Power Reserve Research Articles

A novel distance‐based system reactive power index for system‐level reactive power reserve assessment

AbstractVoltage stability of the power system is of major concern with ever‐increasing stress in the transmission network. The availability of ample reactive power reserve is essential to ensure voltage stability of the power system. Voltage stability and status of reactive power reserves can be monitored in real‐time by using synchrophasor measurements at a very fast reporting rate. Although much attention has been given to online voltage stability monitoring, there has been less focus on real‐time monitoring of reactive power reserve status. In this regard, the major contributions of the study are: (i) development of a novel distance‐based generalised approach for the computation of the system reactive power index, (ii) a proactive methodology for identification and impact estimation of the nearest Q‐limit breach and (iii) formulation of an optimisation problem to identify the limited number of critical generators that need PMUs for accurately predicting the value of the proposed index. The proposed scheme looks at the reactive power reserve of the generators in the network as numerical features. The istance between the base case and nose point numerical features is computed offline. The distance between the current operating point and nose point numerical features can be computed in an online manner. The ratio of these two distance measures is proposed as a system reactive power index. Moreover, a methodology to predict the post‐Q limit breach value of the index is also introduced. The proposed approach can be used with PMUs, linear state estimators or traditional SCADA measurements. Case studies for IEEE 57 and 118 bus test systems are presented to validate the performance of the proposed index.

Engine power distribution system for four-wheel drive autonomous electric vehicle

Nowadays, there is an active stage of development of advanced energy-saving technologies in the field of automotive industry, and therefore, electric vehicles are becoming increasingly popular. One of the main indicators of the efficiency of autonomous electric transport is the power reserve, the increase of which can be achieved by reducing the weight of the vehicle. In classic cars, the torque from the internal combustion engine is passed to the wheels by means of a transmission. In electric vehicles, due to the use of motor wheels, there is no need for a transmission, which significantly reduces the weight of the construction, as well as reduces maintenance and repair costs. The article considers the issue of power distribution of engines of an autonomous electric vehicle based on four-wheel hub motor. A mathematical description of an electronic differential for an electric car based on two and four motor wheels based on the Ackerman control principle is also obtained. A digital simulation of the four-wheel drive electric vehicle system was carried out in the MATLAB/Simulink software. Transients are obtained in terms of the speed of rotation of the engine shaft and the torque on the engine shaft, which satisfy the requirements for overregulation and quickness of the system.

Flexible Power Point Tracking Using a Neural Network for Power Reserve Control in a Grid-Connected PV System

Renewable energy penetration in the global energy sector is in a state of steady growth. A major criterion imposed by the regulatory boards in the wake of electronic-driven power systems is frequency regulation capability. As more rooftop PV systems are under installation, the inertia response of the power utility system is descending. The PV systems are not equipped inherently with inertial or governor control for unseen frequency deviation scenarios. In the proposed method, inertial and droop frequency control is implemented by creating the necessary power reserve by the derated operation of the PV system. While, traditionally, PV systems operate in normal MPPT mode, a derated PV system follows a flexible power point tracking (FPPT) algorithm for creating virtual energy storage. The point of operation for the FPPT of the PV is determined by using a neural network block set available in MATLAB. For the verification of the controller, it is applied to a PV array in a modified IEEE-13 bus system modeled in the MATLAB/Simulink platform. The simulation results prove that when the proposed control is applied to the test network with renewable energy penetration, there is an improved system inertia response.

