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Recently, there has been a push by countries to diversify their energy mix considering various factors. In this regard, there have been several studies conducted to assess the potential for using sources such as wind and solar to generate supplemental energy to the already present energy generation setup. In this regard, this study explores the potential of wind for the Commonwealth of Kentucky. To perform this study, wind data were sourced for eight locations across Kentucky from the publicly accessible wind speed information present at Weather Underground for the years 2020–2021 (two years). An analysis was performed concerning the seasonal, monthly, and hourly variation in the wind speed so as to identify the expected times of sufficient wind energy generation. Moreover, a comparison of the collected data was performed with data from a home-based weather station as well as a deployed wind turbine to validate the variation pattern of the publicly sourced data. Finally, in order to investigate the variation patterns of wind and solar energy sources, a comparative analysis was also performed using data from a solar power generation plant in Kentucky. A seasonal and monthly complementarity was observed between the wind and solar energy. However, when considering daily patterns, the wind was found to follow solar generation with an offset. While further research is required, this analysis indicates that it is possible to deploy wind energy power generation projects in the Commonwealth of Kentucky. The seasonal complementary behavior of wind and solar energy can be used along with battery storage in conjunction with natural gas to provide a diversified electricity generation portfolio. [ABSTRACT FROM AUTHOR]

Unreliable resources in conventional power systems have created new challenges for the users of these systems. These sources of production, including wind and solar sources, with a significant share in the power generation of many power systems, cause problems in the safe and stable operation of power systems due to uncertainty. Therefore, it is very important to provide a method or model for safe and stable operation of power systems. The main innovation of this paper is to present a new SCUC model to maximize the flexibility of the system along with reducing the operating cost in the form of a security constrained multi-level robust optimization problem in the presence of wind uncertainty sources. Also, a set of demand response programs and rapid response hybrid cycle units are used as sources of flexibility. Accordingly, the tolerable range of uncertainty and system slope reservation is developed with a low-cost combination and with the commitment to flexible covering resources. The desired optimization problem has been solved with the help of the NCCG algorithm and MILP method. The efficiency and reliability of this proposed model have been simulated and evaluated in IEEE 6-bus and 118-bus standard power systems, and the simulation results confirm the technical and economic efficiency of this model. [ABSTRACT FROM AUTHOR]

The large shares of wind power generation in electricity markets motivate higher levels of operating reserves. However, current reserve sizing practices fail to account for important topological aspects that might hinder their deployment, thus resulting in high operating costs. Zonal reserve procurement mitigates such inefficiencies, however, the way the zones are defined is still open to interpretation. This paper challenges the efficiency of predetermined zonal setups that neglect the location of stochastic power production in the system, as well as the availability, cost and accessibility of flexible generating units. To this end, we propose a novel reserve procurement approach, formulated as a two-stage stochastic bilevel model, in which the upper level identifies a number of contiguous reserve zones using dynamic grid partitioning and sets zonal requirements based on the total expected operating costs. Using two standard IEEE reliability test cases, we show how the efficient partitioning of reserve zones can reduce expected system cost and promote the integration of stochastic renewables. [ABSTRACT FROM AUTHOR]

With developing concerns, in renewable energy sources can improve which is an increasing amount. This paper reviews both the vitality of the wind and the photovoltaic (PV) energy conversion strategies and their maximum-power-point tracking (MPPT) methods. Then, a new Grid tied wind PV cogeneration generation using back to back voltage source converters system is proposed. For the wind power generation permanent-magnet synchronous machine is used to capture the maximum wind power by using optimum speed control. For the PV power generation boost converter is adopted to harness the maximum solar power by tuning the duty cycle. [ABSTRACT FROM AUTHOR]

The energy sector is highly dependent on climate variability for electricity generation, maintenance activities and demand. In recent years, a few climate services have appeared that provide tailored information for the energy sector. In particular, seasonal climate predictions of wind speed have proven useful to the wind power industry. However, most of the service users are ultimately interested in forecasts of electricity generation instead of wind. Although power generation depends on many factors other than wind conditions, the capacity factor is a suitable indicator to quantify the impact of wind variability on production. In this paper a methodology to produce seasonal predictions of capacity factor for a range of turbine classes is proposed for the first time. The strengths and weaknesses of the method are discussed and the forecast quality is evaluated for an application example over Europe. • A method to produce seasonal forecasts of renewable generation is presented. • A unified approach that fits the specific nature of any wind farm is employed. • Some limitations of seasonal prediction systems are identified and addressed. • The generation forecasts perform better than climatology in some European regions. [ABSTRACT FROM AUTHOR]

Large-scale integration of wind generation changes the power swing characteristics of a power system and may result in the misoperation of legacy power swing protection schemes. This paper presents a qualitative study on the impact of wind generation on power swing protection. The objective is to provide an understanding of the problem through case studies and present possible solutions and adjustments in protection schemes to ensure the efficiency of protection under large-scale integration of wind generation. The misoperation of power swing protection functions, namely power swing blocking and out-of-step tripping (OST), as a result of increased wind generation levels, are shown through case studies. It is also shown that the electrical center of a power system may move due to wind generation. In this case, it would be necessary to revise the optimal location of the OST protection. Finally, the impact of various factors, such as wind generator type, control scheme and fault-ride-through function, and wind generation level and capacity are investigated to determine the key features that need to be accounted for in practical protection studies. [ABSTRACT FROM AUTHOR]

