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This research aims to devise a methodology for optimizing the size of a Battery Energy Storage System (BESS) supporting Wind Energy Systems (WES) to enhance power commitment flexibility in the energy market. The methodology involves three essential steps: (i) estimating rated kW, (ii) initializing rated kWh of the BESSs, and (iii) iteratively adjusting the BESS size based on heuristic rules to prevent State of Charge (SoC) limit violations following the load cycle. Three realistic load cycles for the BESSs out of which one load cycle is generated based on maximum error values and the other load cycles are generated based on the mean and $1\sigma $ of the Normal Distribution Curve (NDC) of forecast errors of WES located at Agasthianpalli, Tamil Nadu, India. Two simple yet effective heuristic rules have been proposed to optimize the BESS size, ensuring maximum SoC at the start of each day and maintaining SoC within limits throughout the day. This leads to two scenarios considering a single set of the BESS to serve the load cycle and two sets of the BESS operating alternatively, reaching maximum SoC on the subsequent day by charging from the grid. Cost analysis indicates that scenario 1 is more favorable in terms of both cost and BESS size, surpassing scenario 2 by 8.89% and 9.95%, respectively. This analysis results in shorter payback period for scenario 1. Validation using Genetic Algorithm (GA) is done by comparing the costs of BESSs, emphasizing the suitability of the proposed technique.

When wind generation systems operate under weak grid conditions, synchronization stability issues may arise, restricting the wind farms' power transfer capacity. This paper aims to address these challenges on the grid side. Firstly, a clear exposition of the coupling mechanism between the grid-connected inverters (GCI) of wind generations and the weak grid is provided. Then, an equivalent parallel compensation method integrated into the PLL to enhance synchronization stability is proposed. The method changes the reference of the PLL and equivalently parallels the virtual resistance with the grid impedance, which alters the strength of the grid. It reshapes the inverter qq-axis impedance at the impedance level. And the proper design of the virtual resistance will enhance the system's stability without compromising the dynamic performance of PLL. In addition, the proposed method is robust to the parameter changes of the grid-connected system and the grid impedance measurement error. Experimental results are presented to validate the effectiveness of the compensation method. [ABSTRACT FROM AUTHOR]

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Wind power plants (WPPs) have been rapidly installed worldwide as an alternative source to thermal power plants. Nevertheless, since the outputs of WPPs constantly fluctuates due to variations in wind speed, WPPs expose power systems to power quality degradation, such as frequency fluctuation. This paper develops an optimal control method of energy storage systems (ESSs) that utilizes WPP output prediction to mitigate WPP output fluctuation. In the proposed method, an output reference of ESS can be obtained as the solution of an optimization problem. Specifically, the proposed method regulates the state of charge of ESS within its appropriate range by minimizing a cost function. At the same time, the minimization of ESS output and multiple grid codes related to the mitigation of WPP output fluctuation are considered as constraints. As a result, the proposed method enables us to mitigate the output fluctuation of WPP sufficiently by an ESS with small rated power. The effectiveness of the proposed method is demonstrated through comparative analysis with conventional methods via scenario simulations.

Frequency regulation of voltage source converter-based multi-terminal high-voltage direct current (VSC-MTDC) system with offshore wind farms enhances the frequency stability by compensating the power for a disturbed AC system. However, it is difficult to reasonably allocate frequency-regulation resources due to a lack of coordination mechanisms between wind farms and the MTDC system. Moreover, it is difficult for the frequency control of the wind farms to manage changes in wind speed; and the risk of wind-turbine stalls is high. Thus, based on the kinetic energy of wind turbines and the power margin of the converters, the frequency-regulation capability of wind turbines is evaluated, and a dynamic frequency-support scheme considering the real-time frequency-support capability of the wind turbines and system frequency evolution is proposed to improve the frequency-support performance. A power adaptation technique at variable wind speeds is developed; the active power in the frequency-support stage and restoration stage is switched according to the wind speed. A hierarchical zoning frequency-regulation scheme is designed to use the frequency-regulation resources of different links in the MTDC system with wind farms. The simulation results show that the novel frequency-regulation strategy maintains frequency stability with wind-speed changes and avoids multiple frequency dips.

In modern power systems, the increasing penetration of renewable energy resources has reduced frequency stability. Consequently, wind turbines (WTs) are expected to participate in frequency regulation. By integrating the electrostatic energy stored in the DC capacitor with the kinetic energy stored in the rotating mass of the WT, an advanced control method is implemented to facilitate frequency regulation. However, previous studies have mainly concentrated on frequency control using WTs but ignored the rotor speed recovery of WT. Therefore, this work proposes a novel control strategy that separates the operating mode of a WT into two distinct states: the frequency support and the recovery of rotation speed stages. The proposed method improves the recovery process for rotor speeds after a WT participates in frequency support, returning the WT quickly to its normal operation to reduce wind energy loss. Furthermore, a new adaptive DC virtual inertia (DVIC) coefficient that utilizes real-time DC voltage to adjust the DVIC’s output smoothly is proposed. The proposed strategy is compared with other mature control strategies and implemented in PSCAD/EMTDC to verify their effectiveness and robustness. The simulation results demonstrate that the proposed method outperforms other mature methods because it reduces wind energy loss by at least 15 % when WTs participate in the frequency support process.

