Integrated Power System Research Articles

Coordination of SRF-PLL and Grid Forming Inverter Control in Microgrid with Solar PV and Energy Storage

Recently, there has been a huge advancement in renewable energy integration in power systems. Power converters with grid-forming or grid-following topologies are typically employed to link these decentralized power sources to the grid. However, because distributed generation has less inertia than synchronous generators, their use of renewable energy sources threatens the electrical grid’s reliability. Suitable control approaches for ensuring frequency and voltage stability in the grid-connected form of operation are established in this study, which offers dynamic, seamless power switching in the islanded mode of operation. In this research, effective Phase Locked Loop (PLL) techniques for grid-forming (GFM) and grid-following (GFL) converters are designed to achieve a smooth transition from grid-tied to islanded mode of operation. In this work, PLL configurations are implemented while considering the active and reactive power, frequency, voltage, and current parameters of the system, and ensuring voltage and frequency stability. The simulation results in a microgrid network that ensures a smooth transition of power transfer while switching between modes of operation, and supports the voltage and frequency stability of the system.

Considering the reliability of gas supply to power plants in the analysis of electric power system adequacy

One of the promising directions for further development of the methodology for investigating and ensuring the reliability of energy systems is the consideration of integrated energy systems. This is caused by the need for the adequate reflection of their joint operation. Previously, the authors proposed several methodological approaches based on "node," "system," and "evaluation" to assess the adequacy of an electric power system when this is operating jointly with a gas supply system. In that case, the focus was made only on high-pressure gas supply systems (simplified calculation). This work aims to consider not only the high-pressure gas systems, but also to take into account the influence of lowpressure gas systems (refined calculation) on the adequacy of electric power system. This approach appears to be more technologically advanced and corresponds to the real conditions of the functioning of integrated power systems. The studies were carried out using the “node” approach, its reference calculation being the most accurate one. The methods applied in the research are probability theory and mathematical statistics: a particular theorem on the repetition of experiments (Bernoulli's trial), calculation of probability distribution series, theorems of addition and multiplication of probabilities. A comparative analysis of reference calculations of the electric power system adequacy was carried out for simplified and refined connection schemes in the gas system (two cases were considered: a highly reliable low-pressure gas system and a low-reliability one). The calculations were performed on an illustrative example of a power system. Assessment of the load supply reliability in integrated systems must factor in the process features of the systems at issue, the block diagram of their connections, as well as the accuracy of the results obtained and the complexity of searching and preparing initial data for the corresponding research model.

Joint non-fragile automatic generation control and multi-event driven mechanism co-design for wind integrated power system under denial of services attacks

Denial of services (DoS) attacks exist in wind integrated power system. DoS attacks can cause network-induced delay and packages loss in information transmission. Meanwhile, considering the parameter perturbation of controller and system model uncertainty in wind integrated power system, these may cause the system dynamic performances degradation or even instability. Based on the above considerations, the joint non-fragile automatic generation robust control of wind integrated power system under DoS attacks is studied in this paper. In order to ensure the expected system performance and more effectively utilize the limited network communication resources under DoS attacks, a novel dynamic multi-event driven mechanism based joint non-fragile H∞ automatic generation control method is proposed. By constructing a suitable Lyapunov-Krasovskii functional and utilizing the Shur complement lemma to handle nonlinear matrix inequality, the sufficient conditions are derived to guarantee the asymptotic stability of wind integrated power system under DoS attacks. Furthermore, the performance of the proposed non-fragile regulator is demonstrated through a four-area wind integrated power system to show the feasibility and applicability. The analysis result indicates that the proposed scheme provides stronger robustness, higher wind energy utilization efficiency and more efficient communication mechanism.

ICEEMDAN-Informer-GWO: a hybrid model for accurate wind speed prediction.

