Variable Wind Power Research Articles

Evaluation of the risk and benefit of the complementary operation of the large wind-photovoltaic-hydropower system considering forecast uncertainty

The complementary operation of wind, photovoltaic and hydropower systems has the potential to increase the integration of renewable energy sources into an existing grid. However, the high variability and forecast uncertainty of wind and photovoltaic power may pose potential risks to the grid and cascade reservoirs. In this study, the benefit and risk of the complementary operation of the wind-photovoltaic-hydropower hybrid system are evaluated. First, an optimal day-ahead complementary operation model is proposed to guide the daily operation of the hybrid system. Then, an optimal real-time load allocation model is developed to deal with power generation derivation resulting from the uncertainty of wind and photovoltaic power forecasting. Finally, the benefit and risk of the complementary operation of the wind-photovoltaic-hydropower system are evaluated. A case study is performed with the wind-photovoltaic-hydropower system in the Yalong River basin of China. The results show that (1) the total power generation, the power generation profit, and the utilization efficiency of electricity transmission lines are significantly increased, but the profit of hydropower stations is sacrificed to compensate for wind and photovoltaic power generation; and (2) the negative effect of the variability of wind and photovoltaic power generation on the power grid can be alleviated; (3) reliable power supply can be achieved, and power loss occurs mainly in the flood season and the maximum load loss is acceptable; and (4) it may lead to an increase in release variation, especially in the dry season, and thus flood control gates and hydropower generating units need to be operated more flexibly.

Hedging the Risk of Wind Power Production Using Dispatchable Energy Source

Abstract In this paper we advance a nonlinear optimization problem for hedging wind power variability by using a dispatchable energy source (DES) like gas. The model considers several important aspects such as modeling of wind power production, electricity price, nonlinear penalization scheme for energy underproduction and interrelations among the considered variables. Results are given in terms of optimal co-generation policy with DES. The optimal policy is interpreted and analyzed in different penalization scenarios and related to a 48 MW hypothetical wind park. The model is suitable for integration of wind energy especially for isolated grids. Some probabilistic results for special moments of a Log-Normal distribution are obtained; they are necessary for the evolution of the optimal policy.

Wind Power Smoothing With Energy Storage System: A Stochastic Model Predictive Control Approach

The utilization of energy storage system (ESS) is an effective method for dealing with the randomness and variability of wind power. Therefore, improving the coordination between ESS and wind power is a direction worthy of research. This study develops a two-layer stochastic model predictive control (SMPC) method for wind power smoothing on different time-scales. The proposed optimization framework smooths wind energy by adjusting the charge and discharge power of hybrid ESSs; moreover, it combines the SMPC approach and the chance constraints to address the uncertainties of wind energy. Furthermore, the previous states are taken into account, in addition to states within the rolling time horizon, to obtain optimal control of the hybrid ESSs, and capacity planning for hybrid ESSs is conducted simultaneously. The numerical results obtained through amplitude-frequency simulation comparison prove that the proposed method is superior to the conventional method in terms of minimizing the frequency fluctuation of wind power and the size of the ESS.

Assessing Low Frequency Variations in Solar and Wind Power and Their Climatic Teleconnections

Assessing Low Frequency Variations in Solar and Wind Power and Their Climatic Teleconnections

Evaluating the potential of offshore wind energy in the Gulf of Oman using the MENA-CORDEX wind speed data simulations

The MENA-CORDEX (the Middle East and North Africa-COordinated Regional Downscaling Experiment) wind speed data at the height of 10 m is converted to the turbine hub-height for estimating the mean wind power in the Gulf of Oman. The results show high spatial variability of the historical and future mean wind power projection. Furthermore, the impact of climate change on the mean wind power (under the representative concentration pathway 8.5, RCP8.5, scenario) is found to be less than 5%, which indicates the sustainability of wind renewable energy. Based on the wind power distribution, bathymetry, and distance from the coast, five sites are selected in the Gulf of Oman as tentative energy hotspots to provide a detailed assessment of the directional variability of wind power for the historical and future periods. Significant variability of the directional distribution of wind power is found in the five study sites, which make it imperative to optimally design wind turbines and farms to achieve the best efficiency. The findings also indicate that the main direction and magnitude of wind power in the five sites under the RCP8.5 climate change scenario will remain almost the same as those of the historical period. Overall, the sustainability of power production under climate change impacts is promising to plan for wind energy extraction in the Gulf of Oman.