Frequency regulation in adaptive virtual inertia and power reserve control with high PV penetration by probabilistic forecasting

The large-scale deployment of sustainable energy sources has become a mandatory goal to reduce pollution from electricity production. As photovoltaic (PV) plants replace conventional synchronous generators (SGs), their significant inherent rotational inertia characteristics are reduced. The high penetration of PV results in reduced system inertia, leading to system frequency instability. Virtual inertial control (VIC) technology has attracted increasing interest because of its ability to mimic inertia. Adoption of the energy storage system (ESS) is hindered by the high cost, although it can be used to provide virtual inertia. The determined forecast gives PVs the ability to reserve power before shading and compensate the power when a system power drop occurs, which can increase system inertia. Nevertheless, it has forecast errors and energy waste in a stable state. To improve the stability of the microgrid and improve the ESS efficiency, this study proposes an adaptive forecasting-based (AFB) VIC method using probabilistic forecasts. The adaptive power reserve and virtual inertia control are proposed to reduce energy waste and increase system inertia. The simulation results reveal that the proposed method has adaptive system inertia to reduce the reserved power, required ESS power capacity, and battery aging.

Frequency Stability Analysis of a Low Inertia Power System with Interactions among Power Electronics Interfaced Generators with Frequency Response Capabilities

One of the main actions required to face and limit global warming is the substitution of conventional fossil-fueled electrical generators with renewable ones. Thus, it becomes fundamental to create non-dispatchable renewable generators able to provide services for power system stabilization that nowadays are delivered by conventional ones. Particularly, renewable generators are usually connected to the electrical power system through power electronic converters lacking natural responses to frequency variations. This challenges conventional frequency control methods that are based on synchronous generators’ capabilities, particularly in systems with high levels of non-synchronous generation. Solutions based on advanced controls that allow renewable generators to participate in frequency control are the subject of current research efforts worldwide. This paper contributes to these efforts by studying the benefits of introducing Power Reserve Control in photovoltaic generators and Extended Optimal Power Point Tracking control in wind generators to provide frequency control in low inertia power systems and the interactions between them. The tests and the simulations, prove that these kinds of controls help in stabilizing the system frequency thanks to the cooperative action of both types of renewable generators.

Frequency and Inertia Response Effects, Capabilities, and Possibilities in Renewable Energy Sources

Background & Objectives: The global power system is in a state of continuous evolution, incorporating more and more renewable energy systems. The converter-based systems are void of inherent inertia control behavior and are unable to curb minor frequency deviations. The traditional power system, on the other hand, is made up majorly of synchronous generators that have their inertia and governor response for frequency control. For improved inertial and primary frequency response, the existing frequency control methods need to be modified and an additional power reserve is to be maintained mandatorily for this purpose. Energy self-sufficient renewable distributed generator systems can be made possible through optimum active power control techniques. Also, when major global blackouts were analyzed for causes, solutions, and precautions, load shedding techniques were found to be a useful tool to prevent frequency collapse due to power imbalances. The pre-existing load shedding techniques were designed for traditional power systems and were tuned to eliminate low inertia generators as the first step to system stability restoration. To incorporate emerging energy possibilities, the changes in the mixed power system must be addressed and new frequency control capabilities of these systems must be researched. Discussion: In this paper, the power reserve control schemes that enable frequency regulation in the widely incorporated solar photovoltaic and wind turbine generating systems are discussed. Techniques for Under Frequency Load Shedding (UFLS) that can be effectively implemented in renewable energy enabled micro-grid environment for frequency regulation are also briefly discussed. The paper intends to study frequency control schemes and technologies that promote the development of self- sustaining micro-grids. Conclusion: The area of renewable energy research is fast emerging with immense scope for future developments. The comprehensive literature study confirms the possibilities of frequency and inertia response enhancement through optimum energy conservation and control of distributed energy systems.