This paper presents a day-ahead coordinated scheduling method of hydro and wind power generation systems (HWPGSs) with consideration of uncertainties. In this method, we first formulate the coordinated scheduling model with two-part price and power flow constraints, which manifests the fixed and variable economic benefits as well as the secure operation of HWPGS, respectively. Then, the interval analysis is used to study the effect of uncertain wind power, water inflow, and electricity load on the coordinated scheduling model. Finally, we use a real test system in a western area of China to conduct simulation studies, which verify the effectiveness of the interval analysis and the effect of price mechanism on the day-ahead coordinated scheduling of HWPGS. [ABSTRACT FROM AUTHOR]

Demand response can reduce peak load, transfer part of peak load to valley load, and reduce system risk at peak time. In this study, a calculation model of power grid loss risk is proposed, which is suitable for evaluating the risk changes caused by the demand response, and calculating the corresponding risk value under the demand response load curve. In the calculation of demand response load, considering the impact of two measures of time-of-use (TOU) price and incentive measure, the TOU and incentive load curve are obtained based on the user's maximum benefit. In order to gain the corresponding load risk index, Monte Carlo simulation method is used, demand response load curve is taken as input, and load point fault time, load point fault rate and expected energy not serve indexes are introduced. Moreover, compared with the risk ratio of the original load curve, the simulation results verify the effectiveness of the proposed risk model, and prove that the demand response measures can transfer the risk of partial high load and balance the risk distribution. [ABSTRACT FROM AUTHOR]

The main cause for cascading failure is large-scale overload caused by localised abnormal flows. With the increase of wind power penetration, the complexity of flow distribution is strengthened. Therefore, it is necessary to study influences of site selection and permeability of wind power generation on cascading failure. An analysis method based on electric betweenness of nodes was put forward, and influences of permeability change on cascading failure on different location selection for wind power generation were researched. According to the study, it was found that when the electric betweenness was low, the overload of wind power led to declining uniformity of power flow distribution, resulting in transfer of flows to other lines. As a result, the heavy load of lines was further aggravated to promote the development of cascading failure. Simulation results of the IEEE30 system showed that with the increase of wind power penetration, the cascading failure was aggravated; and under the same permeability, the lower the electric betweenness of location selection was, the severer cascading failure would be. [ABSTRACT FROM AUTHOR]

As renewable power generation becomes more prevalent, the problem of frequency stability has become a particular concern of transmission system operators, especially those of small power transmission systems. Traditional wind generation systems do not provide frequency regulation because they are decoupled from the power grid. Therefore, as conventional thermal generators are replaced by wind generators, the issue of frequency regulation for wind generation systems has become increasingly important. To release the kinetic energy stored in the rotating mass, inertia and droop control loops can be added into the controller of a wind turbine (WT). This work proposes an advanced control strategy with the time-varying gains of two control loops. In the proposed strategy, the gains are determined based on the desired frequency-response time. Moreover, the initial gain of the control loop is determined based on the wind speed, considering the operating condition of each WT in a wind farm. The effectiveness of the proposed method is verified by using an actual power system, revealing that it can be used to improve frequency regulation in a power grid. [ABSTRACT FROM AUTHOR]

The large scale integration of wind energy generation adds a new burden to frequency regulation because of the volatility of wind power. Incorporating wind turbines (WTs) into automatic generation control (AGC) is a new approach for maintaining a satisfactory frequency regulation performance, which requires the active power control (APC) of WTs. Conventionally, the APC of WTs is achieved by pitch angle control (PAC) or rotor speed control (RSC), which respectively show a slow response and a narrow regulating range. To improve the regulation performance of variable speed WTs, a coordinated APC strategy that includes the simultaneous activation of PAC and RSC and takes full advantage of rotor kinetic energy to absorb or release extra mechanical energy is proposed in this paper. The simulations focusing on both the WT and power system levels have shown the effectiveness of proposed control strategy. [ABSTRACT FROM AUTHOR]

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Abstract: Recently, wind power generation are installed as a countermeasure for the environmental issue in Japan. However, wind power generation output is fluctuated due to wind condition. Moreover, it is some negative impact for system operation such as the economic load dispatching control and the load frequency control. In Japan, NEDO has started the project as a countermeasure for massive penetration of wind power generation in 2014, called “R&D Project on Grid Integration of Variable Renewable Energy.” In this paper, we proposed the output fluctuation suppression control method of wind power generation using the battery and forecast data of wind generation output. Specifically, the target value of wind power generation output is calculated to decrease the deviation output from fluctuation suppression code for ramp event using deterministic optimization method. The effectiveness of proposed method is evaluated through the computational simulation using forecast data and actual wind power generation output in Tohoku area. [ABSTRACT FROM AUTHOR]

Due to the liberalization of the electricity market, the traditional concepts and practices of the electrical systems have resulted in the introduction of Competitive Electricity Market (CEM). The recognition of CEM provides special consideration for the development of Renewable Energy (RE) throughout the world. The paper presents a mixed Genetic Algorithm (GA) and Optimal Power Flow (OPF) based model for determination of the optimal location and rating of Wind Power Generation (WPG). The optimization algorithm has been formulated and solved while considering the procurement cost minimization for obtaining the required energy by optimally locating the WPG in the system. The proposed mixed GA-OPF approach has been successfully applied to the modified IEEE 30-bus test system. The proposed algorithm also resulted in the prioritized list of optimal locations of WPG in the system. [ABSTRACT FROM AUTHOR]