Extensive research has been diligently conducted on wind energy technologies in response to pressing global environmental challenges and the growing demand for energy. Accurate wind speed predictions are crucial for the effective integration of large wind power systems. This study presents a novel and hybrid framework called ICEEMDAN-Informer-GWO, which combines three components to enhance the accuracy of wind speed predictions. The improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) component improves the decomposition of wind speed data, the Informer model provides computationally efficient wind speed predictions, and the grey wolf optimisation (GWO) algorithm optimises the parameters of the Informer model to achieve superior performance. Three different sets of wind speed prediction (WSP) models and wind farm data from Block Island, Gulf Coast, and Garden City are used to thoroughly assess the proposed hybrid framework. This evaluation focusses on WSP for three specific time horizons: 5minutes, 30minutes, and 1hour ahead. The results obtained from the three conducted experiments conclusively demonstrate that the proposed hybrid framework exhibits superior performance, leading to statistically significant improvements across all three time horizons.

Reinforcement learning-driven proximal policy optimization-based voltage control for PV and WT integrated power system

The depletion of conventional fuel reserves and the high carbon emissions have alarmed the energy sector drivers. The integration of renewable energy resources (RERs) towards power system transformation is an obvious approach for a new-zero future. However, this integration also brings challenges in terms of voltage stability and power losses due to the variable output of RERs. To address these challenges, this work proposes a novel approach utilizing photovoltaic (PV) inverters and static var compensators (SVCs) for reactive power control in power distribution networks (PDNs). It enhances voltage stability and minimizes power losses. The proposed study deploys a proximal policy optimization (PPO) algorithm for real-time communication and control between reactive power devices. Performance evaluation was made on an IEEE-33 Bus system to demonstrate the effectiveness of the proposed scheme in integrating RER-based distributed generators (DGs). The proposed system achieved 68 % voltage control, keeping the voltage within a certain range of ±5 % while minimizing power losses. The proposed system also reduced the voltage out-of-control ratio to 0.044, which indicates minimum voltage deviation from the standard value. The proposed study provides a promising solution for controlling the voltage of DGs integrated PDN, which can potentially enhance the efficiency and reliability of the power system.

Ancillary services from wind and solar energy in modern power grids: A comprehensive review and simulation study

Renewable energy sources like wind and solar have increased demand for surplus power capacity. The demand is primarily fueled by the growing impact of forecasting errors associated with these intermittent energy sources. Implementing advanced control methods for automatic generation control (AGC) is essential to integrate wind and solar power with conventional generation sources to balance the power system and reduce reliance on traditional reserves. Therefore, this paper comprehensively overviews solar and wind energy integration in the AGC framework to provide optimal grid ancillary services. Initially, the paper presents an overview of the basic equations used to integrate reserve power from the photovoltaic (PV) system by employing the de-loading strategy. Subsequently, a comprehensive review is conducted on integrating the PV system in AGC strategies to provide grid ancillary services. The study also analyzes the contribution of wind power in AGC services using relevant equations and past practices. The paper presents a real-time dynamic control strategy to optimize the dispatch of the AGC unit by integrating the operating reserves from wind energy systems in conjunction with thermal power systems. The study simulates an 8-bus, 5-machine model using the Dig-SILENT Power Factory. The findings reveal that utilizing operating reserves from wind power can significantly reduce large-scale forecasting errors in massively renewable energy resources (RES) integrated power systems, thereby ensuring the necessary system operational security and reducing the reliance on traditional generating units.

Hydrothermal–pumped-storage scheduling considering renewable energy uncertainty by improved cheetah optimization

The growth of renewable wind and solar energy in modern power systems affects the short-term scheduling of hydrothermal power generation. This article presents the optimum day-ahead scheduling of wind–solar–hydrothermal systems with pumped-storage plants (PSPs). To assess the contribution of PSPs in decreasing the generation costs of a renewable integrated power system, a scheduling model is formulated that considers different security constraints. An improved cheetah optimizer (ICO) is implemented on a renewable integrated test power system to solve the short-term optimum wind–solar–pumped-storage plant–hydrothermal scheduling (OWSPHTS) problem, taking into account all thermal, hydraulic and network constraints. Optimum solutions are obtained with different objectives considering renewable uncertainties. The proposed ICO solution method is compared with the similar algorithms in terms of optimal fuel costs, emissions, convergence success rate and computation time. The comparative solutions show that the introduced optimization technique is efficient for solving the real-world OWSPHTS problem.