An enhanced Borg algorithmic framework for solving the hydro-thermal-wind Co-scheduling problem

An enhanced Borg (EBorg) algorithm has been proposed to solve the dual-objective short-term hydro-thermal-wind co-scheduling (HTW-CS) problem, aiming at minimizing the cost and emissions associated with electric power generation while satisfying various hydraulic and electric constraints. The sophisticatedly designed evolution framework of the EBorg consists of i) ε-dominance-based archive, ii) Pareto-dominance and crowding-distance-based population updating mechanism and iii) auto-adaptive multi-operator recombination, which guarantees the convergence capability and diversity and can avoid blindness selection of recombination operators. Meanwhile, a randomness-priority-based repairing constraint handling technique (CHT) is developed, and the performances of another two popular existing CHTs incorporated in the proposed search framework are compared and discussed. The proposed approaches are tested on the widely used HTW-CS case studies, and the results show that the proposed EBorg can achieve a decrease of cost and emissions compared with the existing methods. Additionally, energy performance in the case studies has shown an average 50% decrease of emissions with wind power integration, while the total cost is largely dependent on the cost coefficients related to wind uncertainty. Varying wind power cost coefficients and water inflow levels will result in different wind power and hydropower integration.

Variability in Wind Energy Generation across the Contiguous United States

AbstractERA5 provides high-resolution, high-quality hourly wind speeds at 100 m and is a unique resource for quantifying temporal variability in likely wind-derived power production across the United States. Gross capacity factors (CF) in seven independent system operators (ISOs) are estimated using the location and rated power of each wind turbine, a simplified power curve, and ERA5 output from 1979 to 2018. Excluding the California ISO, the marginal probability of a calm (zero power production) is less than 0.1 in any ERA5 grid cell. When a calm occurs, the mean co-occurrence across wind-turbine-containing grid cells ranges from 0.38 to 0.39 for ISOs in the Midwest and central plains [Midcontinent (or Midwest) ISO (MISO), Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT) region], increasing to 0.54–0.58 for ISOs in the eastern United States [Pennsylvania–New Jersey–Maryland interconnection (PJM), New York ISO (NYISO), and New England ISO (NEISO)]. Periods with low gross CF have a median duration of ≤6 h, except in California, and are most likely during summer. Gross CF exhibit highest variance at periods of 1 day in ERCOT and SPP; on synoptic scales in MISO, NEISO, and NYISO; and on interannual time scales in PJM. This implies differences in optimal strategies for ensuring resilience of supply. Theoretical scenarios show adding wind energy capacity near existing wind farms is advantageous even in areas with high existing installed capacity (IC), while expanding into areas with lower IC is more beneficial to reducing ramps and the probability of gross CF falling below 20%. These results emphasize the benefits of large balancing areas and aggregation in reducing wind power variability and the likelihood of wind droughts.

A residential community-level virtual power plant to balance variable renewable power generation in Sweden

Power systems with large shares of variable renewable electricity generation, i.e., wind and solar power, require high flexibility in both power generation and demand. Heat pumps and combined heat and power units within district heating systems, and thermal storages have previously been studied for their potential to increase the flexibility of the energy system. When using these technologies for power balancing, they must be operated in a non-standard way with switched merit-order. This study hypothesizes that a residential area could form a local operated entity, i.e., a virtual power plant, that provides power-balancing services to a national power system. The hypothesis is tested with a case-study in Sweden where a combined heat and power unit, heat pumps, a local heat distribution system, and a thermal storage constitute the local entity. A simulation of the energy balances in the system, with optimization of storage size, was performed. The results show that all power surpluses in the system are consumed by the heat pumps. 43% of the annual and 21% of the electricity peak load are covered by the combined heat and power unit. It is concluded that an inter-seasonal thermal storage is crucial for the system's flexibility. Also, large electricity surpluses, if converted to heat and stored, limit the ability of the virtual power plant to utilize the combined heat and power unit for power balancing at a later stage. Despite this, a local virtual power plant can provide increased flexibility by offering power-balancing services to the power system.

Mitigation of offshore wind power intermittency by interconnection of production sites

Abstract. This study uses a unique set of hourly wind speed data observed over a period of 16 years to quantify the potential of collective offshore wind power production. We address the well-known intermittency problem of wind power for five locations along the Norwegian continental shelf. Mitigation of wind power intermittency is investigated using a hypothetical electricity grid. The degree of mitigation is examined by connecting different configurations of the sites. Along with the wind power smoothing effect, we explore the risk probability of the occurrence and duration of wind power shutdown due to too low or high winds. Typical large-scale atmospheric situations resulting in long term shutdown periods are identified. We find that both the wind power variability and the risk of not producing any wind power decrease significantly with an increasing array of connected sites. The risk of no wind power production for a given hour is reduced from the interval 8.0 %–11.2 % for a single site to under 4 % for two sites. Increasing the array size further reduces the risk, but to a lesser extent. The average atmospheric weather pattern resulting in wind speed that is too low (too high) to produce wind power is associated with a high-pressure (low-pressure) system near the production sites.