The development of medium-/long-term studies for power-system operation and planning under the uncertainty of renewable generation is a key challenge faced by power-system agents worldwide. There is a vast literature on stochastic optimization models devoted to addressing the relevant issues on both operation and planning applications. Notwithstanding, few papers focus on addressing the gaps within the subject of joint scenario generation despite the high sensibility of stochastic optimization models with regard to their input scenarios. Characterizing wind power generation (WPG) stochastic processes to devise time- and spatial-dependent scenarios, based on simulation procedures, for time horizons of one to a few years is a difficult task. Multiple regimes and non-Gaussian distributions are two of the main issues that significantly change the risk described through generated scenarios. In this paper, a new methodology to simulate long-term joint scenarios for multivariate WPG time series is presented. The proposed framework, known as generalized auto regressive score models, is derived based on a new class of time-series model with time-varying parameters and an arbitrary non-Gaussian distribution. Our case study shows, based on real data from the Brazilian power system, that the proposed methodology is capable of producing scenarios with coherent temporal and spatial dependence that are needed in power system studies. [ABSTRACT FROM AUTHOR]

Uncertainty of the wind power output is the main influence factor for wind power utilization in the bulk power system. Because of the large capacity and the load characteristic, energy-intensive load holds great potentials to share the burden of wind power fluctuation smoothing. In this paper, a direct control scheme of the energy-intensive load power is proposed to smooth the wind power fluctuation. Based on the characteristic of the energy-intensive load production technology, the feasibility of energy-intensive load control and its influence on the production are discussed. A feedback control is designed to regulate the saturable reactor and transformer tap changer when the power support from the bulk power system is limited. Regulation capacity is analyzed quantitatively based on the energy-intensive load equivalent circuit model. A grid-connected energy-intensive enterprise driven by self-generation wind power plants and thermal power plants is studied as an example case. By the proposed energy-intensive load control scheme, power fluctuation of the wind farms can be smoothed with the minimum control cost. Besides, the regulation requirement of the bulk power system is eased correspondingly so that the utilization capacity of the power system can be improved significantly. Simulation is done on the real-time digital simulator to verify the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

• Real case studies of Tazouta and Fez rural area in Morocco. • Hybrid biomass, wind, and solar electricity generation in areas those are rich in renewable energies. • Potential of bioenergy for producing power in rural areas of Fez-Meknes region in Morocco. High dependence of Morocco's energy sector on imported fossil fuels and subsequent associated expensive import bills, as well as global agreements with greenhouse gas emission reduction, has motivated Morocco to utilize renewable energy sources such as hydro, wind, and solar for energy generation. However, in recent years, the use of wind and solar energies in Morocco has accelerated more than hydropower usage because of the reduction in water levels as a result of rainfall drop, global warming, and natural droughts. Morocco has a great potential for electricity generation from solar and wind energies because of many sunny days, vast desert areas, long coastlines, and appropriate wind blow. However, accommodations of wind and solar generating units in electric power systems are difficult because of wind speed variations, solar irradiation uncertainty, and costly energy storage systems. Regarding the huge amounts of biowaste in Morocco, power generation from biomass can resolve this problem and compensate for the decrease in wind and solar energy generation during cloudy, rainy, and/or non-windy moments. Therefore, in the present paper, the capability of hybrid electric energy generation, using biomass, wind, and solar in a Moroccan village of Tazouta and the rural area of Fez city is evaluated. The proposed mixed-integer linear programming model was implemented in A Mathematical Programming Language (AMPL) using a linear solver of CPLEX. The biomass, solar, and wind power plants are biogas units fed by cow manure, 1-kW photovoltaic (PV) modules, and 5.1-kW wind turbines, respectively. The evaluation of the results indicates that hybrid utilization of wind, PV, and biomass energy resources is a more appropriate way for electricity generation in Tazouta and Fez rural areas compared to the individual operation of wind turbines and other combinations of mentioned renewable energy sources. [ABSTRACT FROM AUTHOR]

The unit commitment is still a widely studied problem, especially when more renewable energy of stochastic character is being added to power systems. This paper proposes a model for weekly planning of systems involving hydro, wind, and thermal energy under a stochastic perspective. The proposed model follows the endogenous reserve determination criterion to achieve a simultaneous optimization of energy and reserves considering wind uncertainty, forced outages of equipment, a dc Flow model of the network, and cascaded head sensitive hydro systems, among others. The paper also develops a practical solution methodology based on outer approximation and benders decomposition. Testing has been conducted over four systems, and computational results demonstrate that the proposed model and solution are useful and effective. [ABSTRACT FROM AUTHOR]

This paper proposes a new filter design method that can smooth the wind power generation output while keeping the energy capacity and power rating of the energy storage system (ESS) small. Wind power generation causes frequency fluctuations in power systems. Therefore, in many cases, the ESS is needed for smoothing the fluctuations of wind generator output. In order to improve the performance of the ESS controlled with the conventional low-pass filter (LPF), this paper investigates other types of filters. First, the relations between filter and energy capacity/power rating of the ESS are disclosed through the worst-case study. Then, the frequency fluctuation analysis of the power system with respect to the wind power generation is carried out in order to realize a pin-point smoothing. Finally, a metaheuristic optimization method is proposed for the multiobjective design of the filter based on these relations so as to achieve an optimal tradeoff between the output smoothing and energy capacity/power rating of the ESS. It is shown via simulation analysis with real wind data that the proposed method can suppress the frequency fluctuation of the power system effectively with the ESS having smaller energy capacity and power rating. [ABSTRACT FROM PUBLISHER]

