Integrated Power System Research Articles

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.

A Novel Stochastic Unit Commitment Characterized by Closed-Loop Forecast-and-Decision for Wind Integrated Power Systems

A Novel Stochastic Unit Commitment Characterized by Closed-Loop Forecast-and-Decision for Wind Integrated Power Systems

Probabilistic forecast of electric vehicle charging demand: analysis of different aggregation levels and energy procurement

Electric vehicles (EVs) are expected to be vital in transitioning to a low-carbon energy system. However, integrating EVs into the power grid poses significant challenges for grid operators and energy suppliers, especially regarding the uncertainty and variability of EV charging demand. Accurate forecasting of EV charging demand is essential for optimal power system integration, yet previous studies have often only considered point predictions that are inadequate for risk assessment. Therefore, this paper compares different probabilistic forecasting models for the short-term prediction of EV charging demand at various aggregation levels, using a large and novel dataset of over 350,000 charging processes at more than 500 locations across Germany. The performance of both machine learning and deep learning methods is evaluated against a naïve benchmark model, and the impact of data availability on the forecasting models is investigated. Further, the paper examines the effects of forecast accuracy on energy procurement, which has so far received minor attention in the literature. The results show that machine learning methods such as Ada Boosting and Random Forest yield robust results with a normalized root mean square error of 0.42 and 0.41 and a mean absolute scaled error of 0.36 and 0.34 at the highest aggregation level. Furthermore, the results show the influence of different site compositions on the forecast quality and how many charging points are likely to yield a robust forecast. Energy and fleet managers can use the described method to reliably predict the required energy quantities for fleets of sufficient size and procure them at low risk.

A robust damping control for battery energy storage integrated power systems to mitigate inter-area oscillations

This paper presents the effect of a Battery Energy Storage System (BESS) on the power system inter-area oscillations under changing load conditions. The dynamic interaction between the BESS control modes and synchronous generators, along with BESS control parameters, influence the damping of prominent inter-area oscillations under different loading conditions. Furthermore, H∞ mixed sensitivity scheme-based Wide-Area Damping Controller (WADC) is proposed for BESS. This controller is designed using the Linear Matrix Inequality (LMI) framework to mitigate the prominent inter-area oscillation of the power system. Sensitivity to control parameter variation and the geometric measure of the observability are utilized to select the location and feedback signal for the WADC. The performance of the proposed WADC is compared with an Energy Storage System-based stabilizer and WADC proposed in an existing work on a modified New England ten-machine benchmark system. The Real-Time Digital Simulator (RTDS) platform is used to assess the real-time viability of the proposed WADC. The simulation results demonstrate that the proposed WADC can effectively diminish several inter-area modes. Additionally, it offers robust performance under varying load conditions, contingencies and with communication delays in feedback signals. The proposed controller is also effective under the system integrated with Doubly Fed Induction Generator-based Wind Turbine System.

Визначення граничних величин споживання електричної енергії засобами оптимізаційного моделювання

In the heating season of 2022/2023, as a result of the military aggression of the Russian Federation and targeted attacks on electric power facilities, a significant shortage of electric energy occurred in the Integrated power system of Ukraine. Restriction schedules and emergency disconnection of consumers were forcibly applied. In the conditions of such an unprecedented violation of the security of electricity supply, the problem of determining the limit values of electric energy and power consumption has gained new relevance for the electricity market participants. In this study, the problem of determining the optimal limit values of electricity consumption based on the criterion of maximum income from its sale to three groups of consumers was set and solved: "Critical infrastructure", "Households" and "Non-household consumers". The formation of the three specified groups is related to price discrimination in the electricity market and the need to supply critical infrastructure facilities without limits. The decision variables in the optimization model are proposed to be specified in fractions of the provision of electrical energy needs (unit fractions), which allows for establishing equal conditions regarding restrictions for all distribution system operators. To take into account the social significance of electric energy as a commodity, an additional constraint was included to the basic optimization model: the lower limit of the decision variable for the "Households" group. Approbation of the proposed optimization model was carried out using spreadsheet modeling in MS Excel on reported data on the results of electrical load measurements on regime days. The results of computational experiments are presented for the conditions of different values of the deficit of electric energy in the Integrated power system of Ukraine and different values of the additional constraint for the «Households» group, in particular, quantitative estimates of the consequences of the included constraints for the functioning of the electricity market. The proposed method of determining the limit values of electric energy consumption allows to formalize the procedure for decision-making according to predetermined rules and thereby achieve a fair distribution of limited resources. Keywords: electric energy consumption, shortage, limit value, optimization modelling, spreadsheet model.

General structures of control area cooperation for variable renewable energy integration in electric power systems

To integrate large-scale variable renewable energy resources (RESs) in modern power grids, the coordinating control area (CA) operation is the most cost-effective method. This article reviews the technical aspects of CA cooperation. Firstly, a brief overview of the active balancing control within each CA is discussed. Secondly, three general control structures for CA cooperation are innovatively proposed, the corresponding implementation details are analyzed, and some representative technologies are also provided in the systematic analysis. Then, some future research directions such as large-scale power sharing by DC, active power control of RES bases, and the new structure for distributed energy resources in local power grids are prospected. Finally, the changes in power systems brought about by their evolution and importance for further promoting cooperation between CAs are summarized.

Surface Modification of Silicon Nanowires with Siloxane Molecules for High-Performance Hydrovoltaic Devices.