A Cooperative Energy Transaction Model for VPP Integrated Renewable Energy Hubs in Deregulated Electricity Markets

This article proposes a cooperative energy transaction model for a virtual power plant (VPP) developed as a bilevel optimization program based on the Stackelberg game in the deregulated electricity markets. The VPP integrates multiple renewable energy hubs consisting of electric vehicle charging stations with photovoltaic and battery energy storage systems. The proposed model derives co-optimized strategic decisions for the VPP operator in the day-ahead (joint active power, reserve, and reactive power) markets while considering the balancing market operation. The proposed model is reformulated as a mathematical program with equilibrium constraints (MPECs) using the Karush–Kuhn–Tucker conditions and the strong duality theorem. For an efficient solution, the MPEC is approximated as a mixed-integer linear program by applying the Fortuny-Amat transform on the complementarity and slackness conditions and the binary expansion on the bilinear terms. The uncertainties of the renewables, loads, and prices are modeled using stochastic scenarios. Finally, comparative case studies of a VPP in an IEEE 33 node active distribution network show that the proposed model improves the profit by strategic cooperative energy transactions.

Energy efficiency of a cone crusher with stops

Metallurgical, construction and mining industries are based on the process of grinding various materials. The main method of primary preparation of raw materials is crushing of the extracted ore. Up to 4 % of the world’s electricity production is spent annually on crushing rocks to obtain the necessary fraction of material, and for a single mine, the share of energy consumption for crushing can reach 50 % of the annual volume. In addition to spending electricity directly on rocks destruction, some of it is spent on creating a power reserve for a crushing machine (hereinafter referred to as a crusher) due to the fact that currently there is no single method of theoretical calculation of the power of its electric drive, no single method of determining energy costs for rocks destruction. It is known that raw materials extracted from different deposits have different physical and mechanical properties, which has a significant impact on the grinding process. However, difference in power of electric drive of crushing machines is due to the difference in their standard sizes, and the geography of their application is taken into account by the creation of the above-mentioned power reserve. The above factors have a negative impact on the operating costs of metallurgical industry enterprises. The article discusses some designs of crushers in which the destruction of the crushed piece occurs as a result of complex stress state. New design of a cone crusher with stops is proposed, which allows reducing energy costs for crushing materials. Due to the presence of stops and simple kinematics of the working body movement, reduction in the power necessary for the destruction of pieces of brittle materials, regardless of their properties, is achieved. At the same time, in crushed pieces destroyed in a cone crusher with stops, it is possible to create a shear stress state, in which theoretically a reduction in power required for crushing brittle materials is achieved by 2 times in comparison with compression crushers. The conditions of occurrence of shear stress state in crushed pieces during their crushing in a cone crusher with stops are described. The authors give recommendations for the reconstruction of these conditions.

Optimal economic operation of microgrids considering combined heat and power unit, reserve unit, and demand-side management using developed adolescent identity search algorithm

In the present study, a method is proposed to solve the problem of economic load distribution in MGs, meet the challenges arising from the use of renewable sources periodically, ensure the stable performance of MGs, and minimize the operating cost of MGs considering combined heat and power (CHP) units and reserve system. Moreover, demand-side management (DSM) as a tool is employed to reduce the operating cost of the power system. Therefore, the proposed model for optimal operation of MGs using DSM is formulated as an optimization problem. Load shifting is considered as an effective solution in DSM. Minimizing the total operating cost of the system is considered as the objective function of this problem. Problem constraints include operating and executive constraints for load shifting. Finally, the model is solved using the developed adolescent identity search algorithm (AISA). In the developed model, Powell's local search operator is employed to improve the efficiency of searching for the optimal solution. Due to the existing uncertainties in load consumption and day-ahead market price, the method is presented as a scenario-based stochastic energy management problem. The results reveal the proposed method is highly efficient in solving the problem, and load management can improve economic indicators.