This paper addresses the stochastic security constrained unit commitment (SSCUC) problem with flexibility resources for managing the uncertainty of wind power generation (WPG). Departing from the traditional flexibility resources such as the thermal units with fast up/down spinning reserves and transmission switching (TS), this paper explores also the use of demand response (DR) and energy storage (ES) systems in an innovative integrated scheme. The proposed scheme utilizes a stochastic optimization framework to coordinate the flexibility resources dealing with the uncertainty of WPGs and equipment failures. The stochastic optimization model is formulated as a mixed-integer linear programming (MIP), and this problem is large and computationally complex even for medium sized systems. Accordingly, we present a novel accelerating decomposition technique aimed at solving this problem and reducing the number of iterations and CPU time. Numerical simulation results on the modified 6-bus system and on large-scale power systems, i.e. IEEE 118 and 300-bus systems, clearly demonstrate the benefits of applying flexibility resources for uncertainty management and the efficacy of the proposed solution strategy for large-scale systems. [ABSTRACT FROM AUTHOR]

With the incremental quantities of variable speed wind turbines (VSWT) integrated into microgrid, the frequency fluctuation and the generation efficiency decrease are caused. To solve the problem, power unreserved control has been well studied, which emulates inertia and stimulates the VSWTs to transiently release the kinetic energy stored in the rotating masses, thus providing response to the frequency excursions promptly and timely. Meanwhile, inertia control and temporary over-production (TOP) control, as two main strategies of power unreserved control, have been put forward to improve the effectiveness of frequency regulation. Nevertheless, a frequency second dip will occur during the rotational speed restoration process in both methods. Therefore, a modified control method is proposed in this paper to strike an appropriate balance between frequency second dip prevention and rotational speed recovery. Our strategy is elaborated through theoretical demonstration and it can adapt to different wind power penetration. Through explicit simulation analysis, the performance of the proposed control strategy is compared with conventional implementations of the inertia control and the TOP control. The results indicate that the modified strategy can effectively offset the frequency second dip while guaranteeing a satisfactory rotational speed restoration to maintain the frequency within an appropriate range in an islanded microgrid. [ABSTRACT FROM PUBLISHER]

Regulation is required to ensure that energy generation and demand on an electricity grid match at all times. Energy storage has been proposed to provide fast, precise regulation as wind energy and other renewable energies displace traditional generators that also provide regulation. In this investigation, different levels of regulation are offered using a 1 MW/2 MWh battery to determine the optimal offering for the system. The sodium–nickel chloride (Na-NiCl2) battery is charge rate limited, which affects the accuracy, especially at high states of charge. Offering a lower regulation capability increases the accuracy in the same state of charge range, but results in lower payments. Performing regulation behind the meter of a wind farm causes additional challenges due to the current electricity rate structure, which has a high demand charge during low wind generation periods. This causes the storage system to be limited to wind generation periods, resulting in regulation not being offered every hour. The battery achieved PJM performance scores above 90% while performing regulation, with month-long averages ranging from 59% to 63%, depending on the regulation offered. The maximum monthly revenue under the described operation, using PJM's regulation rates, is under 50% of the monthly cost of the Wind Energy Institute of Canada's USD 2.34 million dollar battery energy storage system. [ABSTRACT FROM PUBLISHER]

Summary: Most of the rural villages throughout the world are isolated from rest of the regions in accessibility to the electricity that considerably affects the sustainable development of this region. Low generation capacity addition, accessibility, and affordability of electrical power in the remote area are the major causes responsible for such situations. This long‐standing problem can be addressed through user friendly power supply from renewable power generation system with microgrid topology. In this paper a solar photovoltaic‐augmented, cogeneration‐based wind power generation scheme has been proposed for remote rural area power supply. This stand‐alone hybrid‐microgrid‐based power generation scheme will provide uninterrupted power to the under privileged village peoples at minimum cost unlike the existing utility supply. Considering, the complementary nature of the available wind and solar power, this paper also presents a coordinated control mechanism that ensures the automatic power exchange facility within the microgrid effectively. The scheme has been simulated by using MATLAB Simulink‐2016 simulation tool and practically implemented using a dSPACE CP1104 interfacing device, and the results are found satisfactory. [ABSTRACT FROM AUTHOR]

In industrial-scale wind farms, interactions among multiple turbines alter the power generation efficiency of turbines. In general, turbines in downwind rows are impacted by wind deficits, producing less power, compared to upstream turbines. Therefore, the generation performance of multiple turbines differs from one another. Moreover, the power curve of each turbine becomes heterogeneous when changes in wind direction cause some upstream turbines to become downstream turbines. This study proposes an integrative methodology that quantifies the heterogeneous wake effects over a range of wind direction by utilizing the concept of canonical models and similarity functions. We model the direction-dependent multi-turbine power curves in a Bayesian hierarchical framework and validate the performance of the proposed approach with multiple real-world data sets from industrial-scale wind farms. [ABSTRACT FROM AUTHOR]

