Power Reserve Research Articles

Development of the model and improvement of the method of automated control of steam turbine parameters to minimize the power imbalance in the energy system to increase its efficiency

The object of research is the process of regulating power imbalances due to automated control of steam turbine parameters. The work solves the problem of minimizing power imbalances in the electric power system by developing a model of automated control of steam turbine parameters. This will ensure high-quality regulation of frequency and power, increase the efficiency and stability of the electric power system, and provide a new management method for reliable power supply to consumers. The paper analyzes existing models and methods of power imbalance regulation, develops a dynamic model of automated control of K-300-240 steam turbines, which includes a mechanical-hydraulic system, a steam boiler and a steam superheater. As a result of the study, an improved power regulation method was proposed, which ensures efficient operation of the electric power system. The evaluation of the effectiveness of the regulation of imbalances was carried out on the basis of the proposed criterion of the efficiency of electricity supply and consumption, which is based on the convolution of partial criteria into the general criterion of the efficiency of electricity supply. The following criteria were proposed as partial criteria for electricity supply and consumption: volume criterion, quality criterion, and electricity supply efficiency criterion. The research results indicate the need for a reserve on each steam turbine in the amount of 10 % of its nominal power, which is explained by the assessment of the efficiency of electricity supply among the considered modes of operation of the systems. The presence of a power reserve on each steam turbine in the amount of 10 % of their nominal power ensures the most efficient power supply within the considered modes of operation of the power system, taking into account disturbances and as an imbalance of power generation and power consumption. The obtained research results can be applied in the strategy of primary regulation of power imbalances in the electric power system, thanks to the creation of a power reserve in the amount of 10 % of the nominal power on each steam turbine, and the organization of automated control of steam turbine parameters.

Hydro-thermal Power Reserve Allocation Under Outage Uncertainty

In recent decades, the energy sector, namely energy markets have proved to be changing considerably. Most of these changes result in increasing volatility related to global political and environmental factors. This volatility affects all entities operating in the power sector. This paper focuses on the power plant operator’s perspective. First, the global context of the power sector is discussed and the power plant operator’s role is reviewed. Further, the problem of power reserve is discussed revealing the motivations of the presented work. The central contribution of this work lies in the formulation and development of a stochastic model of power reserve coupled with a mixed-integer programming scheduling model. In the results section, we show that the developed model allocates power reserve in an optimal way respecting the technical and economic parameters of the power plants as well as handling the stochastic nature of the power reserve allocation problem by minimizing the mean value of the sum of penalty for not delivering contracted power and lost opportunity.

A Coordinated Emergency Frequency Control Strategy Based on Output Regulation Approach for an Isolated Industrial Microgrid

Constructing isolated industrial microgrids with wind power is beneficial for improving the economic benefits of high-energy-consuming production, such as the electrolytic aluminum industry. Due to the specialized structure of industrial microgrids and the unique characteristics of the electrolytic aluminum load (EAL), the common emergency frequency control methods do not apply to the specific operational requirements of isolated industrial microgrids. Since EALs have huge regulating capacities and fast responses, this paper proposes a coordinated emergency frequency control scheme to deal with power disturbances in isolated industrial microgrids. The coordinated frequency control model of an industrial microgrid considering demand-side participation is derived. With the help of output regulation theory, a practical, feasible coordinated frequency controller is designed by introducing frequency deviation and power disturbance as feedback control signals. The proposed control scheme achieves reserve power distribution between the generation and demand sides. The microgrid frequency can be maintained within a permitted range in the presence of large power imbalances. The simulation results conducted in an actual isolated industrial microgrid validate the effectiveness and dynamic performance of the proposed control scheme.

Emergency frequency control method for power system containing wind generation based on coordination of frequency-autonomous-response, constant-power-control-switching and generator-tripping or load-shedding

Wind generators have the ability to quickly and flexibly control power, improving the freedom degree in emergency frequency control within the power system. The emergency frequency support can be provided to the grid by autonomously emulating synchronous generators that respond to frequency changes, constant-power-control-switching (CPCS) with advanced power reserves, generator-tripping (GT) or load-shedding (LS). However, these control methods are not always effectively coordinated, the frequency control potential of wind generators is not fully utilized due to the difficulty in quantifying security conditions and frequency control capability. Therefore, A novel concept, termed synthetic autonomous regulating speed proposed as a means of characterizing the frequency-autonomous-response (FAR) capability of the WG. A method for quantifying frequency security conditions of the power system containing WGs is proposed by establishing the dynamic frequency security domain under the joint effect of FAR of the WG and the SG, CPCS of the WG, and GT or LS. Thus, an improved emergency frequency control method based on the coordination between FAR, GT or LS, and CPCS of the wind generator is provided. Case studies demonstrate that this method can effectively reduce the amounts of GT or LS and CPCS while ensuring frequency security.