A Reactive Power Reserve Constrained Optimum Reactive Power Dispatch Using Coronavirus Herd Immunity Optimizer

The Optimal Reactive Power Dispatch (ORPD) is a very important study in planning the power system operation. The conventional ORPD formulations focus only on driving the objective functions toward optima and ignore the benefits to retain adequate Reactive Power Reserve (RPR) in the system. Studies show that inadequate RPR can jeopardize the power system voltage security under stressed conditions. In view of this, a Reserve Constrained ORPD (RC-ORPD) is proposed in this paper and solved using the recently developed, Coronavirus Herd Immunity Optimizer (CHIO). For this purpose, the minimum required Effective Reactive Reserve (ERR) is devised and introduced as a constraint in the ORPD problems. Here, the minimization of power loss and L-index are taken as objective functions, and the problem is formulated as a non-linear constrained optimization problem. The proposed problem is tested on standard IEEE 30 bus and IEEE 57 bus systems. To assess the impact of the proposed strategy, the same problems are also solved by relaxing the ERR constraint. Comparisons reveal that the added constraint improves voltage stability linked parameters and offers more RPR in the system without sacrificing much on the optimum solution. Further, the proficiency of CHIO is verified through various case studies and comparisons.

Comparison of wind speed forecasting models for power reserve scheduling in the congested transmission network

Comparison of wind speed forecasting models for power reserve scheduling in the congested transmission network

Combinational load shedding using load frequency control and voltage stability indicator

This paper proposes a load shedding program for evaluating and distributing the minimum load power to be curtailed required to bring the frequency and voltage, after the system was subjected to a heavy disturbance, to the allowable range for each load bus. The quantity of load shedding was estimated to restore the power system's frequency, taking into account the turbine governor's primary control and the generators' reserve power for secondary control. Calculation and review of the load bus's voltage stability indicator (Li) to prioritize the load shedding quantity at these locations. The lower the voltage stability indicator on the load bus, the less load shedding can occur, and vice versa. The frequency and voltage values are still within allowable ranges with this approach, and a significant amount of load shedding can be prevented, resulting in a reduction in customer service interruption. The proposed method's efficacy was demonstrated when it was checked against the IEEE 30 bus 6 generators power system standard simulated in MATLAB environment and it minimize the power to be shed by around 20% of the conventional load shedding schemes.

A multiscale local pattern filtering method for noise mode identification of dynamic signals in bridges

The problem of effective information extraction of dynamic signals is a key challenge of vibration-based structural health monitoring. Traditional ensemble empirical mode decomposition (EEMD) and complementary EEMD (CEEMD) are effective filtering methods but have the shortcomings of mode mixing, completeness and the endpoint effect in adaptive decomposition stage. To address the above problems, this paper proposes a noise mode identification method based on multiscale local pattern filtering with a machine learning algorithm. In addition, this method improves the filtering performance of mode decomposition and wavelet threshold denoising methods effectively. To validate the performance of this method, simulation experiment and real signal analysis were used for validation: their results showed that the proposed method has better adaptive decomposition performance than EEMD and CEEMD. Compared with the EEMD, CEEMD and wavelet threshold denoising methods, the proposed method can better balance smoothness and the power reserve, has optimized time- and frequency-domain characteristics, filters with a higher signal-to-noise ratio and reliability, and has more optimized filtering performance. The method proposed in this paper can be applied to bridge health monitoring technology, and has important scientific and engineering significance.

Synergy of Unidirectional and Bidirectional Smart Charging of Electric Vehicles for Frequency Containment Reserve Power Provision

Besides the integration of renewable energies, electric vehicles pose an additional challenge to modern power grids. However, electric vehicles can also be a flexibility source and contribute to the power system stability. Today, the power system still heavily relies on conventional technologies to stay stable. In order to operate a future power system based on renewable energies only, we need to understand the flexibility potential of assets such as electric vehicles and become able to use their flexibility. In this paper, we analyzed how vast amounts of coordinated charging processes can be used to provide frequency containment reserve power, one of the most important ancillary services for system stability. Therefore, we used an extensive simulation model of a virtual power plant of millions of electric vehicles. The model considers not only technical components but also the stochastic behavior of electric vehicle drivers based on real data. Our results show that, in 2030, electric vehicles have the potential to serve the whole frequency containment reserve power market in Germany. We differentiate between using unidirectional and bidirectional chargers. Bidirectional chargers have a larger potential but also result in unwanted battery degradation. Unidirectional chargers are more constrained in terms of flexibility, but do not lead to additional battery degradation. We conclude that using a mix of both can combine the advantages of both worlds. Thereby, average private cars can provide the service without any notable additional battery degradation and achieve yearly earnings between EUR 200 and EUR 500, depending on the volatile market prices. Commercial vehicles have an even higher potential, as the results increase with vehicle utilization and consumption.