The increasing integration of renewable energy sources (RESs) into the power system reduces system inertia, which presents substantial challenges for maintaining frequency stability. Existing studies have mainly focused on using the load frequency control method (LFC) to stabilize area frequency and tie-line power by optimizing the parameters of supplementary control for synchronous generators (SGs). However, these works primarily used simplified first-order transfer functions for wind turbines (WT), high-voltage direct current (HVDC), and battery energy storage systems (BESS). They neglected dynamic models and, importantly, the impact of control parameters in supplementary frequency control strategies on the stability of the studied system. Therefore, this study proposes a novel load frequency control strategy that coordinates the operation of WT, HVDC, and BESS in conjunction with traditional SGs to participate in frequency regulation. The proposed strategy develops a comprehensive state-space model that incorporates accurate models of WT, HVDC, BESS, and SGs, along with their supplementary control strategies. Then, the developed state-space model was utilized to investigate the impact of control parameters in the supplementary frequency control strategies of BESS, HVDC, and WT on system stability. As a result, this work yields a specific range of coefficients for supplementary strategies to improve stability in the studied system. Lastly, a two-area interconnected benchmark system is adopted to validate the effectiveness of the proposed strategy. Based on the suggested parameters, the results demonstrate that the proposed strategy ensures frequency stability with a high penetration of RESs into the power grid. Furthermore, the results indicate that incorporating diverse sources, such as HVDC, WT, and BESS, to support SGs in frequency regulation reduces the impacts of low system inertia. This approach leads to an improved frequency response not only in areas where disturbances occur but also in other regions, provided that tie-line power interchanges are maintained in balance.

This document is a list of academic research papers related to optimal power flow (OPF) in power systems. The papers cover various topics, including the use of different optimization algorithms, the integration of renewable energy sources, and the application of flexible AC transmission system (FACTS) devices. The papers come from a diverse range of authors and institutions, including researchers from Pakistan, China, Saudi Arabia, and other countries. [Extracted from the article]

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While Wyoming is known for fossil fuel extraction, the state has the capacity to generate 1,653,856 GWh of wind per year. With the growing rate of greenhouse gas emissions and the cyclical Boom-Bust that the state faces, there is an opportunity for private sector investment and a state and federal government that can utilize the overgeneration capacity of wind in Wyoming for Bitcoin mining operations and Carbon Capture, Utilization and Storage. Currently, projects are under development, but the issue of overgenerated wind continues to exist. By harnessing the overgenerated wind for Bitcoin mining, Wyoming has the opportunity to redistribute the global hashrate, incentivize Bitcoin miners to move their operations to Wyoming, and stimulate job growth as a result. Carbon Capture, Utilization, and Storage could help propel Bitcoin mining operations as well as harness carbon to manufacture products across various industries. By assessing workforce characteristics and proposed federal policies, this research addresses the need for the implementation of the Endless Frontier Act with the inclusion of wind turbine and CCS development, workforce protection, and cryptocurrency incentives.

This paper focuses on the research of virtual synchronous generator (VSG) control technology for the doubly-fed induction generator (DFIG)-based wind turbines. The key for DFIG VSG operation is to construct an internal electromotive force (EMF) with the virtual rotor motion characteristic in the stator. The existing control schemes use the rotor or mutual flux-induced EMF as the internal EMF. Since the flux corresponds to a composite magnetic field generated together by the stator and rotor current. Any variations in the stator current caused by external disturbances will reflect on the rotor current to keep the flux constant. The rotor overcurrent is inevitable under a large external disturbance, threatening the safety of the rotor-side converter (RSC). Moreover, the flux is immeasurable. The accurate flux control depends on flux observers, increasing the complexity; while the control without observers cannot ensure the effectiveness, leading to control failure. To address these problems, a novel DFIG VSG control scheme with the rotor current-induced EMF as the internal EMF is proposed in this paper. The internal EMF is corresponded to the single magnetic field generated only by the rotor current. This can lead to the following benefits: the rotor current will not vary with the stator current and can be limited under large external disturbances, ensuring the safety of the RSC; the rotor current can be directly measured without the need for extra observers, reducing the difficulty of control implementations; the underlying controlled vector is unified with the traditional grid-following DFIG, favoring the retrofit of the installed DFIGs. Compared to the existing schemes, this scheme has a larger equivalent internal impedance. An additional rotor current-terminal voltage magnitude droop control is added to effectively restrain the problems brought by this larger impedance. Simulation and analysis results demonstrate that the proposed DFIG VSG control scheme effectively addresses problems in the existing schemes. Moreover, the results also exhibit that the scheme has a robust adaptability across a wide range of short-circuit ratios and possesses the grid-forming ability independent of SGs.