This paper describes the demonstration and evaluation of stacking wind power time-shifting and regulation by a 1 MW/2 MWh battery energy storage system (BESS) within a 10 MW wind park. The BESS time-shifted 15.8 MWh of wind power to peak periods while responding to the automatic generation control (AGC) signals that provide regulation over the 24 day test period. Its fast response time and accurate output allowed the BESS to provide both services simultaneously. Limiting the charging to periods when wind power was available lowered the amount of time-shifting and AGC that could be provided. Some form of AGC was delivered from the BESS for 78.5% of the test period and, if it were remunerated at the PJM rate when the test was performed, it would have earned 8627 USD, with 97% from regulation and the rest from time-shifting wind power. Using PJM's performance template, the BESS averaged a performance score of 70.5% during hours when regulation was performed. This work adds to the growing empirical data that is informing models of and policy for grid storage. [ABSTRACT FROM AUTHOR]

Wind power representation is an integral part of stochastic economic dispatch (ED). Compared with the deterministic approach, stochastic ED allocates system reserves more effectively. This improved reserve strategy heavily relies on the wind power distribution boundary area that is not consistent with classical unbounded distribution models. To address this issue, this paper proposes a new probability distribution model named truncated versatile distribution (TVD) for wind power, which is bounded and more accurate than classical models. The fitting effect and mathematical analysis of TVD are thoroughly discussed. Then, we propose a novel look-ahead dynamic ED method with an adjustable confidence interval (ACI) based on TVD, which not only enables system operators to maintain an acceptable predefined level of risk, but also seeks the optimal level of risk to balance the system reserve strategy and risk of power unbalance. With ACI, TVD offers a reliable wind power representation to search for the optimal level of risk in the dispatch model. In addition, the employment of TVD can simplify the wind power uncertainties by its analytical forms. The results show that compared with other classical distribution models, the novel distribution is a more accurate representation of wind power. Moreover, the ED model results in improved economic performances by ACI compared with traditional ones. [ABSTRACT FROM AUTHOR]

This paper addresses how to extend the concept of small-signal stability region (SSSR) to that of robust small-signal stability region (RSSSR), within which the system can remain stable even under perturbations caused by uncertain and volatile nodal injections, such as renewable generation. We first employ the structured perturbation theory to formulate the perturbations of nodal injections in state space. Both the intensity and the locations of perturbations can be taken into account. Then, we leverage the stability radius theory and structured singular value theory to define the RSSSR in parameter subspace, enabling a systematic analysis of small-signal stability of power systems under perturbations in a region-wise manner. The hyperplane-approximation method can be employed to construct a linear closed-form approximation of RSSSR boundaries. Case studies on the modified two-area system and New England 39-node system illustrate the new concept of RSSSR and its potential applications. [ABSTRACT FROM AUTHOR]

This paper presents a new method to evaluate the reliability of a power system with high penetration of wind generation, considering the impact of not only the intermittence but also the low inertia characteristic of wind power. As wind generation gradually replaces conventional generation, the system stability and the reliability are negatively affected. Some of the measures employed to deal with the challenges resulting from increasing wind penetration include operating wind generators at lower levels than their available output and providing inertia so that wind generation is able to contribute to system frequency regulation. Apart from these measures, another factor that limits the amount of wind power that can be absorbed into the grid is the imposition of the frequency standard and this also affects the reliability of the system in the presence of wind penetration. The reliability evaluation approach proposed in this paper is developed using discrete convolution and implemented on an IEEE RTS-79 system with a suitable modification. Power system reliability with and without considering the impacts of wind intermittence and low inertia are compared to show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper demonstrates the operation of a 1 MW/2 MWh grid-tied battery energy storage system (BESS) in a 10 MW wind R&D park for Automatic Generation Control (AGC) for 29 days. The efficiency and utilization of the BESS in the context of regulation and grid integration are examined. The response time for the BESS is as low as one second, which is faster than the current accepted practice of a conventional generator with governor control. Using PJM's performance template gives an average performance score of 93% while the storage is providing AGC. However, because the storage system only charges when there is sufficient wind energy and spent significant time in maintenance mode, the 29-day performance average is only 65%. The battery was able to carry out some mode of AGC for 64% of the test period. When energy costs and battery degradation are considered, utilizing the battery costs USD 19,000 over the 29-day period, whereas the potential income from AGC, charging only with wind power, was USD 9,037. This 29-day demonstration shows that batteries have fast response and can perform AGC, but within a wind farm AGC is unlikely to be suitable without changes in the tariff schemes. [ABSTRACT FROM PUBLISHER]

High-level wind power integration can dramatically affect a power system's dynamic performance and introduce significant uncertainties to system's operation. This paper proposes a robust dispatch method to optimize the power system's operation state while sustaining its transient stability with highly variable and stochastic wind power generation. The problem is first modeled as an augmented optimal power flow model with uncertain variables and differential-algebraic equations. Then, the stability constraints are converted to approximately-equivalent algebraic equations based on one-machine-infinite-bus equivalence technique and trajectory sensitivity analysis. Next, the uncertain wind power generation is represented by a small number of strategically selected testing scenarios. Finally, a decomposition-based computation strategy is developed to divide the original model into a master problem and a series of slave problems which are solved iteratively. Using industry-grade system dynamic models and simulation software, the proposed method is tested on the New England 39-bus system and Nordic32 system, showing high performance on economic optimality, stability robustness, and computational efficiency. [ABSTRACT FROM PUBLISHER]

