Wind Power Utilization Research Articles

Theoretical analysis and economic evaluation of wind power consumption by electric boiler and heat storage tank for distributed heat supply system

The intermittency and volatility of wind power and the characteristics of the operating mode of cogeneration units pose certain challenges to the wind power consumption of the power grid. To optimize the performance of the power and heat combined operation system and maximize the wind power consumption, this paper establishes a mathematical model for each component of the cogeneration system, including the thermal dynamic characteristics of the heat network, buildings, cogeneration units, electric boiler, and heat storage tank. At the same time, a scheduling optimization model is proposed, which considers the power load demand, and wind power output of the regional heating system. The research results provide insights and optimal dispatching strategies for ensuring the reliable operation of the power system and heating system and realizing the efficient utilization of wind power. This paper verifies the effectiveness and feasibility of optimizing the cogeneration system and provides a practical solution to the challenge of cogeneration economics.

Mixformer: Mixture transformer with hierarchical context for spatio-temporal wind speed forecasting

Wind energy has attracted more and more attention due to its sustainability and pollution-free nature. As wind energy is highly dependent on wind speed, wind speed forecasting is of great importance for fully harvesting wind energy and ensuring the stability and reliability of wind energy systems. By accurately predicting the future wind speed, we can make efficient power schedules and consequently improve the utilization of wind power. Although existing forecasting methods have achieved satisfactory wind forecasting performance, they may still fail to discover the intricate spatio-temporal dependencies obscured in entangled patterns. To resolve this issue and further improve the prediction accuracy, we propose Mixformer, a novel mixture Transformer with hierarchical context for spatio-temporal wind speed forecasting. Mixformer first applies seasonal-trend decomposition, and then employs an MLP to predict the trend part and an attention model to predict the seasonal part. Besides, Mixformer innovatively proposes a spatio-temporal Gaussian mixture attention (ST-GMA) layer, which fuses the periodic temporal and long-term spatial context. To capture intricate long-term spatial characteristics, Mixformer extracts global information by the Dynamic Time Warping algorithm. Moreover, with the ST-GMA layer, Mixformer builds a hierarchical encoder–decoder architecture to fully utilize the context at different scales for seasonal forecasting and further enhance the spatio-temporal modeling. Empirical experiments on four real-world benchmark datasets show that Mixformer yields the lowest prediction errors with the MAE scores of 1.66, 1.68, 3.14 and 0.70 and the RMSE scores of 2.07, 2.01, 3.99 and 0.98, and improves the prediction accuracy by 8.43%, 5.36%, 4.14%, 6.57% in term of MAE scores and 9.18%, 6.92%, 4.01%, 5.75% in term of RMSE scores compared to state-of-the-art methods, which demonstrates the superiority of Mixformer. In a nutshell, Mixformer presents a promising method for spatio-temporal wind speed forecasting and may achieve desirable performance in real-world applications of wind power systems.

High-performing honeycomb-structured triboelectric nanogenerator enhanced by triple electrodes for utilizing wind power

The utilization of wind power and other renewable resources is attracting more and more attention worldwide in response to climate change. However, the majority of energy-converting facilities are usually frail and susceptible to natural factors, which leads to inefficient and inconsistent operation. Here, originating from bionics and nanotechnology, the honeycomb-structured triboelectric nanogenerator with triple-electrode is proposed, permitting long-term efficient and stable working cycles. A simple power management strategy is implemented to enhance the output current by 42.1%. The overall structure exhibits high power density (291.5 W/m3) and motivating ability under low rotational speed (60 rpm), excellent force resistance and specific energy absorption (4.03 ×104 J/m3), as well as flexible integration. Further, a wireless wind speed detection system is managed to monitor the changeable wind conditions intelligently. This work illuminates a feasible and effective solution for converting wind power into electricity on a large scale, providing a feasible solution to the energy crisis.

State-of-the-art review of micro to small-scale wind energy harvesting technologies for building integration