An optimal approach for active power reserve of a de-loaded PV generator operating in coordination with synchronous generators

The de-loading operation of PVs, where PVs are operated with an active power reserve has picked up the interest of the researchers in the last few years. However, in an integrated system, where the PV generators are operated in coordination with the synchronous generators, the estimation of the amount of the active power reserve of the PV generator is crucial. A very high reserve will cause an excessive economical loss and a very low reserve will deteriorate the frequency regulation capability. Therefore, in this paper, the cost function of an integrated system is minimised using the particle swarm optimisation algorithm, and the amount of power reserve of the PV generator and operating power values of synchronous generators are obtained as a result of the minimisation. Further, the frequency response of the system for the obtained power reserve value is investigated by suddenly adding the load in the system. The lowest and highest system costs of 2521.87 and 4474.98 $/h are obtained for the irradiance 1000 and 400 W/m2 respectively, and upon a significant load change, the frequency deviation limits to 0.4513 for a reserve value of 29.0712 MW. System modelling and validation have been carried out in the SIMULINK toolbox of the MATLAB software.

A Versatile Platform for PV System Integration into Microgrids

Advancing decarbonization critically depends on the integration of PV systems into microgrids. However, this integration faces challenges, including the variability of photovoltaic solar energy production, the demands of energy management, and the complexities of grid synchronization and communication. To address these challenges, a PV emulator platform is an essential tool. This paper presents a novel four-layer PV emulator platform that seamlessly integrates power systems, control systems, measurement instrumentation, and communication processes. The proposed platform enables the emulation of I-V curves and the dynamic adjustment of operating points—including both the maximum power point (MPP) and power reserve point (PRP)—as well as temperature and irradiance while providing sufficient power capacity for microgrid integration. To validate its effectiveness, the platform was assessed for its capability to adjust operating points, such as MPPs or PRPs, under varying irradiance and temperature conditions. The results show that the platform effectively adjusts operating points with a deviation of less than 5% from theoretical values and successfully tracks a sequence of operating points. This performance underscores the platform’s potential in integrating and managing PV systems within microgrid environments, thereby advancing the path to decarbonization.

Dynamic adaptation in power transmission: integrating robust optimization with online learning for renewable uncertainties

IntroductionThe increasing integration of renewable energy sources, such as wind and solar, into power grids introduces significant challenges due to their inherent variability and unpredictability. Traditional fossil-fuel-based power systems are ill-equipped to maintain stability and cost-effectiveness in this evolving energy landscape.MethodsThis study presents a novel framework that integrates robust optimization with online learning to dynamically manage uncertainties in renewable energy generation. Robust optimization ensures system resilience under worst-case scenarios, while the online learning component continuously updates operational strategies based on real-time data. The framework was tested using an IEEE 30-bus test system under varying levels of renewable energy integration.ResultsSimulation results show that the proposed framework reduces operational costs by up to 12% and enhances system reliability by 1.4% as renewable energy integration increases from 10% to 50%. Additionally, the need for reserve power is significantly reduced, particularly under conditions of high variability in renewable energy outputs.DiscussionThe integration of robust optimization with online learning provides a dynamic and adaptive solution for the sustainable management of power transmission systems. This approach not only improves economic and environmental outcomes but also enhances grid stability, making it a promising strategy for addressing the challenges posed by the increasing reliance on renewable energy.

A wind farm control strategy for frequency regulation reserve: Optimize wake loss and frequency support capability

—With a high proportion of renewable energy, the issue of grid frequency fluctuations is becoming increasingly prominent. To tackle this challenge, wind farms can enhance frequency regulation response by increasing rotational kinetic energy through overspeed control. However, this approach may result in energy losses due to the wake effect. This paper proposes an optimized configuration strategy for wind farm frequency regulation reserve (FRR), utilizing pitch angle cooperative control to reduce wake losses. The objective is to explore the optimal configuration for maximizing wind energy utilization under FRR conditions. A genetic algorithm is used to find the optimal control parameters in the established FLORIS-based wind farm power reserve wake model, which involves rotor speed and pitch angle control, to maximize output power and rotational kinetic energy. Based on this, a lookup table is constructed to map wind conditions to the optimal control parameters for different FRR level. According to the reserve power schedule, optimization control is applied to the wind farm. Simulation results show that, compared to the traditional equal distribution strategy for FRR power, the proposed control strategy can enhance the total kinetic energy reserve of the wind farm by optimizing wake loss, thereby improving frequency support capability.

Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization

The volatility and uncertainty associated with the high proportion of wind and PV output in the new power system significantly impact the power and energy balance, making it challenging to accurately assess the risks related to renewable energy abandonment and supply guarantee. Therefore, a probabilistic power and energy balance risk analysis method based on distributed robust optimization is proposed. Firstly, the affine factor and the flexible ramp reserve capacity of thermal power are combined to establish a probabilistic index, which serves to characterize the risk associated with the power and energy balance. Drawing upon the principles of the conditional value at risk theory, the risk indexes of the load shedding power and curtailment power under a certain confidence probability are proposed. Secondly, the probability distribution fuzzy sets of uncertain variables are constructed using the distributionally robust method to measure the Wasserstein distance between different probability distributions. Finally, aiming at minimizing the operation cost of thermal power, the risk cost of power abandonment, and the risk cost of load shedding, a distributed robust optimal scheduling model based on a flexible ramp reserve of thermal power is established.

Study on photovoltaic primary frequency control strategy at different time scales

AbstractDuring the participation of photovoltaics in grid frequency regulation, different frequency regulation tasks are required at different time scales. The grid demands that photovoltaics (PVs) improve steady‐state frequency when facing short‐term load fluctuations, while also enhancing frequency response to long‐term environmental and load changes. Therefore, this study takes different time scales as the starting point. First, a two‐stage PV grid‐connected inverter generation system model is established, and an overall control strategy is proposed. Next, for short‐term time scales, a virtual inertia strategy based on direct current (DC) voltage droop control is proposed to utilize the energy storage effect of DC capacitors to suppress frequency fluctuations. For long‐term time scales, a strategy for controlling the variable reactive power reserve capacity is proposed to address the inadequacy of frequency regulation caused by traditional fixed de‐rating rate strategies and redundant standby power. Finally, the effectiveness of the proposed strategies is verified through model validation in MATLAB/Simulink. Simulation results demonstrate the effectiveness of the strategies at different time scales, aiding in improving grid frequency response.

Under-Frequency Load Shedding for Power Reserve Management in Islanded Microgrids

Under-Frequency Load Shedding for Power Reserve Management in Islanded Microgrids

Improving primary frequency response in photovoltaic systems using hybrid inertia and intelligent control techniques

Abstract Low inertia poses a significant challenge to the widespread integration of photovoltaic (PV) systems into the grid, particularly affecting frequency stability. This paper addresses this challenge by proposing an advanced hybrid inertia (AHI) approach, characterized by the integration of real and virtual inertia, combined with the application of intelligent control techniques, to enhance the primary frequency response of a PV system. Internal inertia is provided by a synchronous generator (SG) acting as a compensator, while virtual inertia is generated through a real-time deloading strategy in the PV plant. The AHI is implemented on an isolated grid, utilizing various intelligent control techniques to improve frequency stability. The intelligent techniques employed include genetic algorithms (GA) and fuzzy logic controllers (FLC), which do not require mathematical modeling. This allows them to overcome the nonlinear dynamics of the PV plant and the uncertainties associated with climatic changes. These techniques are applied to the nonlinear components on the generator side, including the governor loop, DC-DC converter loop, and power reserve injection management loop. A frequency fluctuation scenario, induced by generating power perturbations in the proposed system, demonstrates and validates the improvement in frequency stability achieved by the HI and intelligent techniques. All tests are conducted using MATLAB Simulink. Various simulation results show a significant improvement in frequency stability through the incorporation of HI and intelligent control techniques.

Hierarchical power reserve control of string-inverter-based photovoltaic power plant for primary frequency control

Retaining a certain power reserve is the precondition for a photovoltaic power plant (PVPP) to provide primary frequency control. Usually, a string-inverter-based PVPP may consist of hundreds of string inverters, and each string inverter has several direct current (DC) input channels. Thus, how to allocate the power reserve among so many controllable units is a challenging problem. In this paper, a hierarchical power reserve control method for a string-inverter-based PVPP to provide primary frequency control is introduced. In the inverter layer, the power reserve of each DC input channel is determined to balance the DC voltage variation of each channel during primary frequency control. In the plant layer, the power reserve is allocated to each PV cluster based on the predicted power generated by long short-term memory (LSTM) network, and the PV clusters are formed based on the historical generated power of each string inverter using K-means method. Furthermore, the string inverters within the same PV cluster evenly share the power reserve. To validate the proposed method, case studies in both the inverter layer and plant layer are carried out; the results verify the effectiveness of the proposed method.