Part one of this two-part paper presents new models for evaluating flexible resources in two-settlement electricity markets (day-ahead and real-time) with uncertain net loads (demand minus wind). Physical resources include wind together with fast- and slow-start demand response and thermal generators. We also model financial participants (virtual bidders). Wind is stochastic, represented by a set of scenarios. The two-settlement system is modeled as a two-stage process in which the first stage involves unit commitment and tentative scheduling, while the second stage adjusts flexible resources to resolve imbalances. The value of various flexible resources is evaluated through four two-settlement models: 1) an equilibrium model in which each player independently schedules its generation or purchases to maximize expected profit; 2) a benchmark (expected system cost minimization); 3) a sequential equilibrium model in which the independent system operator first optimizes against a deterministic wind power forecast; and 4) an extended sequential equilibrium model with self-scheduling by profit-maximizing slow-start generators. A tight convexified unit commitment allows for demonstration of certain equivalencies of the four models. We show how virtual bidding enhances market performance, since, together with self-scheduling by slow-start generators, it can help a deterministic day-ahead market to choose the most efficient unit commitment. [ABSTRACT FROM PUBLISHER]

The wide integration of gas-fired units and implementation of power-to-gas technologies bring increasing interdependence among the natural gas and electricity infrastructures. This paper studies the equilibrium of the coupled gas and electricity markets, which is driven by the strategic offering behaviors: each producer endeavours to maximize its own profit by taking the market clearing process into consideration. The market equilibrium can be obtained from an equilibrium problem with equilibrium constraints. A special diagonalization algorithm is devised, in which the unilateral equilibrium of the gas or electricity market is found in the inner loop given the rivals’ strategies; the interactions of the two markets are tackled in the outer loop. Case studies on two test systems validate the proposed methodology. [ABSTRACT FROM PUBLISHER]

Increasing wind power (WP) integration is forcing conventional units to go through more frequent and significant cycling operations, which would accelerate wear and tear to unit components and eventually affect the unit's lifespan. In this context, this paper proposes a hierarchical scheme to control the power of plug-in electric vehicles (PEVs) to mitigate unit ramp cycling (URC) operations. A general-form representation of the URC operation is proposed for the first time. At the top level of the hierarchical scheme, a system net load variation range (NLVR) is constructed first to capture the uncertainty in WP forecasts, and then the PEV power is scheduled to reshape the NLVR so as to minimize the URC operations that can be caused by the possible net load realizations in the NLVR. Based on updated WP forecasts, the middle-level dispatch model exempts overscheduled anti-URC regulation onus on PEVs to promote PEV charging. At the bottom level, a decentralized PEV charging control strategy is used to implement the PEV power dispatch instruction. Simulation results verify that the proposed scheme can avert the URC operations effectively, while preserve most of the desired PEV charging energy. Simulation results also show that the proposed scheme is more capable of withstanding WP forecast errors compared with its deterministic version and a benchmark scheme. [ABSTRACT FROM PUBLISHER]

Decomposition methods are widely applied as a prestage of wind power prediction (WPP) to reduce the prediction errors caused by the nonstationarity and nonlinearity of wind power time series (TS); however, they cannot address the issues posed by the chaotic behavior of wind power TS. This paper, therefore, proposes a novel decomposition approach to take the chaotic nature of wind power TS into account and to improve WPP accuracy. In this decomposition approach, as a primary step, the wind power TS is separated into several components with different time-frequency characteristics (scales) by means of ensemble empirical mode decomposition. Chaotic TS analysis is then applied to determine which components are chaotic, and then singular spectrum analysis (SSA) is applied thereto. This multi-scale SSA (MSSSA) can maintain the general trend of chaotic components, which become smoother by eliminating extremely rapid changes with low amplitudes, and thus several steps ahead WPP with higher accuracy can be realized. Following the proposed decomposition, a novel short-term WPP method comprised of localized direct and iterative prediction is proposed to perform multi-step prediction for the chaotic and nonchaotic components of MSSSA, respectively. The proposed framework is finally validated using historical data related to overall wind power generation for Alberta (Canada), the Sotavento wind farm (Spain), and Centennial wind farm in Saskatchewan (Canada). [ABSTRACT FROM PUBLISHER]

Two critical issues have arisen in transmission expansion planning with the rapid growth of wind power generation. First, severe power ramping events in daily operation due to the high variability of wind power generation pose great challenges to multi-year planning decision making. Second, the long construction periods of transmission lines may not be able to keep pace with the fast growing uncertainty due to the increasing integration of wind power generation. To address such issues, we propose a comprehensive robust planning model considering different resources, namely, transmission lines, generators, and FACTS devices. Various factors are taken into account, including flexibility requirements, construction period, and cost. We construct the hourly net load ramping uncertainty (HLRU) set to characterize the variation of hourly net load including wind power generation, and the annual net load duration curve uncertainty (LDCU) set for the uncertainty of normal annual net load duration curve. This results in a two-stage robust optimization model with two different types of uncertainty sets, which are decoupled into two different sets of subproblems to make the entire solution process tractable. Numerical simulations with real-world data show that the proposed model and solution method are effective in coordinating different flexible resources and rendering robust expansion planning strategies. [ABSTRACT FROM PUBLISHER]