To reduce the Carbon footprint and reduce emissions from the globe, the world has kicked-off to leave reliance of fossil fuels and generate electrical energy from renewable energy sources. The MOOPF problem is becoming more complex, and the number of decision variables is increasing, with the introduction of power electronics-based Flexible AC Transmission Systems (FACTS) devices. These power system components can all be used to increase controllability, effectiveness, stability, and sustainability. The added uncertainty and variability that FACTS devices and wind generation provide to the power system makes it challenging to find the right solution to MOOPF issues. In order to determine the best combination of control and state variables for the MOOPF problem, this paper develops three cases of competing objective functions. These cases include minimizing the total cost of power produced as well as over- and underestimating the cost of wind generation, emission rate, and the cost of power loss caused by transmission lines. In the case studies, power system optimization is done while dealing with both fixed and variable load scenarios. The proposed algorithm was tested on three different cases with different objective functions. The algorithm achieved an expected cost of $833.014/h and an emission rate of conventional thermal generators of 0.665 t/h in the case 1. In Case 2, the algorithm obtained a minimum cost of $731.419/h for active power generation and a cost of power loss is 124.498 $/h for energy loss. In Case 3, three objective functions were minimized simultaneously, leading to costs of $806.6/h for emissions, 0.647 t/h, and $214.9/h for power loss.

The transition to clean electricity generation is a crucial focus for achieving the current objectives of economy decarbonization. The Balearic Archipelago faces significant environmental, economic, and social challenges in shifting from a predominantly fossil fuel-based economy to one based on renewable sources. This study proposes implementing a renewable energy mix and decarbonizing the economy of the Balearic Islands by 2040. The proposed system involves an entirely renewable generation system with interconnections between the four Balearic islands and the Spanish mainland grid via a 650 MW submarine cable. This flexible electrical exchange can cover approximately 35% of the peak demand of 1900 MW. The scenario comprises a 6 GWp solar photovoltaic system, a wind system of under 1.2 GWp, and a 600 MW biomass system as generation sub-systems. A vanadium redox flow battery sub-system with a storage capacity of approximately 21 GWh and 2.5 GWp power is available to ensure system manageability. This system's levelized electricity cost (LCOE) is around 13.75 cEUR/kWh. The design also incorporates hydrogen as an alternative for difficult-to-electrify uses, achieving effective decarbonization of all final energy uses. A production of slightly over 5 × 104 tH2 per year is required, with 1.7 GW of electrolyzer power using excess electricity and water resources. The system enables a significant level of economy decarbonization, although it requires substantial investments in both generation sources and storage. [ABSTRACT FROM AUTHOR]

Inertial response support from wind turbine generators has become a priority requirement in most grid codes to improve the frequency response and frequency stability margins of power systems. However, the interaction between MPPT and inertial controllers may significantly degrade the power system dynamics. Therefore, there is a need to comprehensively understand the electromechanical dynamics of power systems with high penetration of wind generation. In this context, this work proposes a simplified dynamic model to assess the electromechanical dynamics of modern power systems with inertial response support from wind generation. The proposed simplified model allows simple analyses of the intrinsic and extrinsic aspects of wind generation that directly affect the system frequency dynamics and the dynamics of wind turbine generators. As a secondary contribution, this work also provides a comprehensive assessment of intrinsic and extrinsic aspects of wind generation that significantly affect the electromechanical dynamics of power systems with inertial response support from wind generation. [ABSTRACT FROM AUTHOR]

The proliferation of renewable energy sources and their impact on power systems makes it necessary to conduct studies to ensure the proper operation of the power system. This paper investigates recent research on the impact of renewable energy sources on voltage stability and new methods used to assess this stability. The effects of solar and wind power generation both individually and collectively are studied, along with other inverter models through which renewable energy sources are connected to transmission systems or distribution networks. In addition, the results are highlighted by categorizing them into a deterministic and probabilistic approach. [ABSTRACT FROM AUTHOR]

Summary: Active power equilibrium is analogous to frequency control. A hypothesis of maintaining this balance with voltage regulation is slightly less instinctive, notwithstanding the contribution it can make to the overall stability of the power system. This idea in synergism with the utilization of superconducting magnetic energy storage (SMES) technology in a colossal multi‐machine power network, is exercised in this paper. The main focus of this work is to make a small‐rated SMES more providential in large power systems with the aid of voltage frequency control (VFC). This study proposes an adaptive model predictive control (AMPC) equipped small capacity SMES as well as VFC operation, to ensure load frequency control of a wind power penetrated system. While assuming the plant as an autoregressive discrete mode system with exogenous input, the determination of both the plant model and controller parameters are effectuated online using a recursive least squares (RLS) identification algorithm. Detailed mathematical modeling of SMES is presented in addition to the discrete mode automatic generation control (d‐AGC) and governor dead band non‐linearity at the synchronous power source ends. A compact doubly fed induction generator (DFIG) model architecture harmonizing the maximum power point tracking (MPPT) mode using the standard two‐dimensional look‐up table with turbine characteristics is also discussed. Simulations in MATLAB/Simulink domain reveals a percentage improvement of 82.6% in the frequency nadir under load disturbance with the proposed VFC‐SMES scheme. Furthermore, an average percentage improvement of 82% in peak frequency deviations under turbulent wind scenario is attained. These results are validated in real‐time, employing the real‐time digital simulator OPAL‐RT (OP4510). [ABSTRACT FROM AUTHOR]