Tuning hydrogen boil-off via inert gas insulation purge in a vapor cooled shielded fuel tank

Vapor cooled polymer composite tanks for liquid hydrogen are a newopportunity for light weight power-system integration into unmanned aerial vehicles. Vapor shielding has the ancillary benefit of pre-conditioning the hydrogen for use by a fuel cell. However, the mass flow rate required by a fuel cell should be matched by the natural boil-off rate of the tank. With limited ability to vary insulation thicknesses, the challenge becomes satisfying the fuel cell consumption in UAVs at different mass flow rates when at varying stages of flight from take-off, cruise, and landing. This paper provides experimental measurements of mass flow rate of hydrogen from the tank considering batch purging with helium or argon in the vapor cool shielded insulation layer. A 5-shell vapor cooled shielded tank is used with two layers of insulation including aerogel, helium or argon, and two vapor channels. A more complete understanding of system-level thermal conductance is determined by mass flow of hydrogen leaving the tank during hypothetical flight.

Evaluating the impact of virtual energy storage under air conditioning and building coupling on the performance of a grid-connected distributed energy system

Energy storage technologies are vital in improving the operation performance of grid-connected distributed energy systems. The adjustability of indoor temperature and the thermal inertia of buildings can form an excellent virtual energy storage. However, there are few studies on the impact of this virtual energy storage on the operation performance of grid-connected distributed energy systems. Therefore, this study first calculates the equivalent thermal resistance and thermal capacitance of a building by using EnergyPlus and establishes the first-order thermodynamic load calculation model. Subsequently, the system dynamic optimal scheduling model, considering the virtual energy storage, was developed based on the first-order thermodynamic load calculation model. The Gurobi nonconvex solver is used to optimize the model, and the results are compared with the optimal scheduling results without considering the virtual energy storage. The results indicate that, guided by time-of-use electricity pricing, the virtual energy storage effectively reduces the air conditioning load during high and peak tariff periods while increasing it during valley tariff periods. This change in air conditioning load leads to an increase in grid power consumption during valley tariff periods. However, it also improves the system's operation efficiency and ultimately reduces the total grid power and gas consumption. The lower energy consumption makes the primary energy saving rate and carbon dioxide emission reduction rate of Scenario 2 greater than zero compared to Scenario 1 and increases with the increase of renewable energy penetration of the integrated power system. Furthermore, affected by the difference in the proportion of grid power consumption under time-of-use electricity pricing and the total energy consumption, the system's operating cost in Scenario 2 is less than in Scenario 1. The reduction rates in summer and winter typical days are 1.95 % and 6.48 %, respectively. Therefore, fully utilizing the virtual energy storage under air conditioning and building coupling can reduce the operating cost, primary energy consumption, and carbon dioxide emissions of grid-connected distributed energy systems.

A Comprehensive Review of Battery‐Integrated Energy Harvesting Systems

AbstractAt the forefront of technological advancement, the proliferation of portable and wearable electronics has necessitated the development of innovative power solutions. As these devices become increasingly indispensable in daily life, the demand for sustainable and adaptable power sources has intensified. This review focuses on integrated self‐charging power systems (SCPSs), which synergize energy storage systems, particularly through rechargeable batteries like lithium‐ion batteries, with energy harvesting from solar, mechanical, thermal, and chemical energy. These SCPSs extend operational times, reduce recharging frequency, and have the potential to develop self‐sufficient power systems. The study explores various approaches to optimize both individual components and the integrated power system for wearable and flexible electronics, covering SCPSs that combine multiple energy‐harvesting strategies. Special attention is given to design considerations, material advancements, and engineering challenges, alongside the latest research breakthroughs in energy harvesting and storage technology. The review concludes with an assessment of the prospects and challenges in the field of battery‐integrated energy harvesting systems, highlighting the need for advancements in energy density, power output, and safety to meet the demands of modern electronics.