The prospects for the use of alternative gel formers for hydraulic fracturing

The article discusses the relevance of using alternative gel-forming agents in the preparation of fracturing fluids for hydraulic fracturing (HF). Besides the obvious tasks, such as increasing the residual conductivity of the fractures created during stimulation, it also addresses the impact of alternative gelforming agents on the treatment process. The author, supported by field data, concludes that under otherwise equal conditions, replacing traditional fracturing fluids with alternative ones significantly reduces frictional pressure losses in the pipes, which is particularly important when treating deep and extensive horizontal wells with limited internal pipe diameters. Moreover, the aforementioned impact of gel-forming agents on frictional pressure losses allows for a reserve of power in the hydraulic fracturing fleet equipment. Consequently, the treatment can be performed with higher flow rates under otherwise equal conditions, without the need for additional high-pressure pumps or the deployment of more expensive, stronger, larger-diameter tubing. Another important conclusion reached by the author is that due to the specific properties of alternative fracturing fluids, their ability to transport and retain proppant is significantly increased. This property of fracturing fluids is especially important when treating low-permeability, fractured formations and during the stimulation of long horizontal wells. On the other hand, the use of alternative gel-forming agents raises the requirements for the controlled breakdown of fracturing fluids, complicating the task of selecting a rational formulation and necessitating additional research.

Innovative real-time deloading approach to wind systems with applications in primary frequency control

The integration of wind systems into the electrical grid faces a significant challenge due to the absence of inertia, a fundamental characteristic of this system. This lack of internal inertia directly impacts frequency stability. To address this challenge, various techniques have been developed, including storage systems, inertia emulation, and deloading methods, among others. Among these approaches, the latter method appears to be more suitable. This study introduces a novel deloading approach that offers several advantages. The proposed strategy is an online technique that is easy to implement. It does not necessitate mathematical models, estimations, prior knowledge of wind turbine (WT) characteristics, or the use of an extra sensor, thereby simplifying the approach. This approach is based on a WT cycle consisting of two consecutive operating modes: a maximum power measurement (MPM) mode and a power reserve (PR) mode. These modes are controlled by two controllers: a pitch angle controller (PAC) and a perturb and observe (P&O) algorithm controller. The cycle is managed and initiated using a monitoring signal with multiple configurations, providing various solutions and implementation possibilities. The effectiveness of this approach has been verified through numerous simulation tests conducted on both finite and isolated grids. These simulations employ theoretical and actual wind speed signals in the MATLAB Simulink environment, confirming the practicality and reliability of the proposed method.

Frequency regulation controller for multi‐area interconnected power system

AbstractBy increasing the number of electric vehicles (EVs) to achieve a less carbon environment, not only they consume power from the grid to be charged, but also do they deliver power to the grid, and this can play a significant role in load frequency control. However, EVs take part in frequency regulation based on their state of charge (SoC) which will cause uncertainties. In order to manage these uncertainties, EV aggregator (EVA) concept has been introduced. The EV owner participates in the demand response program provided by the EVA arbitrarily considering her/his requirements. Accordingly, EVA calculates the up and down power reserve for the power system operator. Following any frequency deviation, EVA sends the proper commands to each EV to consume or to inject power to the system. There are also communication delays between different parts, uncertainties, and non‐linearities that existed in the power system. To overcome these issues, this study proposes a new robust load frequency controller based on feedback theory and artificial neural network which is designed through the non‐linear multi‐machine power system. Simulation results on IEEE 39‐bus power system show that the proposed controller regulates frequency more desirably in comparison with other methods.

The Design Concept of Integrated Pedestrian Sidewalk with Solar Plants as a Form of Green Campus Development at the Bali Land Transportation Polytechnic