This paper presents a novel integration scheme of solar Photovoltaic (PV) with a large-capacity Doubly Excited Induction Generator (DFIG)-based wind energy system. The proposed scheme leverages both the grid and rotor-side power converters of the DFIG to inject PV power into the grid, eliminating the need for a dedicated converter for PV power processing and offering a cost-effective PV-grid integration solution. The system effectively delivers a substantial amount of PV power to the grid when compared to an equivalent rating inverter used in conventional PV-grid systems. Moreover, the proposed scheme prevents circulating power during sub-synchronous operation in the presence of solar radiation, enhancing overall system efficiency. Additionally, the system's stability benefits from turbine inertia, allowing for higher PV penetration into the power grid. The intermittent complementary nature of solar PV and wind energy sources significantly improves the utilization of the converters. Furthermore, the proposed scheme minimally impacts Maximum Power Point Tracking (MPPT) for PV and wind sources, except in rare environmental glitches, which the PV power control algorithm is adept at handling. The study provides a comprehensive system model used to design the control strategy, supported by analysis, simulations, and experiments conducted on a laboratory prototype. [ABSTRACT FROM AUTHOR]

Power systems are becoming more complex than ever and are consequently operating close to their limit of stability. Considering its significance in power system security, it is important to propose a novel approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables. Moreover, the time-domain simulation approach for transient stability evaluation can be very computationally intensive, especially for a large-scale system. The impact of wind penetration on transient stability is critical to investigate, as it does not possess the inherent inertia of synchronous generators. Thus, this paper proposes a risk-based, machine learning decision-making approach, for probabilistic transient stability enhancement, by replacing circuit breakers, including the impact of wind generation. The IEEE 14-bus test system was used to test and validate the effectiveness of the proposed approach. DIgSILENT PowerFactory and MATLAB were utilised for transient stability simulations (for obtaining training data for machine learning), and applying machine learning algorithms, respectively. [ABSTRACT FROM AUTHOR]

Novelty detection is a statistical method that verifies new or unknown data, determines whether these data are inliers (within the norm) or outliers (outside the norm), and can be used, for example, in developing classification strategies in machine learning systems for industrial applications. To this end, two types of energy that have evolved over time are solar photovoltaic and wind power generation. Some organizations around the world have developed energy quality standards to avoid known electric disturbances; however, their detection is still a challenge. In this work, several techniques for novelty detection are implemented to detect different electric anomalies (disturbances), which are k-nearest neighbors, Gaussian mixture models, one-class support vector machines, self-organizing maps, stacked autoencoders, and isolation forests. These techniques are applied to signals from real power quality environments of renewable energy systems such as solar photovoltaic and wind power generation. The power disturbances that will be analyzed are considered in the standard IEEE-1159, such as sag, oscillatory transient, flicker, and a condition outside the standard attributed to meteorological conditions. The contribution of the work consists of the development of a methodology based on six techniques for novelty detection of power disturbances, under known and unknown conditions, over real signals in the power quality assessment. The merit of the methodology is a set of techniques that allow to obtain the best performance of each one under different conditions, which constitutes an important contribution to the renewable energy systems. [ABSTRACT FROM AUTHOR]

Wind Power Plants utilize induction generators to generate electrical power. This type of generator produces less short circuit current than synchronous generators; hence it may affect the operation of transmission line protection relays. This research aims to analyze the effect of a large-scale wind power plant connected to the transmission line on the performance of the distance relays. The study utilizes a simulation method using Digsilent Powerfactory on IEEE 5 bus test system. The performance of the distance relays is compared between the original system, and the system in one of its generators is replaced with a wind turbine generator. The simulations are carried out for 3-phase faults that consist of bolted short circuits, 1-ohm fault resistance and 10-ohm fault resistances. The results show that the relays performances in zone 1 are the same for all types of generations. For zones 2 and 3, depending on the relay's position, the reaches may increase or decrease when the generator is replaced by wind power. The increasing reach of the relays is due to the dropping of infeed effect felt by the relay after installation of wind power. While the decreasing reaches of some relays because they see less fault current from the wind generation. The other relays do not experience any changes. Fault resistances cause all relays to experience reduced reach.