This work develops an under-frequency preventive control strategy for island power systems that are based on evaluating the initial one-hour-ahead operating status of the system and a real-time correction method. The developed preventive control system evaluates initial system flexibility using a forecast of net load, it includes a low-frequency preventive control strategy to ensure stable operation and to support a corrective process, and it includes an economic dispatch strategy to reduce operating costs. This system can be operated automatically, stably, and economically. [ABSTRACT FROM PUBLISHER]

This paper presents a nonlinear technique based on the sliding mode control theory for mitigation of torsional vibrations in grid-connected doubly fed induction generator (DFIG) based wind turbines. The presented method increases the lifespan of wind turbines by reducing torsional vibrations caused by mechanical or electrical disturbances. The effectiveness of the proposed technique is demonstrated on torsional vibrations caused by a voltage dip and a wind gust. In this paper, dynamics of the generator, multiinertia drivetrain, rotor- and grid-side converters, and transmission line are developed upon the 750-kW fatigue, aerodynamics, structures, and turbulence (FAST) simulator wind turbine model comprising wind turbine aerodynamics. [ABSTRACT FROM PUBLISHER]

In recent years, with the ever increasing penetration of wind generation, great concerns have been raised since the constantly decline of system's inertia may considerably deteriorate the frequency stability of power system. In this regard, an inertial response control technique is proposed to enable wind generators to provide the power system with controlled inertia in need via releasing energy to or absorbing energy from the system. In this paper, an extended state observer (ESO)-based inertia emulation controller (InEC) is proposed for doubly-fed induction generators (DFIGs), which is shown to be robust to measurement noise and changing working conditions. In addition, to mitigate potential adverse impacts of rotor speed recovery control (RSRC) of DFIGs on system frequency, an ESO-based RSRC is derived, allowing a schedulable dynamic of speed recovery. Experiments carried out on a power hardware-in-loop testbed manifest that the proposed controllers outperform the traditional proportional–differential type InEC and proportional–integral type RSRC in performance and robustness. [ABSTRACT FROM PUBLISHER]

Soft-stall control of small wind turbines is a method to protect the generation system and/or load from excessive wind speeds and wind gusts without discontinuing power generation. Soft-stall can be activated due to an excess of the power and/or torque/current. This paper proposes a method to improve the existing soft-stall methods for over torque/current protection using a turbine torque estimator. In addition, this paper also proposes two methods to emulate the wind turbine inertia without communications between the load drive (wind turbine emulator) and the generation system controller. This will allow the evaluation of the proposed methods in working conditions. [ABSTRACT FROM AUTHOR]

In this paper, we study unit commitment (UC) problems considering the uncertainty of load and wind power generation. UC problem is formulated as a chance-constrained two-stage stochastic programming problem where the chance constraint is used to restrict the probability of load imbalance. In addition to the conventional mixed integer linear programming formulation using Big-M, we present the bilinear mixed integer formulation of chance constraint, and then derive its linear counterpart using the McCormick linearization method. Then, we develop a bilinear variant of the Benders decomposition method, which is an easy-to-implement algorithm, to solve the resulting large-scale linear counterpart. Our results on typical IEEE systems demonstrate that (i) the bilinear mixed integer programming formulation is stronger than the conventional one and (ii) the proposed Benders decomposition algorithm is generally an order of magnitude faster than using a professional solver to directly compute both linear and bilinear chance-constrained UC models. [ABSTRACT FROM PUBLISHER]

This paper presents a method to derive the optimal offering/bidding strategy of a power producer who owns a hybrid power station (HPS), comprising wind farms (WFs) and pumped-hydro storage. The method is in line with the provisions of the Greek grid code for non-interconnected islands regarding the operation of HPSs. The goal of the HPS producer is to construct a single energy offer/bid for the total daily production/absorption, which maximizes his profits in the day-ahead market and minimizes any imbalance penalties during real-time operation. To this purpose, a two-stage stochastic bilevel optimization model is formulated, where the uncertainty lies in the wind power production of both the WFs belonging to the hybrid producer (internal WFs–IWFs) and the WFs belonging to other independent producers (WFs external to the HPS–EWFs). The upper level of the proposed bilevel model represents the hybrid producer's profit maximization, while the lower level represents the system operator's (SO) market clearing problem. This stochastic bilevel model is finally converted to a mixed-integer linear programming model in order to be tractable. Finally, simulation results from two test cases are thoroughly discussed and useful conclusions are drawn. [ABSTRACT FROM PUBLISHER]

Studies have shown that a large geographic spread of installed capacity can reduce wind power variability and smooth production. This could be achieved by using electricity interconnections and storage systems. However, interconnections and storage are not totally flexible, so it is essential to understand the wind power correlation in order to address power system constraints in systems with large and growing wind power penetrations. In this study, the spatial and temporal correlation of wind power generation across several European Union countries was examined to understand how wind 'travels' across Europe. Three years of historical hourly wind power generation data from 10 countries were analysed. The results of the analysis were then compared with two other studies focused on the Nordic region and the USA. The findings show that similar general correlation characteristics do exist between European country pairs. This is of particular importance when planning and operating interconnector flows, storage optimization and cross-border power trading. Copyright © 2017 The Authors Wind Energy Published by John Wiley & Sons Ltd [ABSTRACT FROM AUTHOR]