The utilisation of wind power in buildings has gained significant interest, but deploying wind turbines in built environments presents unique challenges due to highly turbulent wind patterns. Existing small wind turbines may not be as efficient in such complex conditions, and their transient loads and vibrations can compromise their durability. This study aims to assess the recent status, challenges, and limitations of building-integrated wind turbines and micro or small-scale wind-induced vibration technologies to enhance their performance, efficiency, reliability, and cost-effectiveness. The research evaluates advancements, applications, and technical features that optimise these technologies to function effectively in non-uniform wind flows and a wide range of wind speeds. Modeling conventional systems, including horizontal axis and vertical axis wind turbines, is well-established using computational fluid dynamics and blade element momentum methods. Micro or small-scale wind-induced vibration technologies have demonstrated power outputs ranging from milliwatts to kilowatts, making them suitable for powering actuators and low-powered sensors used in buildings. The study emphasises the importance of harnessing wind velocity acceleration induced by the building's roof shape when incorporating wind energy harvesting technologies. Nevertheless, research on wind-induced vibration harvesting primarily takes place in controlled environments, neglecting the influence of real buildings. This represents a significant research gap, considering the potential for wind-induced vibration technologies to provide power to off-grid communities and facilitate building integration. The lack of comprehensive analysis concerning the energy, economic, and environmental aspects of micro-energy harvesting technologies hinder their widespread adoption and a comprehensive understanding of their potential. Addressing these research gaps is essential to promote the implementation and efficacy of micro-scale wind energy harvesting technologies in various real-world scenarios.

Low-carbon economy dispatching of integrated energy system with P2G-HGT coupling wind power absorption based on stepped Carbon emission trading

To improve the renewable energy consumption capacity of integrated energy system (IES) and reduce the carbon emission level of the system, a low-carbon economic dispatch model of IES with coupled power-to-gas (P2G) and hydrogen-doped gas units (HGT) under the stepped carbon trading mechanism is proposed. On the premise of wind power output uncertainty, the operating characteristics of the coupled electricity-to-gas equipment in the system are used to improve the wind abandonment problem of IES and increase its renewable energy consumption capacity; HGT is introduced to replace the traditional combustion engine for energy supply, and on the basis of refined P2G, a part of the volume fraction of hydrogen obtained from the production is extracted and mixed with methane to form a gas mixture for HGT combustion, so as to improve the low-carbon economy of the system. The ladder type carbon trading mechanism is introduced into IES to guide the system to control carbon emission behavior and reduce the carbon emission level of IES. Based on this, an optimal dispatching strategy is constructed with the economic goal of minimizing the sum of system operation cost, wind abandonment cost, carbon trading cost and energy purchase cost. After linearization of the established model and comparison analysis by setting different scenarios, the wind power utilization rate of the proposed model is increased by 24.5%, and the wind abandonment cost and CO2 emission are reduced by 86.3% and 10.5%, respectively, compared with the traditional IES system, which achieves the improvement of renewable energy consumption level and low carbon economy.

Clearing method of regional power spot market based on blockchain and distributed data security reading algorithm

Abstract With the progress of society, the supply of electricity has become an inevitable choice for the development of all walks of life. The stability, safety, and economic dispatch of the electric energy system directly impact the entire country’s economic development, from national defense, military, and even people’s daily life, all closely associated with the smooth running of the network. In the aspect of power grid planning and operation, the economic security dispatching problem of power system is a very typical optimization problem. The problem is how to maximize the operating cost of the system under the premise of satisfying the system’s load limit and safety and stability. Due to the rapid development of power technology, the research on power system security and economic planning is essential. As an important means to promote China’s energy structure adjustment and promote the supply side structural reform, the regional spot electricity market is playing an increasingly important role in building a resource optimization allocation mechanism, improving China’s energy resource allocation efficiency, and promoting social and economic development. However, the development of China’s regional spot power market is still in its infancy, and the transaction price of the regional spot power market is quite different from that of other countries. It was given these problems, this article discusses the use of particle swarm algorithms for secure and economic scheduling of power systems in the context of securely reading blockchains and distributed data. The research results showed that: The introduction of environmental pollution penalty programs improved the priority dispatch of wind and photovoltaic power when considering environmental penalty programs and backup penalties for wind and photovoltaic power. The setting of the coefficient of the environmental penalty term depended on the designer’s emphasis on the priority scheduling of wind power and photovoltaic (PV) power generation (PG), and the standby capacity penalty clause achieved reasonable dispatch and utilization of wind power and PV PG, which reduced the dramatic fluctuations and intermittent volume of the system, and facilitated safe and consistent operation of the network. The research of this paper shows the positive relationship between the blockchain and distributed data security reading algorithm and the clearing method of regional spot power market, and points out a new method for its development.