Water pumping model (WPM) is essential part in modern days for human’s daily activities. The WPM powered by renewable energy power sources (REPS) can reduce the pollution as well as a best solution for many other problems. Implementation of a backup power source through REPS for WPM can also help in decreasing the peak load on the utility grid. Proper sizing of a hybrid power supply system (HPSS) can ensure a consistent water supply to consumers. The wind and photovoltaic modules (PVMs) based HPSSs are two major REPS which commonly used in worldwide. Nevertheless, an energy storage mechanism is required to uphold energy equilibrium within the system due to the unpredictable fluctuations in both irradiance and wind speed. Hence, required number of batteries needs to be integrated to the system with the help of proper converter to make continuous water supply without any interrupt. Adequate space is available for the installation of PVMs and wind systems on both apartments and overhead water tanks in various rural and urban locations. Therefore hybrid PVMs-Wind-Battery based WPM is useful on such places. However, to achieve the best effective and efficient operation of the system, proper coordinated energy management coordination should be developed among wind, PVMs, motor, pump and battery bank unit (BBU). Therefore, a centralized novel energy management approach is designed in this paper. A PMDC generator is included in wind system and PMDC motor is coupled with water pump to reduce losses. Maximum power point tracker circuits (MPPTC) are utilized for optimizing the performance of both wind turbines and PVMs. The two MPPTCs have been combined into a shared dc-link. The BBU is connected to the dc-link via a bidirectional circuit. The bidirectional circuit will maintain voltage at dc-link to drive the PMDC motor corresponding to higher efficiency point. OPAL-RT devices have been designed to showcase outcomes across different operational modes through Hardware-in-Loop technology.

Microgrids, characterized by their ability to work individually or in combination with the main power system, play a pivotal role in addressing the growing demand for reliable and sustainable energy solutions. This work concentrates on the integration of sustainable energy sources, specifically photovoltaic (PV), and wind generation and a battery storage system within a microgrid framework. Additionally, a power flow control strategy is implemented to enhance the dynamic behaviour and stability of the microgrid. The proportional-integral (PI) controller is a fundamental component in regulating the microgrid’s power flow, ensuring optimal performance under varying operating conditions. However, tuning the PI controller parameters is a difficult task because of the dynamic and nonlinear nature of renewable energy sources. In this work, the application of the Enhanced Randomized Harris Hawk Optimization (ERHHO) to fine-tune the PI controller is proposed, using the algorithm’s ability to mimic the hunting behaviour of hawks in finding optimal solutions. The PV-Wind-Battery microgrid system is modelled, and the proposed algorithm is employed to optimize the PI controller parameters for efficient energy management. The ERHHO algorithm’s exploration-exploitation balance is harnessed to navigate the complex solution space and converge to optimal PI controller settings, thereby enhancing the microgrid’s stability and performance. The study evaluates the effectiveness of the proposed ERHHO-based PI controller tuning through comprehensive simulations. Performance metrics such as transient response, overshoot, settling time, and steady-state error are analysed to validate the robustness and efficiency of the proposed method. Compared to its nearest optimization algorithm, with the proposed algorithm rise time is reduced by 50%, overshoot is reduced by 75%, settling time is reduced by 66%, and finally, a percentage of reduction of steady-state error is 45%. The outcomes of this research contribute to the advancement of microgrid control strategies, offering a novel approach to PI controller tuning in the context of diverse renewable energy sources. The integration of the Harris Hawk Optimization algorithm provides a promising avenue for enhancing the operational efficiency and reliability of microgrids, paving the way for sustainable and resilient energy systems in the aspect of growing energy landscapes.

Abstract Microgrids (μ-grids) are gaining increased interest around the world for supplying cheap and clean energy. In this paper, a μ-grid comprising a wind turbine generator (WTG) and diesel generator (DG) is considered. It is one of most practical and demanding systems suitable for the present energy crisis in isolated or rural areas. However, wind energy is intermittent in nature while load demand changes frequently. Therefore, a µ-grid can experience large frequency and power fluctuations. The speed governor of the DG tries to minimize the frequency and power deviations in µ-grid though its operation is slow and cannot adequately minimize system deviations. The paper proposes a novel arrangement based on a dual structured fuzzy (DSF) whose structure changes according to the switching limit with a reduced rule base. It has the capability to switch between proportional and integral actions and hence improves the frequency regularization of the μ-grid. The proposed strategy is tested in a μ-grid and the results considering step load alteration, load alteration at different instants of time, nonstop changing load request are compared with some of the well published methods to validate the effectiveness and simplicity of the present design. In addition, it shows that ultra-capacitor establishment in a μ-grid has a positive impact in minimizing system deviations with DSF for the studied cases.