Cooperative constrained multi-objective dual-population evolutionary algorithm for optimal dispatching of wind-power integrated power system

Due to increasing uncertainty and multiple operational requirements of current power system, it brings great challenge to power dispatch of wind-power integrated power system. To address above problems, a cooperative constrained multi-objective dual-population evolutionary algorithm (CCMDEA) is proposed with uncertainty budget of wind power, which divides the intermittent power into different intervals with flexible uncertain parameters. On the basis of non-dominated sorting genetic algorithm III (NSGA-III), constraint violation (CV) is also involved to guide the population evolution combined with two defined populations: convergence population (CP) and diversity population (DP) to coordinate convergence and diversity performance of pareto-fronts, and a coordinated selection mechanism is designed to select suitable parents according to the state of evolutionary population, which can coordinate the convergence population and diversity population well. According to simulation results on two test systems, the efficiency and priority of the proposed algorithm is well verified, which also reveals that the proposed algorithm can be a viable way for solving power dispatching of wind-power integrated power system.

Inertia Energy-Based Required Capacity Calculation of BESS for Achieving Carbon Neutrality in Korean Power System

Frequency response performance in power systems is becoming vulnerable due to the transition toward the higher penetration of renewable energy such as achieving carbon neutrality. In particular, reducing power system inertia energy as the asynchronous generation increases could result in violating the frequency stability constraint when a disturbance occurs in the power systems. In order to control the rapidly fluctuating frequency of the power system with low inertia, it is necessary to introduce fast frequency response resources such as a Battery Energy Storage System (BESS). This paper proposes a method to calculate the required capacity of BESS for compensating the frequency control performance of the power system using inertia energy. For calculating the required capacity of BESS, the inertia energy in the critical power system, where frequency control performance marginally satisfies frequency stability constraint, should be calculated. Also, the inertia energy in the evaluated power system having deficit inertia energy should be calculated. By comparing power systems that respond with different dynamics when the same disturbance occurs, the proposed calculation corresponds to the ratio of inertia energy deficiency based on critical power system inertia energy within the power imbalance. Through various case studies employing Korean power systems, the effectiveness of the inertia energy-based calculation method for the required BESS is verified by the fact that the BESS integrated power system marginally satisfies the frequency stability constraint. In these study cases, it is found that the instant response of BESS is very effective for compensating the frequency control performance of the low inertia power system. By applying the proposed method, it is also found that about 840 MW of BESS can achieve carbon neutrality in the Korean power system.

Smart Grids Data Aggregation Method on Paillier Homomorphic Encryption

ABSTRACT Smart grid (SGs) is a highly integrated power system, it is gradually replacing the traditional power grid, but at present there are problems in the SGs data aggregation, such as user privacy leakage, grid data query inflexibly and data leakage. In order to solve these problems, this paper studied the SGs data aggregation method based on Paillier homomorphic encryption (HE). In this paper, the Paillier HE algorithm was used to study the power grid data, and the encrypted data was numerically calculated under different encryption states. It used the cloud computing center in the blockchain to directly aggregate the ciphertext data generated by users, and used the hash function to set the secret key to prevent the ciphertext data from being tampered with, and obtained the aggregate result of the original data after decryption by the power grid management center. When the number of security parameters was 30,000, the encryption time required by this method was 21.71 seconds. When the number of smart meters (SMs) was 80, the signature verification time required by this method was 2.31 seconds.

Identification method of all-operating-point admittance model for wind farms considering frequency-coupling characteristics

Admittance identification is an effective tool to solve the issue of black-box admittance modeling in wind farms. However, due to the large operating range of wind farms, it is difficult to accurately identify the admittance model of wind farms under all operating conditions, which limits the research on wideband oscillation caused by the interaction between wind farms and the power grid. This paper analyses the characteristics of the frequency-coupling admittance for wind farms. It is found that the power-sharing ratio of wind turbine generators (WTGs) affects the admittance characteristic of the wind farm, which leads to a huge number of operating points for the wind farm. The all-operating-point (AOP) admittance model of wind farms considering frequency-coupling characteristics is hard to directly identify. Aiming for this problem, this paper proposes to first identify the AOP-admittance model for WTGs. Then, based on the operating points of each WTG and the network structure, the AOP-admittance model of the wind farm is obtained via the admittance aggregation and model reduction method. This proposed method solves the problem of black-box admittance modeling and addresses the problem of dimension disaster in admittance modeling for wind farms. The identified model of the wind farm can be used to accurately assess the stability of the wind power integration system under various operating conditions. Finally, the effectiveness of the proposed method is verified through the admittance measurement and stability analysis of the wind farm.