Limited Power Point Tracking for a Small-Scale Wind Turbine Intended to Be Integrated in a DC Microgrid

Limited power point tracking (LPPT) is emerging as a new technology for power management controllers for small-scale wind turbines (SSWTs) thanks to its advantages in terms of operation flexibility, economy and system security. LPPT operates in such a way that power requested by the user can be extracted from the wind turbine while respecting constraints. However, operating in LPPT mode still requires a deep understanding to obtain a compromise between minimizing power oscillations and transient response. For that, three LPPT power control strategies for an SSWT intended to be integrated in a direct current (DC) urban microgrid are investigated. These methods concern perturb and observe (P&O) with fixed step size, P&O based on Newton’s method and P&O based on the fuzzy logic (FL) technique. The experimental results highlight that all methods function correctly and reach the limited power point (LPP). The FL method improves dynamic performances with more steady oscillations around LPP compared to fixed step size and Newton’s methods. The sudden variation of wind velocity and power lead us to conclude that the FL method ensures a good balance between reducing oscillation of wind turbine (WT) output power around the operating point and convergence of rising time toward LPP.

Techno-economic evaluation of transportable battery energy storage in robust day-ahead scheduling of integrated power and railway transportation networks

In recent years, the use of renewable energy (RE) sources has an upward trend due to the environmental and economic reasons. However, finding a solution method to manage the fluctuating nature of these sources and more efficient utilization of total generation capacity are challenging problems, especially when there is a high penetration of REs in power systems. On the other side, the network congestion in power grids is another obstacle that inhibits the full utilization of REs. Battery-based energy storage transportation using a railway network leads to emerging high-efficiency technology called transportable battery-based energy storage (TBES) system. TBES technology is a practical and economical option to reduce transmission congestion and increase the utilization of the energy storage systems’ (ESSs’) capacity by providing additional facility to transfer power. As a flexible resource, TBES can adapt to the load profile of the system at peak-load hours and result in cost reduction and more prudent management of wind power variations. The demand response (DR) program is another solution to deal with wind power uncertainty and has a considerable impact on reducing power network congestion and total operation cost by peak-load shaving. Hence, to overcome the mentioned challenges and obstacles, this paper focuses on solving a robust network constrained unit commitment (NCUC) with TBES and DR programs. To manage the wind power uncertainty, an information gap decision theory (IGDT)-based robust optimization technique is proposed to obtain maximum robustness against the wind power uncertainty. The advantage of the presented model is that neither probability distribution functions (PDFs) nor scenario generation are required. The 6-bus power system coordinated with the 3-station railway network is applied as the test system. Numerical studies pointed out that integrating TBES technology in IGDT-based robust NCUC problems and considering the DR program has improved the power system’s flexibility and uncertainty management of wind power, alleviated the congestion, and reduced the optimized cost. Simulation results revealed a 6.5% cost reduction by applying TBES and also 11.3% cost decrement by developing coordinated TBES and DR.

Grid Synchronization of WEC-PV-BES Based Distributed Generation System Using Robust Control Strategy

In this article, a renewable (solar and wind) energy sources based distributed generation system (DGS) is controlled to operate in the grid-connected (GC) mode and an islanded mode using the robust and fast IAPV (Improved Affine Projection Versoria) and proportional resonant based control strategy. Due to the use of IAPV-based control in the GC mode, the grid current becomes immune to the dc offset and the other nonfundamental harmonics during an unbalanced load, which significantly improves the grid current quality. It also presents the flexible operation of DGS in the GC mode using the variable and constant power injection into the grid, which ensures the grid stability during large and fast wind and solar power variations. Moreover, a modified second-order sequence frequency locked loop is used to improve the synchronization and seamless mode switching (islanded to GC and vice versa) performance by quickly and accurately estimating the phase angle and frequency at distorted and unbalanced grid voltages. Simulation and test results validate the microgrid operation and robustness of the microgrid control.