As the proportions of variable renewable sources (VRSs) such as solar and wind energy increase rapidly in the power system, their uncertainties inevitably undermine power supply reliability and increase the amount of operating reserve resources required to manage the system. However, because operating reserves have the characteristics of a public good and their value is related to the social cost of blackouts, it is difficult to determine their market price efficiently, which leads to inefficiencies in procuring operating reserves. This study estimates the operating reserve demand curve (ORDC) of the Korean power system to provide an effective basis for measuring the proper value and quantity of operating reserves needed to meet the reliability standard. A stochastic dynamic optimization model is applied to incorporate the probabilistic characteristics of VRS and the inter-hour constraint, which is necessary for analyzing load-following reserves. An econometric model and the Monte Carlo simulation method are used to generate the forecast profiles of solar and wind generation. The results indicate that the proper amount of hourly operating reserves needed in 2034 is approximately 4.4 times higher than that in 2020 at the current reserve offer price. The ORDC of 2020 has a price-inelastic shape, whereas the ORDC of 2034 has a price-elastic shape because the reserve requirement varies considerably with its offer price level in the high-VRS penetration case. This variability is due to alternatives, such as VRS curtailment or load shedding, which can replace the reserve requirement. This study also showed that VRS curtailment is an effective balancing resource as an alternative to reserves. [ABSTRACT FROM AUTHOR]

The generation from renewable sources has increased significantly worldwide, mainly driven by the need to reduce the global emissions of greenhouse gases, decelerate climate changes, and meet the environmental, social, and governance agenda (ESG). The main characteristics of variable renewable energy (VRE) are the stochastic nature, its seasonal aspects, spatial and time correlations, and the high variability in a short period, increasing the complexity of modeling, planning, operating, and the commercial aspects of the power systems. The research on the complementarity and dependence aspects of VREs is gaining importance, given the development of hybrid generation systems and an array of VREs generators spread over a large region, which could be compounded by different renewable sources, such as hydro, solar, and wind. This review is based on a systematic literature review, providing a comprehensive overview of studies that investigated applied methodologies and methods to address dependence and complementarity. It is a recent field of interest, as 60% of the articles were published in the last five years, a set of methods that have been employed to address this issue, from conventional statistics methods to artificial intelligence. The copulas technique appears as an important approach to modeling renewable energy interdependence. There is a gap in articles comparing the accuracy of the methods employed and the computational efforts. [ABSTRACT FROM AUTHOR]

The transition to clean and low-carbon energy in public buildings is crucial to energy saving and green social development. This paper focus on the sustainable development of public buildings and the construction of complementary power generation systems in existing public buildings. In the study, it was found that the constraints of the energy storage system could not be satisfied, which would result in the failure of the energy storage system for the purpose of peak regulation and stable operation of the microgrid. In order to satisfy the constraint conditions of the energy storage system, a spatial transformation method was proposed that improves the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The simulation results show that the spatial transformation Non-dominated Sorting Genetic Algorithm-II (STNSGA-II) has advantages in dealing with the strong constraints of the energy storage system. The introduction of the complementary power generation system with energy storage system in public buildings can save 23.74% to 31.17% from the perspective of optimal cost, and can reduce of CO2 emissions by at least 2478 kg from the perspective of carbon emission reduction. This study presents a case for transforming public buildings from simple consumers of energy systems to active contributors supporting large-scale wind and PV access. [ABSTRACT FROM AUTHOR]

This paper proposes a security system for frequency control in electrical grids with variable renewable generation; the spinning reserve is determined to take control actions toward operating power system in a defensive position, and the frequency droop is modified in to improve the primary frequency response. The proposed security system analyzes the electrical network in both long term and short term. For long term or steady stable operation, the spinning reserve is defined in a deterministic way to withstand the worst contingency, and in short term or dynamic analysis, if a contingency reaches the load shedding trip threshold, it is proposed to modify the frequency droop in the machines to improve system regulation. The non-controlled contribution of variable renewable generation imposes different requirements on regulation and reserve margins. Thus, the proposed security system responds dynamically to different operating conditions. IEEE 9-bus and IEEE 39-bus test systems were used, adding wind generation models to evaluate the proposed security system. The results in both test systems were satisfactory for diverse conditions and improved the frequency response. [ABSTRACT FROM AUTHOR]

The risk of unstable subsynchronous oscillations (SSO) in DFIG-based wind parks radially connected to transmission lines with series capacitive compensation is typically assessed with numerous electromagnetic transient (EMT) simulations, which is a time-consuming process. However, not all operating scenarios present risk of SSO and require such a detailed investigation. This paper proposes two charts based on impedance equivalents of wind generators obtained through frequency scans to quickly map which combinations of parameters can create unstable SSOs and which combinations are risk-free. With the information, engineers can immediately filter out scenarios with no risk of instability and conduct detailed studies on fewer scenarios that are truly critical. These charts can be obtained with simple equations that use only information readily available in practice to engineers, without the need to run any computer simulation. The charts also reveal the key operating conditions that can increase the risk of an unstable SSO and provide real-time quantitative insights into how close a wind park is to an instability. Application examples are provided to illustrate how this approach can help engineers speed up studies to identify the risk of SSO. [ABSTRACT FROM AUTHOR]

