carbon benefits. The initial carbon price was set at $12 per t, with an 

annual increase of $2 per ton, culminating in a stabilized price of $ 20 per t after a five-year period. The project 

was estimated to generate 40.53 × 106 kWh of clean wind power annually, concurrently reducing CO2 emissions 

by approximately 32,000 t y-1. The findings revealed that incorporating a carbon trading mechanism within the 

base scenario of allowing for carbon benefits significantly enhanced the project's resilience. The introduction of 

the carbon trading mechanism increased the IRR of the base scenario by 55 %, reaching 11.8 %, and 

maintained an IRR of 9.1 % in the extreme scenario. This indicated that the calculation method of "electricity 

revenue + carbon emission reduction revenue" effectively enhanced the project's IRR. 

4.2 Sensitivity analysis 

The sensitivity analysis focused on the impact of fluctuations in on-grid energy and tariffs on the project's IRR. 

Considering the anticipated advancements in the local grid's capacity to accommodate renewable energy 

generation, the reduction in the on-grid energy due to variations in wind curtailment rates was 0-20 %. 

Concurrently, the range in tariff fluctuations was ±15 % of the benchmark price, which was 0.068 yuan. The 

352



outcomes are illustrated in Figure 2, with the horizontal axis representing the feed-in tariff and the vertical axis 

representing the reduction due to wind curtailment. The IRR values exhibited a clear increase from dark blue to 

dark red. These findings indicated that the IRR was considerably influenced by the simultaneous fluctuations in 

tariffs and wind curtailment rates. When the tariff was at the benchmark level of 0.068 yuan, for every 5 % 

increase in the wind curtailment rate (corresponding to a 5 % reduction in the amount of electricity fed into the 

grid), the IRR decreased by an average of 0.65 %, gradually decreasing from 11.8 % (0 % wind curtailment) to 

9.1 % (20 % wind curtailment). The downward pressure on tariffs exerted a significant inhibitory effect on the 

IRR. When the tariff decreased to 0.0578 yuan (-15 %) and the wind curtailment rate reached 20 %, the IRR 

declined to a minimum of 7.4%, a decrease of 4.4 % compared to the benchmark scenario. However, when the 

tariff declined by 10 % ($ 0.0612), under the same wind curtailment rate, the IRR decreased to 8.0 %. 

Conversely, an increase in tariffs partially offset the impact of the wind curtailment rate. For example, when the 

tariff increased by 15 % ($0.0782), even if the wind curtailment rate increased to 20 %, the IRR was maintained 

at 10.8 %, which was 1.7% higher than that of the scenario with the same wind curtailment rate under the 

benchmark tariff. When the tariff increased by 5-15 %, the decrease in the IRR due to shifts in the wind 

curtailment rate stabilized at 0.7 % to 0.9 % for every 5 % increase in the wind curtailment rate. This suggested 

that the positive impact of rising tariffs on project returns had a diminishing marginal effect. This was because, 

under elevated tariffs, the revenue loss per kilowatt-hour increased, thereby intensifying the adverse impact of 

the wind curtailment rate on the IRR. The project's capacity to withstand risk was substantially influenced by the 

interplay between tariffs and wind curtailment rates. Relying exclusively on an increase in tariffs is challenging 

in terms of continuously offsetting the risk posed by increasing wind curtailment rates. A heightened level of 

scrutiny is warranted when considering the possibility of a concurrent decline in tariffs and a high wind 

curtailment rate because this scenario posed a pronounced risk to the project's financial stability. 

 

Figure 2: Sensitivity Analysis Result 

4.3 General observations 

The impact of changes in external conditions (allowable on-grid energy) and policy changes on the economic 

feasibility assessment of grid-integrated wind power projects should be prioritized. Wind power project 

constructors and investors should enter long-term contracts to mitigate the risks of feed-in tariff volatility. 

Concurrently, at the policy level, power market reform and the associated subsidy policies for the utilization of 

renewable energy must be monitored closely. To ensure the sustainable development of the renewable energy 

industry, policymakers must perform regional grid absorption capacity assessments and rationally judge medium 

and long-term grid planning and corresponding incentive policies based on future development needs. 

5. Conclusion 

This study explored the discrepancy between conventional economic assessment methodologies and actual 

development outcomes. An economic feasibility assessment method for grid-integrated renewable energy 

projects that considered both carbon market benefits and policy changes was proposed. A case study of a large-

scale wind power project in an oil-gas field in China was conducted. The findings of the research indicated that 

in the absence of integrating carbon benefits, the project's capacity to withstand risk was considerably 

353



constrained. Furthermore, when the wind curtailment rate was >10 % or the feed-in tariff declined by a similar 

margin, the IRR approached a critical value of 6 %, which is considered the industry standard for viability. In a 

worst-case scenario, where the wind curtailment rate reached 20 % while the feed-in tariff remained constant, 

the IRR declined to 4.4 %, rendering the project unfeasible from an investment perspective. This underscored 

the substantial impact of wind curtailment on project feasibility assessments. In the same extreme scenario, 

incorporating carbon benefits (the dynamic discounting of carbon quota trading benefits) can augment the 

project's IRR to 9.1 %, mitigating the constraint of relying solely on electricity revenue. This study quantified the 

marginal contribution of carbon prices to revenue and considered changes in external conditions. The economic 

feasibility assessment method for grid-integrated renewable energy projects was improved, providing scientific 

support for investment decisions in developing projects in energy-intensive industries (such as oil and gas, 

chemical, and metallurgical industries). Future research should combine regional carbon market trading rules 

and renewable energy consumption policies as well as consider dynamic carbon prices and real-time interaction 

with the grid to enhance the depiction of real-world scenarios. 

Author contributions 

Jihong Hang: Methodology, Investigation, Data Curation, Writing-original Draft. Jinze Li: Methodology, 

Investigation, Project Administration, Conceptualization, Writing – Review & Editing. Pei Liu: Writing-review & 

editing, Validation. Guosheng Zhang: Validation, Funding acquisition. He Liu: Supervision, Funding Acquisition. 

Acknowledgments 

The authors gratefully acknowledge support from The National Natural Science Foundation of China (72140005). 

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	Techno-economic and Environmental Feasibility of Grid-integrated Wind Power for Energy-intensive Industry Under Policy and Market Uncertainties