Joint contribution of RTEM and AGC system for frequency stabilisation in renewable energy integrated power system

AbstractIncreasing penetration of variable renewable generations will diminish system inertia thereby degrading the conventional frequency regulation capability. As a result, maintaining frequency stability will be more and more challenging with traditional approaches. Even though renewable sources integration would jeopardise the grid stability, it also presents several opportunities as well. For example, converter‐interfaced generators can bid in real‐time electricity markets (RTEM) and provide short‐time dispatch to minimise load‐generation mismatch. In this paper, an integrated approach that accommodates discrete automatic generation control (AGC) system with a regulation mileage framework and RTEM model to balance generation and consumption is proposed. The RTEM model is assumed to have a five‐minute dispatch trading interval which is to some extent comparable to the discrete AGC system. Furthermore, a fractional order PID (FOPID) controller is equipped in the AGC system whose parameters are tuned using a novel metaheuristic‐based optimisation called Lichtenberg Algorithm (LA). The proposed framework is tested in a three‐area system under several operating conditions to reveal the improvement in the dynamic performance of the system. The objective function is also incorporated with mileage payment that allows a fair compensation rule for all the units.

ENERGY POTENTIAL OF DISTRIBUTED GENERATION AT POWERFUL BOILER HOUSES OF UKRAINE IN CONDITIONS OF MILITARY AGGRESSION

The Integrated Power System of Ukraine (IPS) is purposefully destroyed by the russian aggressor and suffers significant damage, which has caused long-term emergency interruptions in the power supply of critical infrastructure facilities, enterprises and the population. One of the ways to increase the stability of the IPS of Ukraine is to increase the share of distributed generation in its composition. The conceptual idea of solving this problem is the transformation of existing critical infrastructure objects from electricity consumers into electricity producers/suppliers who will provide their own electricity needs and the needs of other electricity consumers. Boiler houses of centralized heat supply systems (DHS) of Ukrainian cities with their existing electric power and fuel infrastructure can become such objects in wartime conditions. The author proposes the widespread introduction of energy-efficient cogeneration gas-piston units (CGPUs) at boiler houses of the DHS. The container-type CGPU is a typical mass-produced equipment that is manufactured in Ukraine and abroad and has a short implementation period (up to 5 days from the date of delivery to the industrial site of the boiler house). The high maneuverability of the CGPUs allows for an increase the flexibility of the IPS of Ukraine. The article presents the main technical and economic indicators of distributed generation with the use of CGPU at existing boiler houses for further national planning of the development of distributed generation during the martial law and post-war reconstruction of Ukraine. The application of CGPU at boiler houses of the DHS of Ukrainian cities has the potential to provide additional distributed generation with a total capacity of up to 2365.7 MW, in particular, 1224.8 MW at 158 boiler houses with a thermal capacity of 100 Gcal/h and more (612 CGPUs with an average unit electric power of 2.0 MW each); 561.9 MW at 409 boiler houses from 20 to 100 Gcal/h (803 CGPUs of 0.7 MW each); 561.9 MW in 2101 boiler houses from 3 to 20 Gcal/h (4136 CGPUs of 0.14 MW each). Under the conditions of 8 hours a day of use of the installed capacity of CGPUs, 567.8 thousand MWh of electricity will be produced every month at the boiler houses of the DHS (taking into account the consumption of the boiler houses for their own needs and release to the network to other consumers) and 136–142 million cubic meters of natural gas will be consumed. According to the average specific cost of modular CGPU (turnkey supply) from 800 to 950 USD/kW of installed electric capacity, capital costs for implementing the CGPUs with a total capacity of 2,365.7 MW will amount to USD 1.89–2.25 billion. Bibl. 31, Fig. 3.

Decarbonization pathways for bulk vessels: Integrating power systems, fuels, and control measures

The shipping industry must delineate feasible switching pathways of emission reduction technologies for vessels if it wants to meet the emission reduction targets set forth by the International Maritime Organization (IMO). This paper introduces a programming model integrating power systems, alternative fuels, and air emission control measures to decarbonize bulk vessel operations. The model captures the uncertainty in fuel prices and carbon emission prices. Reliable decision-making schemes are generated using interval quadratic programming. The results reveal that power systems will switch from mono-fuel internal combustion engines (MF ICE) to dual-fuel internal combustion engines (DF ICE). Traditional fossil fuels will progressively give way to carbon-neutral alternatives. The combination of air emission control measures will markedly reduce emissions.