This paper applied an artificial intelligence technique to control Variable Speed in a wind generator system. One of these techniques is an offline Artificial Neural Network (ANN-based system identification methodology, and applied conventional proportional-integral-derivative (PID) controller). ANN-based model predictive (MPC) and remarks linearization (NARMA-L2) controllers are designed, and employed to manipulate Variable Speed in the wind technological knowledge system. All parameters of controllers are set up by the necessities of the controller's design. The effects show a neural local (NARMA-L2) can attribute even higher than PID. The settling time, upward jab time, and most overshoot of the response of NARMA-L2 is a notable deal an awful lot less than the corresponding factors for the accepted PID controller. The conclusion from this paper can be to utilize synthetic neural networks of industrial elements and sturdy manageable to be viewed as a dependable desire to normal modeling, simulation, and manipulation methodologies. The model developed in this paper can be used offline to structure and manufacturing points of conditions monitoring, faults detection, and troubles shooting for wind generation systems. [ABSTRACT FROM AUTHOR]

This paper proposes a novel coordinated control method of wind farms (WFs) and hydrogen production systems (HPSs). In a grid-connected system where the WF and the HPS are connected to the grid, the WF can supply the power to the grid, producing hydrogen in the HPS. Moreover, the output fluctuation of the WF can be mitigated when the HPS produces hydrogen from the output surplus. The purpose of the grid-connected system is to smooth the WF output fluctuation sufficiently, produce hydrogen constantly, and maintain a high capacity factor in the HPS. The proposed coordinated control achieves the mitigation of the WF output and the high capacity factor in the HPS. The key ideas are 1) utilizing the kinetic energy of wind generators and 2) virtual discharge of the HPS. The fluctuation components of the WF output are compensated by both the WF and the HPS. The proposed coordinated controller enables us to produce hydrogen constantly in the HPS with a low-rated power. The advantage of the proposed coordinated control is verified by a comparative analysis with conventional methods through simulations using real wind data.

Using wind-availability forecasts in day-ahead unit commitment can require expensive real-time operational adjustments. We examine the benefit of conducting interim recommitment between day-ahead unit commitment and real-time dispatch. Using a simple stylized example and a case study that is based on ISO New England, we compare system-operation costs with and without interim recommitment. We find an important tradeoff-later recommitment provides better wind-availability forecasts, but the system has less flexibility due to operating constraints. Of the time windows that we examine., hour-20 recommitment provides the greatest operational-cost reduction.

This paper proposes a novel optimal control method for integrated systems of Wind farms (WFs) and hydrogen production systems (HPSs). Green hydrogen production via renewable power generation (RPG), such as wind power generation, is a promising technology to overcome environmental problems. RPG has the potential to become more widespread if we can produce hydrogen in an HPS using the output fluctuation and the output surplus of RPG, which cause power outages due to supply-demand imbalances. The proposed optimal control maximizes the capacity factor of HPS while producing hydrogen constantly and satisfying the technical requirement related to the output fluctuation of the WF. The proposed control is also easy to implement and needs no WF output forecast. We demonstrate the effectiveness of the proposed optimal control through simulated comparative analysis with conventional methods.

The seasonality and randomness of wind present a significant challenge to the operation of modern power systems with high penetration of wind generation. An effective short-term wind power prediction model is indispensable to address this challenge. In this paper, we propose a combined model, i.e., a wind power prediction model based on multi-class autoregressive moving average (ARMA). It has a two-layer structure: the first layer classifies the wind power data into multiple classes with the logistic function based classification method; the second layer trains the prediction algorithm in each class. This two-layer structure helps effectively tackle the seasonality and randomness of wind power while at the same time maintaining high training efficiency with moderate model parameters. We interpret the training of the proposed model as a solvable optimization problem. We then adopt an iterative algorithm with a semi-closed-form solution to efficiently solve it. Data samples from open-source projects demonstrate the effectiveness of the proposed model. Through a series of comparisons with other state-of-the-art models, the experimental results confirm that the proposed model improves not only the prediction accuracy, but also the parameter estimation efficiency.

The growing penetration of wind generation comes with implicit challenges for power system operators, one of which is the effect that additional shares have on the sufficient magnitude of reserve capacity needed. The determination of adequate reserves would enhance the efficiency and flexibility of the power system. The probabilistic methodology suggested in this paper estimates the reserve requirements as a function of historical data and estimates the incremental increase in reserve requirements as the penetration level increases. Also, the paper estimates the optimal mix of spinning reserve and standing reserve to decrease the number of part-loaded power plants and accommodate more wind power, where a synchronized plant operates less efficiently when partially loaded to provide a reserve. The adopted methodology is applied to real data collected from aggregated wind farms in the period from 2015 to 2020.