The annual cycle and intra-annual variability of the global wind power distribution estimated by the system of wind speed distributions

The intermittent nature of wind energy is a major challenge transforming the energy sector from fossil fuels to renewables. Depending on the location, results from previous studies show that the availability of wind energy can strongly vary over a year. However, although global temporal wind speed fluctuations are complex on the monthly and seasonal scales, they have been rarely quantified so far. Thus, the goals of this study were to assess the annual cycle and intra-annual variability of wind power around the world. A comprehensive dataset of more than 7000 globally distributed near-surface wind speed time series was analyzed. After extrapolation to a typical wind turbine hub height of 120 m, the monthly and seasonal mean wind speed, wind power density, and intra-annual variability were calculated. The system of wind speed distributions, which consists of the Burr-Generalized Extreme Value, Kappa, and Wakeby distributions, was fitted to all wind speed time series and used to estimate wind turbine related capacity factors. The greatest global wind resource was found for spring (global mean capacity factor: 0.272). In summer, the global wind resource decreased by 20.7%. The results reveal the greatest intra-annual variability in regions affected by the Indian monsoon circulation.

Optimal Placement and Sizing of DG considering Power and Energy Loss Minimization in Distribution System

Optimal placement of Distributed Generation (DG) in the distribution network is a significant solution to resolve the power loss issue. Selection of the optimal locations and sizes of the DG is a practical problem and challenging job to achieve the minimum loss. In this work, the optimal location and appropriate size of the DGs have been found out to minimize the total active power loss of the distribution system with less penetration level of the DG considering of 24 hours duration. A modified search algorithm has been proposed in this paper which is capable to obtain the best solutions. Moreover, several reputed soft computing techniques have been applied to solve the problem and validate the optimal results. Technical aspects like energy losses have been minimized instead of power loss and practical factors like hourly basis solar output, wind generation and load variation have been considered to make this work more realistic. The solution techniques have been tested on the IEEE 33, IEEE 69 and 118 radial distribution test bus systems and results have been compared with recent literature. The quality of the results establishes the efficiency of the proposed modified algorithm to solve the optimal location and sizing problem with the effect of PV and wind power variation along with the variable load.

Climatology of wind variability for the Shagaya region in Kuwait

Electrical system operators utilizing wind energy production need accurate wind power forecasts to prepare for changes in power production. To understand the forecast problem and sources of forecast uncertainty, a climatology of the region of interest is needed. For Shagaya Renewable Energy Park in Kuwait, seasonal and diurnal wind patterns and the atmospheric phenomena that cause them are identified using observations from meteorological towers, surface weather stations, and wind turbines. A setup conducive to shamals increases hub-height wind speed by up to 3 m s-1 from May to August and thereby increases power production of the Shagaya wind turbines by 24%, in a season with higher energy demand for cooling homes and businesses. Near sunset, wind speed ramps up and remains faster throughout the night due to the prevalent nocturnal low-level jet. Wind speed ramps back down after sunrise when the nocturnal boundary layer is eroded by convective turbulence, which leads to more short-term fluctuations in wind speed and wind power during the day. Given knowledge on these seasonal and diurnal cycles of short-term and long-term wind power variability, wind power has clear potential to meet a significant portion of Kuwait's energy needs.

District energy system modeling and optimal operation considering CHP units dynamic response to wind power ramp events

With the increase in clean energy penetration, its power curtailment during operation is made increasingly evident. In this circumstance, it is imperative to address the conflict between inflexible combined heat and power (CHP) units and variable wind and solar power. In this paper, a novel coordinated optimal operation strategy of a district energy system with CHP, wind power and energy storage is established with the following characteristics: the optimal installed capacity of electric energy storage (EES) is determined to smooth the high frequency fluctuation of wind power generation; the CHP units achieve dynamic response to wind power ramp events timely after EES smoothing; and the CHP model with start-stop and dynamic response mechanism is able to reduce the installed capacity of electric boiler (EB) significantly. One-week operation data is adopted in the case studies to increase the reliability of simulation results. The simulation results show that with EES integration, high frequency wind energy curtailment is reduced, the capability of peak regulation and power ramp of CHP units is enhanced by start-stop and the proposed dynamic response mechanism and environmentally sustainable and socially resilient cities is promoted.