Short-term wind speed prediction based on fractal dimension-variational mode decomposition and general continued fraction

Accurate wind speed prediction is significant to maintain the stable power system operation and enhance wind power utilization efficiency. However, most of wind speed prediction models cannot well fit the variation pattern of wind series due to its random and chaotic characteristics. This study proposes a novel wind speed prediction model incorporating fractal dimension (FD) and variational mode decomposition (VMD) and general continued fraction (GCF). More specifically, the fractal feature of wind speed series is analyzed, and the parameter determination strategy for VMD based on fractal feature of wind series is developed to overcome the problem of ambiguous mode parameter K for VMD, so that the relatively regular modes can be extracted from the raw wind series. To well capture the variation characteristics of wind series, a novel GCF model is derived on the basis of the inverse difference quotient theory, and the structure parameters of GCF model are determined by the bats algorithm (BA). To verify the accuracy and stability of the proposed model, several experiments involving comparisons with some mainstream models are executed on five wind speed datasets, and the proposed model outperforms comparative models with mean absolute percentage error reduction of 0.48 %–74.44 %. The results of the experiments indicate the proposed model has great capacity of capturing the variation characteristics of wind speed series.

Research on the optimal planning method of hydrogen-storage units in wind–hydrogen energy system considering hydrogen energy source

Utilizing wind power (WP) for hydrogen production can alleviate wind curtailment and improve wind energy utilization. The optimal planning of hydrogen-storage units(HSUs) in wind–hydrogen energy system(W-HES) will affect its economic operation. This paper proposes a W-HES model comprising WP, HSUs, and loads. We then utilize clustering algorithm-based WP and power load scenario division method. And taking the minimum investment, operation, and maintenance cost of W-HES as the objective function, use the particle swarm optimization(PSO) algorithm to optimize the planning of HSUs of W-HES. Finally, we investigate the impact of diverse hydrogen energy sources and daily hydrogen load variations on the optimal planning outcomes of HSUs. It will provide a valuable insights for the planning and configuration of HSUs in W-HES.

Design and Key Technology of Energy Management System Based on Wind Storage System

With the goal of “carbon peaking and carbon neutrality” and the proposal of building a new power system, more and more research and applications of wind power supporting energy storage have been conducted in scientific and technological research and engineering construction. The energy management system technology of wind storage system plays a key role in improving system operation efficiency, improving grid security and wind power utilization, and reducing the cost of the whole life cycle. This paper sorts out the development trend of energy management systems, introduces the management objects, system architecture, network architecture, and functional architecture of the wind storage system energy management system, and finally expounds on the key technologies of the wind storage energy management system.

Cost-Optimal Sector Integration and Energy Balancing Strategies for Reaching Carbon Neutrality

Sectoral integration will play a major role in the clean energy transition to increase the utilisation rates of available renewable energy sources (RES). Preliminary studies have shown that the decarbonisation of power generation can be reached through well-developed technical solutions such as the integration of hydro, wind, and solar energy. However, emissions in the buildings, transport, and industrial sectors remain stubbornly high. Therefore, the electrification of these sectors and interconnection through smart grids have been identified as promising future development trends to avoid the usage of fossil fuels. The TIMES optimisation model is used to evaluate the future cost-effective pathways for reaching carbon neutrality in the Latvian energy sector. The model includes both the end-use sectors such as transport, buildings, industry and agriculture and the energy sector with a well-developed database of existing and future RES and storage technologies. The modelling framework allows for identifying the cost-optimal future energy mix by considering the electrification potential of each sector. Therefore, it allows analysing of the impact of different policy strategies at sectoral integration levels and the necessity for additional energy storage capacities. The preliminary results show that one of regret-free solutions for reaching the energy efficiency targets in 2030 is the wide expanse of heat pump utilisation in residential buildings instead of inefficient biomass boilers. The building heat supply transformation also brings higher power consumption and interacts with the wider utilisation of wind power. In addition, sensitivity analyses have been performed to evaluate the impact of high uncertainties related to fuel costs, resource availability and other conditions.

Data‐driven chance‐constrained dispatch for integrated power and natural gas systems considering wind power prediction errors

AbstractStochastic wind power prediction errors hurt the normal operation of integrated power and natural gas systems (IPGS). First, the data‐driven stochastic chance‐constrained programming method is applied to deal with wind power prediction errors, and its probability distribution is accurately fitted by variational Bayesian Gaussian mixture model with massive historical data. In addition, the data‐driven chance constraints of tie‐line power and reserve capacity of gas turbine are built. Next, to utilize wind power more reasonably, the operational characteristics and optimal commitment of power‐to‐hydrogen devices are considered and modelled in proposed strategy to reflect the actual situation of IPGS. Then, the original complicated dispatch problem is converted into a tractable second‐order cone programming problem via convex relaxation and quantile‐based analytical reformulation techniques. Finally, the effectiveness of the proposed strategy is validated by numerical experiments based on a modified IEEE 33‐bus system integrated with a 10‐node natural gas system and a micro hydrogen system.