Abstract An important aspect of creating a viable campus environment is providing safe and comfortable walking paths. Proper walking paths give some advantages for students, including improved physical and mental health, transportation efficiency, and increased Student satisfaction and happiness. The pedestrian sidewalk area at Bali Land Transportation Polytechnic (Poltrada Bali) covers 3800 m2, experiencing high pedestrian activity but lacking protective roofing to enhance pedestrian comfort. Based on the pedestrian sidewalk area, a solar power plant as support for the green canopy construction combined with shading vines is possible. The generated electrical energy serves as the power source for the Public Electric Vehicle Charging Stations (PEVCS) in the campus parking lot as a support for the electric vehicle acceleration program in Bali province. In addition to PEVCS, energy extraction surplus is used as alternative energy for street lighting facilities in the campus area. In this study, the design concept of a shaded pedestrian sidewalk has been carried out, with multiple benefits as solar plants using Delphi as a variable identification and validation tool, and SketchUp software to visualize design shapes aesthetically. The results show that a pedestrian comfort level of 94% was obtained and the maximum power generation of 934,800 Wp, thus it was able to meet the 887,832 W campus operational power reserve needs, street and garden lights of 9,728 W, and the power requirements of two PEVCS units of 22,000 W with a surplus of 15,240 W electric power.

Assessing power profile characteristics in solar PV-storage integrated electricity markets: A quantitative study

Integrating solar PV inverters and storage devices into the modern power grid generates multiple power profiles with varying magnitudes. The intermittent nature of PV necessitates installing storage devices to reduce unit commitment challenges and accommodate reserve power. This paper proposes various operational factors to determine the boundaries for individual and aggregated power profiles within a cluster of PV systems and storage units. The study utilizes dispatchability and operating reserve factors (primary and secondary) during storage discharge mode to extract dispatchable power and primary and secondary reserve power. Similarly, storage arbitrage and non-dispatchability factors extract arbitrage, non-dispatchable, and a portion of supplemental or tertiary reserve power during storage charging mode. An optimization model leveraging mixed-integer linear programming is formulated to minimize operational expenditures considering these hybrid PV-storage power profiles. Extrapolated electricity market rates for hybrid power profiles are projected using the prevailing prices of photovoltaic (PV) systems and storage technologies. This paper utilizes the proposed aggregated operational factors as constraints while extracting these power profiles for a cluster of PV-storages. The efficacy of the proposed optimization framework is tested on a modified IEEE 34-bus system by adding 10 PV-storage devices on 10 buses. The final quantitative values correspond to the percent penetration and arbitrage of these power profiles.

Model‐Based Systems Engineering Approach for Designing an Artificial Magnetic Field Generator System for Spacecraft Radiation Protection

AbstractThe hazardous environment of space, dominated by cosmic and solar radiation, poses a significant threat to spacecraft and their occupants. Traditional radiation shielding methods, like passive materials, have limitations in weight and effectiveness. An artificial magnetic field generator system emerges as a promising solution to replicate Earth's magnetosphere, providing a protective magnetic shield against harmful radiation. (Dick, Launius, 2007) This paper presents a Model‐Based Systems Engineering (MBSE) approach to the holistic modeling and design of such a system.Utilizing the MBSE approach, this study models the system's components, their interactions, and the offered services, incorporating Radiation Monitoring, Magnetic Shielding, Power Management, System Health & Diagnostics, and Crew Communication services. The conceptual data model captures key entities and their relationships, ensuring a coherent integration of the system's parts. The activity diagram illustrates the operational flow, providing clarity on the system's dynamic behavior under varying radiation conditions and power reserves. A services taxonomy is developed to hierarchically categorize and ensure the comprehensive functionality of the system.The application of MBSE methodology provides numerous advantages, including a unified visualization of the system's complexities, enhanced stakeholder communication, and a streamlined validation and verification process. Furthermore, the flexibility inherent in the MBSE approach ensures that the system can be easily updated or scaled based on advancements in technology or changing mission requirements. (ECLIPSE Suite, 2022) The MBSE approach's application to the design of an artificial magnetic field generator system for spacecraft presents a robust and systematic method to ensure optimal performance, safety, and adaptability in the perilous realm of space.

Managing power balance and reserve feasibility in the AC unit commitment problem

Incorporating the AC power flow equations into unit commitment models has the potential to avoid costly corrective actions required by less accurate power flow approximations. However, research on unit commitment with AC power flow constraints has been limited to a few relatively small test networks. This work investigates large-scale AC unit commitment problems for the day-ahead market and develops decomposition algorithms capable of obtaining high-quality solutions at industry-relevant scales. The results illustrate that a simple algorithm that only seeks to satisfy unit commitment, reserve, and AC power balance constraints can obtain surprisingly high-quality solutions to this AC unit commitment problem. However, a naive strategy that prioritizes reserve feasibility leads to AC infeasibility, motivating the need to design heuristics that can effectively balance reserve and AC feasibility. Finally, this work explores a parallel decomposition strategy that allows the proposed algorithm to obtain feasible solutions on large cases within the two hour time limit required by typical day-ahead market operations.