Network and Reserve Constrained Economic Analysis of Conventional, Adjustable-Speed and Ternary Pumped-Storage Hydropower

With increasing renewable penetration and projected increase in natural disasters, the reliability and resiliency of a power system become crucial issues. As network inertia drops with increasing penetration of renewables, operators search for flexible resources that can help cope with a disruptive event or manage renewable intermittency. Energy storage is a solution, but the type of storage solution needs to be profitable to exist in the current and upcoming power markets. Advanced pumped-storage hydropower (PSH) is one solution that can help cope with such requirements, which will in turn help to increase the renewable penetration in the system. This paper qualitatively compares the revenue earning potential of PSH configurations, including, adjustable-speed PSH (AS-PSH) and ternary PSH (T-PSH) in comparison to conventional PSH (C-PSH) from the arbitrage and regulation markets, with and without the presence of wind penetration. In addition, a framework for quantitative analysis of any energy storage system has been proposed. A 24-bus RTS system is studied with summer and winter variations in load and wind power. Through revenue and operational mode analysis, this paper reveals that T-PSH has the highest revenue earning potential, which is mainly due to its ability to operate with a hydraulic short circuit.

Optimal operation modeling and synergetic dispatch of source-load-storage for high renewable energy penetration

ABSTRACT With the increase in clean energy penetration, its power curtailment during operation is made increasingly evident. In this circumstance, it is imperative to address the conflict between inflexible combined heat and power (CHP) units and variable wind and solar power. With regard to the district energy system with high penetration renewable energy, a new source-load-storage synergetic optimization operation dispatch mode is explored in this paper. It demonstrates such characteristics as the full consumption of clean energy, the CHP units with lower power output and better capability of deep peak regulation, and the small installed capacity of electric energy storage (EES) devices. Besides, this model is capable to balance heat and power demands at any time throughout the day with a variety of different energy sources, including CHP, wind, photovoltaic (PV), electrical boilers (EBs), EES, and thermal energy storage (TES) devices. Moreover, with the competitive swarm optimization (CSO) algorithm applied to solve this model, the convergence performance is improved and the computation time is reduced compared to other heuristic algorithms. Relative to the other three simulation results, the single cost of simulation result can be reduced by as much as 29.3%-34.0% at most by applying the model proposed in this paper. Moreover, this model is verified as feasible.

Error-Based Wind Power Prediction Technique Based on Generalized Factors Analysis with Improved Power System Reliability

As a green energy source, the use of wind has been rapidly growing in recent years. Whereas wind has complex and stochastic nature hence precise wind power predictions are essential for economic operation of the wind energy systems. For utilities, the rapid variations in wind power can generate serious problem of reliability reduction. The forecasting of wind power changes allows a utility to plan the connection and disconnection of wind power generation based on forecasting wind power generation and predicted load. In this paper, an environment friendly wind power prediction technique of variable-speed wind power system is proposed. The technique is employed from the prediction algorithm to create a prediction model to get accurate power. It is authenticated on the producer power curve of the variable-speed wind system. Additionally, the technique is used in average monthly wind power prediction and the outcomes show a huge improvement in prediction accuracy using the proposed method. Further, the likely value of rated wind speed for installed wind power system in Vishakhapatnam, Bhopal, Ahmedabad, Thiruvananthapuram, Bangalore, India, are also discussed. The empirical outcomes are compared with different wind forecast models and based on the root mean square error (RMSE), the proposed model gives the perfection in prediction accuracy compared to Gaussian Processes and Numerical Weather Prediction, Wind power prediction without adjustment, Wind power prediction with adjustment, support vector machine methods. Further, the developed model is used to evaluate the annual reliability indices by convolving the predicted generation with predicted load in the selected station.

Chaotic multi verse optimizer based fuzzy logic controller for frequency control of microgrids

This paper represents an arrangement of fuzzy PD and derivative filter based PID controller (FPIDF) with its optimally designed membership functions and is employed for the load frequency control (LFC) of isolated multi- microgrids. The performance of a recently developed multi verse optimizer (MVO) algorithm is improved by introducing chaotic map appropriately in the algorithm. The improved algorithm, named as CMVO algorithm is applied to tune the proportional integral derivative (PID) controller gains for the LFC of microgrid. The superiority of the proposed CMVO algorithm is examined by its superior performance compared to MVO PID, recently published IAYA PID, JAYA PID and GA PID in the microgrid system. Further, CMVO based FPIDF with its optimized membership position (FPIDF-OM) outperforms compared to CMVO based FPIDF, IJAYA tuned FPID and FPD/PI-PD controller in microgrid system. Better dynamic performances are found with the proposed technique for stochastic type wind power, solar irradiance and load variations in the microgrid compared with FPIDF and PID. The robustness of the proposed technique is established by the sensitivity analysis. The proposed design approach has been extended to a microgrid model including biogas turbine generator, biodiesel engine generator and aqua electrolyser along with fuel cell unit. Finally, OPAL-RT based hardware-in-the-loop simulation of proposed techniques has been done.