Global Flexible Power Point Tracking in Photovoltaic Systems Under Partial Shading Conditions

Flexible power point tracking (FPPT) aims to regulate the output power of photovoltaic (PV) systems to a predefined value to enable grid support functionalities, such as virtual-inertia provision. Even though partial shading is a common condition in PV systems, especially in small-scale residential PV systems, the current literature, only investigates FPPT control under uniform shading conditions. This article proposes a novel global FPPT (GFPPT) algorithm to provide two functionalities in PV systems under partial shading conditions: first, constant power control (CPC), in which the PV power is regulated to predefined reference value, and second, power reserve control (PRC), under which a constant power reserve is kept in the PV system under steady state to enable grid support under transients. The conventional global maximum power point tracking (GMPPT) algorithm is also modified to adapt with the proposed GFPPT algorithm. The aim of such modification is to obtain faster dynamics after the detection of any environmental changes. Experimental results under dynamically changing partial shading conditions verify the effectiveness of the proposed algorithm in providing CPC or PRC functionalities in PV systems.

Pushing the envelope of ancillary services with variable speed technology

Hydropower is the backbone of energy transition thanks to its operational flexibility and ability to provide ancillary services. These grid support capabilities are called upon to play a major role to maintain the grid vulnerability at acceptable levels in view of the increasing penetration of stochastic and intermittent renewable energies. In this context, variable speed reversible pump-turbine technology is a key asset as it can extend the head operating range of a powerplant, enable power network control in pump mode and further increase the flexibility services to the electrical grid. Furthermore, by taking advantage of the so-called flywheel effect, variable speed enables the fast active power injection/absorption in pumping and generating mode. The additional degree of freedom offered by the variable speed opens the door to different control strategies for the hydroelectric plant, as the converter can be used for speed or power control. This can be exploited to maximize either the efficiency or the power reserve dedicated to grid support. In this paper, the strategies to maximize the ancillary service of Frades 2 pumped storage power plant (PSPP) are investigated. The plant features two high-head single-stage reversible variable speed units, coupled with 420 MVA doubly-fed induction motor-generators (DFIM). Using a 1D numerical model to simulate the power plant behavior, it is explored to which extent Frades 2 can deliver frequency containment reserve (FCR) power, while complying with the ENTSO grid code, and speed deviation constrains inherent to DFIM. By choosing a strategy which fully exploits the flywheel effect, it is established that the FCR power band can be equal to the whole operating range of the power plant. Moreover, the fast frequency response capacity (FFR) is also evaluated. It is found that by maximizing the energy stored in the rotating masses, each unit of Frades 2 can deliver up to 110 MW of active power in 1.3 seconds.

Alternating Optimization Approach for Voltage-Secure Multi-Period Optimal Reactive Power Dispatch

This paper proposes an optimization approach for day-ahead reactive power planning to improve voltage security in transmission networks. The problem is formulated as a voltage-secure multi-period optimal reactive power dispatch (MP-ORPD) problem. The optimization approach searches for optimal set-points of dynamic and static reactive power (var) resources. Specifically, the output includes set-points for switching shunts, transformer taps, and voltage magnitudes at the regulated buses. The primary goal is to maximize the dynamic reactive power reserve of the system, by minimizing the reactive power supplied by synchronous generators. As the size of the MP-ORPD problem increases significantly with increasing number of contingencies and time periods, efficiency is crucial for practical applications. In this paper, a decomposition technique based on consensus and alternating optimization, where integer variable targets are obtained via MILP, is used to partition the MP-ORPD problem into a set of subproblems, which can be solved in parallel to reduce the computation time. The proposed MP-ORPD problem and its solution algorithm are integrated into the EPRI-VCA software. The results of various power networks of large electric utilities in the Eastern interconnection demonstrate the effectiveness of the proposed algorithm in providing preventive control schedules.

