Wind Power: The Way-Forward in India

Energy storage system is an effective means to overcome the fluctuation of wind power generation and improve electrical network stability. This paper briefly introduces the impact of wind power generation on the grid and different battery energy storage technologies first. Demonstration projects of combined wind power generation and energy storage systems is then discussed. This is followed by an outline of three main operating modes of the combined wind power generation and energy storage using batteries, including smoothing wind power fluctuation, tracking wind power schedule output and load shifting. Current status of control strategies and storage capacity for the combined wind power generation and energy storage systems are then presented. Finally, further research needed for the combined system is discussed and improvement on the economic aspects is concluded to be a key aspect for future research.

Offshore oil and gas platforms can accelerate their shift towards lower greenhouse gases emissions by combining wind power generation and energy storage systems. However, the variability of the wind resources and power demand, and the limited storage capacity make the design of the system particularly challenging. We present a modelica library at its early stage of the development and yet with promising results. The model will be used to simulate the dynamic of the whole system for a long period of time using simplified power components and balanced micro grid. This paper shares some preliminary results by applying the model on a data set of wind resources and power demand from the North Sea. The results are the power system dynamics and an approximation of the mass of greenhouse gas emissions. On the long term the model will be applied to determine the right control and optimization strategy to control the energy system towards lower greenhouse gas emissions without compromising the balance between the power supply and demand.

With the fast development of clean energy in China, the conflict between limited peak load regulation capability and the increasing installed wind power capacity became more and more obvious. Two different wind power integration dispatching modes were proposed in this paper, meanwhile, the wind power integration capacity and system economy under different scenarios, which have different wind power penetration and energy storage system (ESS) capacity, were also analyzed. As indicated in the example analysis, the ESS can significantly enhance the wind power integration capacity; and the economical wind power integration dispatching mode is the most suitable choice for the power grid in wind-rich area.

Different from conventional generators, wind power is an intermittent energy source, power system dispatch and control is confronted with new challenges. This paper establish the mathematical model of wind power and energy storage system for simulation and analysis, and study the wind power prediction using statistical methods and physical methods, and study the key technologies of automatic generation control and automatic voltage control which were in the large-scale wind power and energy storage system. The results show that the wind power prediction is reasonable for grid, and the power quality and stability of wind farm connected to power grid can be well improved by battery energy storage.

In view of uncertainties caused by large-scale wind power integration, energy storage system (ESS) is being considered to stabilize the fluctuation of wind power. In this paper, the influence of ESS on power system operation with wind power is analyzed in detail, and an economic dispatch (ED) model with wind power and ESS is proposed based on scenario set. First, the initial scenario set of wind power output is generated by the Monte Carlo sampling. To overcome the shortcoming of heavy dependence on the initial clustering centers, which usually leads to unstable clustering results, the k-means clustering is improved by combining self-organizing feature map neural network and particle swarm optimization (PSO). Then, the initial scenario set is reduced based on this improved k-means clustering method. Finally, an ED model solved by PSO is used to minimize the comprehensive power generation cost based on the reduced scenario set. Taking IEEE-39 bus system as an example, the scenario-set-based ED model is implemented in this paper. The simulation results show that, when solving the ED problem with wind power and ESS, the proposed method considering scenario reduction makes not only the clustering index better, but also the results of ED more reasonable.

Wind power intermittency represents one of the major challenges facing the future growth of grid-connected wind energy projects. The integration of wind turbines and energy storage systems (ESS) provides a viable approach to mitigate the unfavorable impact on grid stability and power quality. In this study, an economic model predictive control (MPC) framework is presented for an integrated wind turbine and flywheel energy storage system (FESS). The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a baseline wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is investigated. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load with negligible effect on the wind energy harvested.

Empowering the electric grid: Can SMES coupled to wind turbines improve grid stability?

Frequency regulation in Multi-region Interconnected Power Systems (MIPS), incorporating wind turbine systems, energy storage units, and demand response, is a challenging control problem. The problem involves maintaining grid stability, integrating variable renewable energy sources, enhancing grid resilience, optimizing energy storage and demand response capabilities, and ensuring regulatory compliance. Effective frequency regulation is a key problem for reliable and sustainable power system operation. In this paper, complex and uncertain dynamics in various components of a MIPS are modeled using multiple first-order dynamic fractional-order Type-2 Fuzzy Logic Systems (T2-FLSs). The models are evaluated, and the best possible dynamic model is chosen. With the best possible model, an optimal controller is designed. The stability and optimality analysis are presented through a Linear Matrix Inequality (LMI) approach. The adaptive laws of T2-FLSs are derived such that some LMI-based conditions are satisfied. The designed controller does not depend on the dynamics of MIPS. The uncertainties of time-varying load, wind energy, and solar power are modeled using T2-FLSs. The suggested LMI technique presents adaptation laws for T2-FLSs to ensure stability in the presage of natural disturbances and errors. The designed scheme is validated by applying to a practical 39-bus IEEE test system that includes the wind farms, demand response, and energy storage systems. The simulation results under various conditions verify the usefulness of the suggested controller. The comparisons with conventional controllers demonstrate that the suggested approach is more effective under uncertainties and natural perturbations.