This paper proposes a method to quantitatively determine the sizes of energy storage systems that are intended to mitigate negative impacts of integrating wind energy into power systems. Although the integration of wind power has several advantages, it poses several technical challenges such as variability and uncertainty of wind speed and failures of wind turbine generators (WTGs), which may deteriorate the reliability of power systems. One of the most practical solutions to mitigate these drawbacks is the use of energy storage systems. The method proposed in this paper determines the sizes of the energy storage systems considering the effect of wind power uncertainty and variability, failures of WTGs, wind speed temporal resolution, and correlation with system load. Sizes of energy storage systems are determined based on composite system reliability analysis under operational and technical constraints using the ac power flow model. Monte Carlo simulation is used to emulate the behavior of the system. The proposed method is demonstrated on the IEEE reliability test system and the results are provided. The results show that the size of an energy storage system is dependent on wind farm characteristics, as well as the connectivity with the rest of the system. [ABSTRACT FROM AUTHOR]

In this paper, electromagnetic performances of 12-phase 24-stator-pole redundant switched flux permanent magnet (SFPM) machines with 20-, 22-, 26-, and 28-rotor-pole rotors designed for wind power generation are comparatively analyzed. The influence of key design parameters on the open-circuit phase electromotive force and cogging torque is comparatively evaluated by a 2-D finite-element analysis (FEA). FEA results show that the 24-/26-pole SFPM machine exhibits the highest electromagnetic torque and efficiency than the other three, while the 24-/22-pole one has the smallest cogging torque and torque ripple as well as relatively good voltage regulation and efficiency, which are essential for a wind generator. Furthermore, the investigation on redundancy performance shows that cross coupling among the four sets of three-phase balanced windings and the saturation effect can be neglected when the generator operates with relative light loads. Finally, the 12-phase 24-/22-pole SFPM machine is built and tested to validate the simulations. [ABSTRACT FROM AUTHOR]

With high renewable power penetration, uncertainty and intermittence of renewable sources become major concerns of power system planning and operation. Large and fast wind speed change may cause great variation of active power generation, which may lead to system stability and reliability problems. The response speeds of the committed conventional generators (CGs) for frequency regulations are critical for system reliable and stable operation. The slow response of the committed CGs may result in power shortage or surplus, which may affect system frequency. This paper proposes a technique to evaluate operational reliability and efficiency problems of power systems with high wind power penetration from frequency aspect. Energy unnecessarily consumed and less supplied during system frequency control processes are modeled in detail. The reliability and economic indexes are formulated with considering system dynamic frequency control processes. The IEEE-RTS79 is used to verify the proposed models and method. [ABSTRACT FROM AUTHOR]

This paper investigates two power generation systems that utilize a rectifier with small number of controlled switches associated to a two-phase permanent magnet synchronous machine. The proposed topologies have as a main purpose converting wind energy into electrical energy for low-power applications, giving them large potential to be employed in urban and rural areas. Each configuration is commanded by only two controlled switches and has natural protection against short circuit on the dc link. Compared with two three-phase generation systems that use a reduced number of controlled switches, the proposed topologies permit obtaining sinusoidal machine currents, with low harmonic distortion, using a smaller number of controlled switches. At last, to investigate the proposed system and control strategy, simulation and experimental results are presented. [ABSTRACT FROM PUBLISHER]

In modern wind farms, maximum power point tracking (MPPT) is widely implemented. Using the MPPT method, each individual wind turbine is controlled by its pitch angle and tip speed ratio to generate the maximum active power. In a wind farm, the upstream wind turbine may cause power loss to its downstream wind turbines due to the wake effect. According to the wake model, downstream power loss is also determined by the pitch angle and tip speed ratio of the upstream wind turbine. By optimizing the pitch angle and tip speed ratio of each wind turbine, the total active power of the wind farm can be increased. In this paper, the optimal pitch angle and tip speed ratio are selected for each wind turbine by the exhausted search. Considering the estimation error of the wake model, a solution to implement the optimized pitch angle and tip speed ratio is proposed, which is to generate the optimal control curves for each individual wind turbine off-line. In typical wind farms with regular layout, based on the detailed analysis of the influence of pitch angle and tip speed ratio on the total active power of the wind farm by the exhausted search, the optimization is simplified with the reduced computation complexity. By using the optimized control curves, the annual energy production (AEP) is increased by 1.03% compared to using the MPPT method in a case-study of a typical eighty-turbine wind farm. [ABSTRACT FROM AUTHOR]

Due to the development of renewable energy sources (RESs), maximization of hosting capacity (HC) of RESs has gained significant interest in the existing and future power systems. HC maximization should be performed considering various technical constraints like power flow equations, limits on the distribution feeders' voltages and currents, as well as economic constraints such as the cost of energy procurement from the upstream network and power generation by RESs. RESs are volatile and uncertain in nature. Thus, it is necessary to handle their inherent uncertainties in the HC maximization problem. Wind power is now the fastest growing RESs around the world. Hence, in this paper a stochastic multi-objective optimization model is proposed to maximize the distribution network's HC for wind power and minimize the energy procurement costs in a wind integrated power system. The following objective functions are considered: 1) Cost of the purchased energy from upstream network (to be minimized) and 2) Operation and maintenance cost of wind farms. The proposed model is examined on a standard radial 69 bus distribution feeder and a practical 152 bus distribution system. The numerical results substantiate that the proposed model is an effective tool for distribution network operators (DNOs) to consider both technical and economic aspects of distribution network's HC for RESs. [ABSTRACT FROM AUTHOR]