Simulation Analysis of Issues with Grid Disturbance for a Photovoltaic Powered Virtual Synchronous Machine

The increase in inverter-based resources associated with the increased installation of PV sources is a concern because it reduces the inertia of the power system during peak PV generation periods. As a countermeasure to reduce grid inertia, the addition of pseudo-inertia using virtual synchronous machines can be selected, and PV generation can cooperatively contribute to the stable operation of the power system by using the suppressed output as reserve power. However, few studies have analyzed VSMs that do not use batteries and use PV as a resource (PV-VSM) in simulations, including grid interconnection and solar radiation fluctuations, and it is necessary to clarify the issues and discuss countermeasures. In this study, electromagnetic transient response analysis was applied to a VSM connected to a two-generator system, simulations were performed, and the following findings were reported and countermeasure methods for the problem were proposed. When the PV capacity is insufficient for the output required by the VSM inverter, the PV-VSM control system may become unstable. This is caused by a drop in the capacitor voltage of the DC/DC converter due to insufficient PV output. The limiter control system is designed to address this problem by combining the headroom estimation system with the current limiting algorithm. The proposed limiter control system is validated on solar radiation ramp fluctuations as a test case and found that the system was effective in supressing PV-VSM instability. In our simulation case, the PV-VSM with our limiter control can continue to operate stably even if the PV available power is 0.03 [p.u.] short of the inverter’s reference power by the solar power ramp fluctuation, as long as the inverter installation rate is less than 50%.

A numerical study to compensate duck curve of ESS integrated gas turbine system with reused-battery

Due to the intermittentness and variability of renewable energy sources(RES), flexible power generation is possible, and the importance of an integrated system capable of storing reserve power is increasing. In particular, the instability of the power system is intensifying due to the duck curve phenomenon (the net load between sunrise and sunset decreases rapidly and the demand for power increases for about 3 h after sunset). Therefore, this paper presents the ESS integrated gas turbine (EIGT) system, which is an integrated system of energy storage system (ESS) using micro gas turbine (MGT) and reused battery. This research contributes to verifying the utility of reused battery and compensating a duck curve through operation in a system that integrates an energy storage system using micro gas turbine and reused battery, which are small power sources that can be operated independently of the existing renewable energy. According to the result of this research, the state of health (SOH), state of charge (SOC), internal resistance, temperature, and heating rate of the reused battery were verified by supplying power, which is increased by about 66 % after sunset in a duck curve phenomenon. Accordingly, it may contribute to stabilizing the power system in the duck curve phenomenon.

Frequency support strategy for single-Stage grid-Connected photovoltaic generation with active power reserves

Large-scale photovoltaic (PV) generation grid connection causes lack of inertia and insufficient frequency regulation capacity of power system. To solve this problem, this study proposed the active power-frequency droop control (APFDC) and virtual inertia control (VIC) for single-stage PV generation. PV generation is able to participate in the grid frequency regulation by improving the control system of voltage source converter (VSC). The effect of control parameters on the inertia characteristic of PV generation is analyzed. On this basis, the distribution mechanism of unbalanced active power among PV generators with inertia control strategy is revealed. The simulation results indicated that PV generation can be controlled by setting the control strategy of the voltage source converter (VSC) to reduce or increase the active power; it also takes part in the frequency regulation of the system. The inertia provided by PV generation is controllable and frequency-dependent, increases with the increase in control gain, the decrease in the time constant of VIC, and the decrease in phase-locked loop (PLL) control bandwidth.