Intelligent optimal scheduling strategy of IES with considering the multiple flexible loads

As the energy system continues to evolve and advance, a relatively single energy system gradually turns to the comprehensive energy system. With the advancement of technology related to electric vehicle networks progresses, the flexible load in the power system has been significantly improved, and there will be more and more schedulable resources in the power system. On this basis, the paper mainly studies the integrated energy system including the power station of electric driven vehicles and a variety of flexible loads. First, an intelligent energy system model is built, including wind power, ES, cogeneration units, gas boilers, etc. Secondly, according to the flexible load response of electricity, heat and gas, the dynamic response of flexible loads such as electricity, heat and natural gas is incorporated into the optimal scheduling of the integrated energy system, and a model has been created for optimizing the integrated energy system with the goal of minimizing the system operational expenses. Finally, YALMIP is utilized to formulate the problem during modeling, while CPLEX is employed as the solver to find a solution. Through the example calculation, the system operation cost is reduced by 13.04%, the wind power consumption rate is increased by 8.65%, and the peak valley difference is reduced by 24.58%. This approach has been demonstrated to lower the overall operational expenses of the system, as well as assist in smoothing out peak and off-peak electricity demand, and increase the utilization of wind power.

Multi-objective coordinative scheduling of system with wind power considering the regulating characteristics of energy-intensive load

Energy-intensive load (EIL) has excellent regulating potential in the utilization of wind power: it not only offers high flexibility and large power capacity but also features significant price sensitivity. Without considering the production tasks and the regulating characteristic of energy-intensive load, the current scheduling approach is difficult to implement. A novel multi-objective coordinative scheduling approach is proposed in this paper for wind-power utilization considering the regulating models of energy-intensive load to guarantee the benefits of both power system and energy-intensive load, which can greatly improve the willingness of energy-intensive load to participate in scheduling. Firstly, A general model of regulating characteristics for energy-intensive load is given based on production process. Next, based on this modeling, a coordinative scheduling model is established with three layer. Layer A determines the total tasks of load side and generating side with the goal of minimizing the wind curtailment. Layer B and layer C make decomposition optimization to thermal power units and load control units with the goal of minimizing the generation cost and load-adjustable cost, respectively. Finally, a case study to verify the modeling is presented. The study shows that the proposed method can significantly improve the utilization of wind power at lower cost on the basis of ensuring the production requirements and benefits of energy-intensive load.

Optimization and analysis of an integrated energy system based on wind power utilization and on-site hydrogen refueling station

An integrated energy system coupled with wind turbines and an on-site hydrogen refueling station is proposed to simulate the future scenario, which can meet the demands of cooling, heating, power and hydrogen. The system was modeled to calculate the capacity and annual operation of each equipment with the total annual cost as the optimization objective. This study evaluates the performance of the system based on the results. When the system is configured with 0–10 wind turbines, the economics, energy consumption and carbon emissions improve as the scale of wind turbines increases. Energy utilization and wind power utilization are above 66.79% and 99.73%, respectively. The on-off coefficient of the power generation unit can affect energy efficiency. When the system contains 5 turbines, 91% of the hydrogen can be self-produced with the minimum amount of energy redundancy.

The Most Promising New Energy Source—Wind Power

Energy is an important part of the development of human society, but due to the large consumption of oil, coal and other resources, it also brings environmental pollution. Therefore, people have higher and higher requirements for environmental protection and sustainable development. Renewable energy plays a key role in meeting climate change agreement targets, increasing energy security, improving access to electricity and reducing fossil energy consumption. Wind power is a sustainable energy source. Because it is environmentally friendly and rich in resources, scientists have spent thousands of years looking for an effective method. This paper mainly introduces the development of wind power utilization and generation, wind navigation aid, wind water diversion and wind heat. In addition, the present situation, advantages and disadvantages of these technologies are described in detail, and the future development of wind power generation is briefly described. Hopefully this article will give a general idea of what wind power can be used for.

Research on energy utilization of wind-hydrogen coupled energy storage power generation system