Low-carbon economic dispatch strategy for integrated power system based on the substitution effect of carbon tax and carbon trading

As the introduction of carbon peak and carbon neutrality, the intensity of carbon regulation is growing. The power system, as the main body of carbon emission, will face the constraints of compound carbon reduction policy. To address this issue, a low-carbon economic dispatch strategy for integrated power system based on the substitution effect of carbon tax and carbon trading is proposed to improve the economic and environmental joint benefits. Firstly, facing the volatility characteristics of carbon trading price, Monte Carlo method is implemented to analyze the uncertainty of carbon trading price. Next, the renewable energy power and electricity load are forecast by long short-term memory method. Subsequently, the gray wolves algorithm is imposed to optimize the dispatch model and obtain the optimal dispatch plan. The comparative analysis reveals that the carbon emission and dynamic payback period of the optimized integrated power system are 4.37 × 106 t and 10.06 years, which are reduced 1.67 × 105 t and 0.3 years compared with the conventional power system. Besides, the economic analysis demonstrates that the substitution effect can decrease the unit cost of carbon emission by 1.03 USD/t. Finally, the comparative analysis manifests that the proposed dispatch model can effectively boost the economic and environmental joint benefits for the integrated power system.

Power System Integration of Electric Vehicles: A Review on Impacts and Contributions to the Smart Grid

In recent years, electric vehicles (EVs) have become increasingly popular, bringing about fundamental shifts in transportation to reduce greenhouse effects and accelerate progress toward decarbonization. The role of EVs has also experienced a paradigm shift for future energy networks as an active player in the form of vehicle-to-grid, grid-to-vehicle, and vehicle-to-vehicle technologies. EVs spend a significant part of the day parked and have a remarkable potential to contribute to energy sustainability as backup power units. In this way, EVs can be connected to the grid as stationary power units, providing a range of services to the power grid to increase its reliability and resilience. The available systems show that EVs can be used as alternative energy sources for various network systems like smart grids, microgrids, and virtual power plants besides transportation. While the grid–EV connection offers various contributions, it also has some limitations and effects. In this context, the current study highlights the power system impacts and key contributions of EVs connected to smart grids. Regarding the power system impacts in case of EV integration into smart grids, the challenges and difficulties are categorized under the power system stability, voltage/current distortions, load profile, and power losses. Voltage/current distortions like sags, unbalances, harmonics, and supraharmonics are also detailed in the study. Subsequently, the key contributions to the smart grid in terms of energy management, grid-quality support, grid balancing, and socio-economic impacts are explained. In the energy management part, issues such as power flow, load balancing, and renewable energy integration are elaborated. Then, the fault ride-through capability, reactive power compensation, harmonic mitigation, and grid loss reduction are presented to provide information on power quality enhancement. Lastly, the socio-economic impacts in terms of employment, net billing fees, integration with renewable energy sources, and environmental effects are elucidated in the present study.

Multi-Power System Electrical Source Fault Review

The phrase “Multi-Power System (MPS)” refers to an application that combines different energy conversion technologies to meet a specific energy need. These integrated power systems are rapidly being lauded as essential for future decarbonized grids to achieve optimum efficiency and cost reduction. The fact that MPSs multiply several sources also multiplies their advantages to be environmentally friendly and increases the possibility of energy autonomy as they do not depend on a single source. Consequently, this increases the reliability and reduces the production costs and the size of the storage system. However, the main disadvantages of such a system are the complexity of its architecture and the difficulty in managing the power level, which leads the system to face many faults and sometimes failure. In this case, a fault-tolerant control (FTC) system can automatically adapt to component malfunctions while maintaining closed-loop system stability to achieve acceptable performance. However, on the way to build efficient FTC, one first needs to study the faults that may occur in the system in order to tolerate them. This review paper presents the faults of the MPS electrical sources used in a hybrid system, including a photovoltaic generator and a diesel generator, plus a lead–acid battery as a storage device. Only the most-encountered faults are treated.