The loss of small signal stability under parameter variation (e.g., fluctuation of loads and wind powers) can be ascribed to local bifurcations, i.e., saddle-node, Hopf, singularity-induced, and limit-induced bifurcations. Classic bifurcation calculation methods like the direct method and continuation method can only provide a bifurcation point or two-parameter bifurcation curve. Based on Galerkin method and the implicit function theorem, this paper proposes accurate polynomial approximations of bifurcation hypersurfaces in the multi-dimensional parameter space of interest. The proposed method can ensure high accuracy in this parameter space, and thus is preferable to the existing Taylor expansion-based local approximation method, given the intrinsic large-variation characteristic of wind powers. Acquired bifurcation hypersurfaces are immediately used to construct the small signal stability region of the continuous system, and then compute the stability margin for the operating point subjected to uncertainty of wind generation. Besides, the validity scope of the proposed method is analyzed, and the handling of limit-triggered equation switching as well as its computational difficulty is discussed. Computational results on the two-parameter 11-bus two-area and six-parameter IEEE 145-bus test systems validate the high accuracy and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The transition to clean electricity generation is a crucial focus for achieving the current objectives of economy decarbonization. The Balearic Archipelago faces significant environmental, economic, and social challenges in shifting from a predominantly fossil fuel-based economy to one based on renewable sources. This study proposes implementing a renewable energy mix and decarbonizing the economy of the Balearic Islands by 2040. The proposed system involves an entirely renewable generation system with interconnections between the four Balearic islands and the Spanish mainland grid via a 650 MW submarine cable. This flexible electrical exchange can cover approximately 35% of the peak demand of 1900 MW. The scenario comprises a 6 GWp solar photovoltaic system, a wind system of under 1.2 GWp, and a 600 MW biomass system as generation sub-systems. A vanadium redox flow battery sub-system with a storage capacity of approximately 21 GWh and 2.5 GWp power is available to ensure system manageability. This system’s levelized electricity cost (LCOE) is around 13.75 cEUR/kWh. The design also incorporates hydrogen as an alternative for difficult-to-electrify uses, achieving effective decarbonization of all final energy uses. A production of slightly over 5 × 104 tH2 per year is required, with 1.7 GW of electrolyzer power using excess electricity and water resources. The system enables a significant level of economy decarbonization, although it requires substantial investments in both generation sources and storage.

A battolyser is a combined battery electrolyser in one unit. It is based on flow battery technology and can be adapted to produce hydrogen at a lower efficiency than an electrolyser but without the need for rare and expensive materials. This paper presents a method of determining if a battolyser connected to a wind farm makes economic sense based on stochastic modelling. A range of cost data and operational scenarios are used to establish the impact on the NPV and LCOE of adding a battolyser to a wind farm. The results are compared to adding a battery or an electrolyser to a wind farm. Indications are that it makes economic sense to add a battolyser or battery to a wind farm to use any curtailed wind with calculated LCOE at £56/MWh to £58/MWh and positive NPV over a range of cost scenarios. However, electrolysers, are still too expensive to make economic sense. [ABSTRACT FROM AUTHOR]

In this paper, the problem of economic dispatch of energy of an electrical system is solved, based on three different approaches: first is deterministic, a second is stochastic and a third given by bilevel programming. It is observed that when solving the deterministic economic energy dispatch, results follow the principle of order of merit, likewise under some scenarios availability of a large flexible capacity during the power balance stage becomes necessary. In another hand, the stochastic model becomes a tool that optimizes flexible capacity by sacrificing the order of merit which is not the case of bilevel model that adopts both, order of merit and optimization of flexible capacity by choosing an optimum of wind power to dispatch. In terms of profit, it has been observed that under the stochastic approach those flexible participants must fall into losses under certain scenarios. However, under the bilevel approach, the aforementioned issue is improved. Finally and in order to illustrate the impact of the bilevel approach a 24-node system serves as a test system to obtain results and demonstrate the economic advantages of an bilevel dispatch. [ABSTRACT FROM AUTHOR]

Power electronic devices interfaced doubly fed induction generators (DFIGs) cause a reduction in the power system inertia and further the power system becomes vulnerable to severe disturbances. DFIGs provide fast frequency response (FFR) strategies to the power system by increasing the output power. Nevertheless, these strategies produce a large frequency second drop or a slow rotor speed restoration. This article suggests a FFR strategy of a DFIG based on variable power point tracking control to boost the frequency support capability with grid-friendly rotor speed recovery. Furthermore, the benefit of the proposed strategy when participating in FFR is calculated. The test results illustrate that the proposed FFR strategy enhances the performance of the frequency nadir, size of SFD, and benefits of auxiliary FFR service. Hence, the proposed strategy provides a promising solution of ancillary service for FFR from a wind turbine generator to power systems. [ABSTRACT FROM AUTHOR]

Increasing wind generation insertion levels on electrical grids through power converters may cause instabilities in the AC grid due to the intermittent wind nature. Integrating a Battery Electric Energy Storage System (BESS) in wind generation can smooth the power injection at the Common Coupling Point (PCC), contributing to the power system voltage and frequency stability. In this article, it is proposed to analyze the operation of a lithium-ion battery technology based 1 MW/1.29 MWh BESS connected in parallel with wind generation with a capacity of 50.4 MW. The main characteristics investigated are power smoothing and power factor correction. Experimental results show that BESS contributes to smoothing the active power and correcting the power factor of wind generation, improving the quality of electrical energy at the PCC. [ABSTRACT FROM AUTHOR]