The world is rich in renewable energy, and wind power generation accounts for a large proportion of renewable energy generation. The coupling of hydrogen energy and wind power generation will effectively solve the problem of energy surplus. In this study, a simulation model of a wind-hydrogen coupled energy storage power generation system (WHPG) is established. The effects of different operating temperatures on the hydrogen production and electricity consumption of alkaline electrolyzer, and on the electricity generation and hydrogen consumption of the fuel cell are studied. The suitable operating temperatures of the electrolyzer and fuel cell are determined. The energy management strategy of the coupled system is proposed considering the operating characteristics of the electrolyzer, fuel cell and hydrogen storage tank. Finally the economics of hydrogen energy storage systems are analyzed. The study shows that: (1) At the various operating temperatures, the maximum difference the electrolyzer is at 40 °C and 100 °C electrolyzer reduces electricity consumption by 0.26% and increases hydrogen production by 3.7%. (2) At different operating temperatures, the maximum difference the electrolyzer is at 30 °C and 100 °C. Fuel cell increases electricity production by 30.2% and reduces hydrogen consumption by 14.4%. (3) When the users’ demand for electricity is the same, the uncoupled system 1-hour surplus electricity is about 19.5 times the coupled system 1-hour surplus electricity, the uncoupled system 1-hour deficit electricity is about 1.54 times the coupled system 1-hour deficit electricity. (4) The hydrogen storage system has a net present value of 2347,681 ¥, a dynamic payback period of 15.3 a and an internal rate of return of 11%, the coupled system has a better economics. The WHPG improves wind power utilization and power supply stability.

Research on large-scale wind power consumption in the electricity market considering demand response and energy storage systems

Large-scale wind power integration brings great challenges to power system operation. The use of large-scale wind power in the electricity market has become a concern for many researchers. Demand response (DR) and energy storage systems (ESSs) play crucial roles in the consumption of large-scale wind power. In this paper, a detailed DR model is established, including price-based demand response (PBDR) and incentive-based demand response (IBDR). IBDR contains load shifting (LS) and load curtailment (LC). The IBDR model in this study not only includes its bidding and market clearing but also contains relevant constraints: maximum/minimum duration time, shifting/curtailment gap time, and shifting/curtailment frequency. A two-stage trading method, including a day-ahead (DA) market and a real-time (RT) market, is proposed. The method contains various market participants: conventional units (CUs), rapid adjustment units (RAUs), wind power, ESS, and multiple types of DR. The roles and economic benefits of various market participants in the consumption of large-scale wind power are analyzed in an IEEE 30 bus system, verifying the accuracy and validity of the model. The best DR scale and the suggestions of ESS are given. The results show that the proposed method can effectively utilize wind power and decrease system costs.

The Impact of Wood Fibers in Composite Panels Made from Recycled Fiberglass Wind Turbine Blades

The utilization of wind power has increased almost exponentially during the last decade, leading to the growth in both the number and size of wind turbines. Modern turbine blades are typically made of fiberglass sandwiched around a balsa wood (BW) core. With an increase in the use of wind energy a collateral issue of what to do with the large and voluminous wind turbine blades (WTB) that reached end-of-life has arisen. Through previous research, we developed a recycling process that will keep these turbine blades out of the landfill by considering recycled wind turbine blades as a feedstock for second generation composite panels. The objective of this research is to further the research by understanding the effect that different compositions of wood and fiberglass have on the properties of these panels. Through testing, it was found that the addition of balsa wood increases the modulus of rupture (MOR) and the modulus of elasticity (MOE). The internal bonding (IB) strength values are well above that of typical particle board. All panels tested were visibly more resistant to water sorption than typical particle board. The thermal conductivity for all samples was within the typical range for particleboard. Fire test result indicates that the addition of balsa wood increases the heat and visible smoke release rate of composites.

The pricing method for abandoned wind power contract between wind power enterprises and desalination plants in bilateral transactions

In Northeast China’s electric power auxiliary service market, guiding interruptible load users to participate in bilateral transactions is an effective measure to ease the difficulty of grid peak regulation and improve the utilization rate of wind power. Aiming at the lack of theoretical guidance in the current bilateral transactions, this paper proposes a two-stage pricing (TSP) method. Firstly, the freshwater supply and demand balance model of the desalination plant is constructed. The upper-level optimization model of bilateral transaction for profit maximization of the desalination plant is constructed. Then, considering the profit distribution among transaction parties and constraints on wind power utilization, a low-level calculation model of wind power pricing is constructed. Finally, the TSP method is applied to the numerical analysis of bilateral transaction between a desalination plant and a wind power company. The TSP method jointly optimizes the dispatching scheme between the variable speed pump and the water storage tank of the desalination plant. Under the constraints of reasonable profit distribution and wind power utilization, the transaction price finally converges to a range acceptable to both parties. The TSP method can effectively improve the utilization rate of wind power and optimize the flexibility of energy utilization. • A detailed mixed-integer linear programming (MILP) model is developed for desalination plants. • A model for seawater desalination plants to participate in bilateral trading markets is proposed. • A TSP method for calculating the price of bilateral transactions is proposed. • The TSP method can effectively optimize the flexibility of energy utilization.

Analysis of electricity prices for power supply toward a social optimum for installed wind and solar power utilization

Analysis of electricity prices for power supply toward a social optimum for installed wind and solar power utilization