During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest.

Current trend in offshore wind energy sector and material requirements for fatigue resistance improvement in large wind turbine support structures – A review

This study presents a technoeconomic analysis of a hybrid wind‐PV (photovoltaic) power plant (HPP) compared to onshore wind power plants (WPPs) and photovoltaic power plants (PVPPs) in the Nordic electricity market, focusing on locations in Finland and Sweden. Wind power capacity has recently increased significantly in the Nordics, increasing the profit cannibalization of wind power. Renewable energy subsidies have been phased out in Finland and Sweden, thus new wind and PV power value creation is formed from the power market. The PV power capacity has also encountered significant growth in the Nordics. However, the capacity is still relatively low, allowing more revenue for produced PV power compared to wind power. The lower PV power profit cannibalization has increased interest in HPPs instead of WPPs. This contribution studies the economic feasibility of wind and PV power in changing market conditions in the Nordic electricity market. The market operation is modeled with three different configurations including selling all the power into the day ahead spot market and baseload or pay‐as‐produced power purchase agreement (PPA). In addition, a battery energy storage system (BESS) investment is analyzed using the operating strategy of shifting production to more profitable spot price hours. This study shows that due to the profit cannibalization and high cost of capital, the power plants are currently not profitable in the Nordic electricity market except when the bidding area has high average spot prices. The worst profitability was with WPPs when exposed to the market shape risk and with PVPPs when pay‐as‐produced PPA was agreed upon due to the higher levelized cost of electricity. However, the PV power profit cannibalization is expected to increase in the future as more PVPPs operate in the Nordic power market. Thus, the PVPP shape risk may increase in the future as well.

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

In view of the frequency fluctuation of the micro-grid system containing wind power, hybrid energy storage system composed of batteries and supercapacitors is adopted to coordinate the output, so as to maintain the frequency stability of the micro-grid and provide the possibility for the micro-grid to further absorb wind power and other clean energy. Firstly, by analyzing the characteristics of wind power output, the power deviation signal of the system is decomposed into low-frequency and high-frequency parts through wavelet packet decomposition, so as to maximize the consumption of wind power output power on the premise of meeting the stability of the system. Then, the high frequency part of the power gap is further divided to determine the initial FM power distribution scheme of the energy storage system. Finally, the energy storage output is modified by the Logistic regression function to take into account both the energy storage adaptive frequency modulation and the energy storage charged state self-recovery. Example analysis shows that the proposed control strategy can realize the optimal distribution of wind power, ensure the full utilization of wind farm output, improve wind power grid connection capacity, and increase efficiency and economy.

This paper proposes a coordinated operational strategy of energy storage system (ESS) and wind farm to reduce wind power spillage and alleviate wind power fluctuation. Firstly, power curve of a wind farm, in the form of an equivalent wind turbine, is determined by least square fitting. Based on the power output characteristic of the wind farm and historic operating data, the statistical properties of wind power spillage and fluctuation can be obtained. Secondly, the target for wind farm and ESS power output is calculated. Power generation/absorption capabilities of ESS and available power output reducing range of the wind farm are quantified as well, considering the operational constraints of ESS and dispatched wind power output. Finally, a coordinated operational strategy is developed not only to adjust the combined ESS and wind farm to meet the dispatch requirement, but also to ensure ESS and the wind farm to satisfy operational constraints. Case studies are conducted on a practical wind farm with battery energy storage system installed, which demonstrate that the coordination of ESS can greatly boost the revenue and improve power quality of wind farm.

Offshore wind power technology has matured significantly and now directly competes with conventional and onshore wind power generation. Thanks to continuous technological developments and significant cost reduction, offshore wind power is closing the gap with the onshore wind power about the levelized cost of electricity; however the technology challenges in the offshore environment still poses threats to the long-term operational reliability and profitability of offshore wind farm projects. This article focuses on one such threat: harmonic resonance in the offshore grid and presents an analytical solution to identify and mitigate it by applying advanced harmonic modelling of an offshore wind turbine. The analytical derivation of the frequency dependent positive and negative sequence impedance of a converter harmonic model of a 8MW generic wind turbine is presented. It concludes by comparing the frequency domain converter harmonic model of a generic 8MW offshore wind turbine with its time domain counterpart as well as the ideal current source model (conventional solution) under the distorted grid condition. The results obtained confirm that the converter harmonic model demonstrates superior accuracy when compared to the ideal current source model (conventional solution) for low order harmonics resonance interaction assessment. To conclude, the discrepancies in the results obtained from the time domain and the frequency domain models respectively deserves further investigation. Particularly the frequency dependent impedance as derived from the average model of the associated power electronics should be examined in detail as its validity depends strongly on the phenomena one is interested in (typically the average model provides sufficient accuracy when the frequency of interest under investigation is ten times smaller than the switching frequency).