Hydrovoltaic devices (HDs) based on silicon nanowires (SiNWs) have attracted significant attention due to their potential of high output power and good compatibility with Si-based photovoltaic devices for integrated power systems. However, it remains a major challenge to further improve the output performance of SiNW HDs for practical applications. Here, a new strategy to modify the surface of SiNWs with siloxane molecules is proposed to improve the output performance of the SiNW HDs. After modification, both the open-circuit voltage (Voc) and short-circuit current density (Jsc) of n-type SiNW HDs can be improved by approximately 30%, while the output power density can be greatly increased by over 200%. With siloxane modification, Si-OH groups on the surface of typical SiNWs are replaced by Si-O-Si chemical bonds that have a weaker electron-withdrawing capability. More free electrons in n-type SiNWs are liberated from surface bound states and participate in directed flow induced by water evaporation, thereby improving the output performance of HDs. The improved performance is significant for system integration applications as it reduces the number of required devices. Three siloxane-modified SiNW HDs in series are able to drive a 2 V light-emitting diode (LED), whereas four unmodified devices in series are initially needed for the same task. This work provides a simple yet effective strategy for surface modification to improve the output performance of SiNW HDs. Further research into the effect of different surface modifications on the performance of SiNW HDs will greatly promote their performance enhancement and practical applications.

Grid-Connected Solar-Biogas Power System for Cost Mitigation and Sustainability in a Bangladeshi University: A HOMER Pro Approach

This study examines the feasibility and impact of a solar-biogas power system integration at Pabna University of Science and Technology (PUST) in Bangladesh, optimized using HOMER Pro software. The main goal is to reduce energy costs and carbon emissions within the university. The proposed system combines solar and biogas with the existing grid, using net metering for enhanced efficiency and sustainability. The financial analysis shows a Total Net Present Cost (NPC) of BDT 231,587,200.00 with a competitive Levelized Cost of Energy (COE) at BDT 1.49 per kWh. The Internal Rate of Return (IRR) is 18.4%, with a payback period of 4.89 years, emphasizing the system's economic viability. Environmentally, it significantly reduces CO2 emissions from 1,960,780 kg to 840,268 kg annually, aligning with the university's sustainability goals. This study highlights the potential of renewable energy integration in Bangladeshi academic institutions, offering valuable insights for similar initiatives.

Operation and Coordinated Energy Management in Multi-Microgrids for Improved and Resilient Distributed Energy Resource Integration in Power Systems

Multi-microgrids (MMGs) revolutionize integrating and managing diverse distributed energy resources (DERs), significantly enhancing the overall efficiency of energy systems. Unlike traditional power systems, MMGs comprise interconnected microgrids that operate independently or collaboratively. This innovative concept adeptly addresses challenges posed by pulsed load effects, capitalizing on the cooperative nature of interconnected microgrids. A coordinated MMG system effectively redistributes and shares the impact of pulsed loads, mitigating voltage fluctuations and ensuring sustained system stability. The proposed cooperative MMG scheme optimizes power distribution and load prioritization, facilitating the seamless allocation of surplus energy from neighboring microgrids to meet sudden surges in demand. This study focuses on DC standalone multi-microgrid systems, showcasing their inherent adaptability, resilience, and operational efficiency in managing pulse, variable, and unpredictable generation deficits. Several experiments on a laboratory-scale DC multi-microgrid validate the system’s robust performance. Notably, transient current fluctuations during pulse loads are promptly stabilized through the effective collaboration of microgrids. Variable load experiments reveal distinct behaviors, shedding light on the profound influence of control strategies. This research reveals the transformative potential of MMGs in addressing energy challenges, with a particular focus on DC standalone multi-microgrid systems. The findings underscore the adaptability and resilience of the proposed cooperative scheme, marking a significant stride in the evolution of modern power systems.

Optimal Tuning of PID Controllers for LFC in Renewable Energy Source Integrated Power Systems Using an Improved PSO

The constant rise in energy demand and concerns about climate change have led to increased penetration of renewable energy sources (RES). Maintaining active power balance between generation and demand in power systems with significant penetration of these highly variable and intermittent renewable sources requires an efficient load frequency control (LFC) strategy. One such strategy that has gained the attention of researchers is optimal tuning of PID controllers of LFC using metaheuristic method. This paper presents a PSO variant for optimal tuning of PID controllers for load frequency control of power system integrated with renewable energy resources. The proposed PID tuning technique is tested on a two-area power system commonly used in the literature. Seven scenarios have been used to validate the effectiveness of the proposed Load Frequency Control. For more realistic evaluation, governor dead band and communication time delays have been incorporated in the test system in one of the scenarios. Simulation results obtained when compared with those of three well-known PID-tuning metaheuristic algorithms produced shorter settling time and smaller frequency and tie line power deviations.

An optimal membership function based Fuzzy-[formula omitted] stabilizer design to suppress low frequency oscillation in synchronous generator

An optimal membership function-based fractional order fuzzy proportional integral (Fuzzy-PIλ) power system stabilizer (PSS) is designed to suppress low frequency oscillation (LFO) in a synchronous generator connected to an infinite bus power system. Speed deviation and the change in speed deviation of synchronous generator due to LFO are taken as inputs of the fuzzy controller, and the parameters of a fractional-order PI controller (proportional gain, integral gain, and the fractional term in integral control action) are taken as fuzzy output variables. The range, scaling, and shape of the membership functions of the fuzzy controller are optimized such that it can tune the fractional order proportional integral (PIλ) stabilizer under any disturbance or parametric uncertainty in the synchronous generator. The advantage of the proposed stabilizer is that it can handle a wide range of disturbances and adjust the gains of the control parameters for the system. A nonlinear dynamic acceleration coefficient-based class-topper optimization is applied to optimize the fuzzy settings. The robustness and sensitivity of the proposed optimal Fuzzy-PIλ stabilizer are verified under different scenarios for the synchronous generator and compared with available results.

Advancing Green Energy Integration in Power Systems for Enhanced Sustainability: A Review

Advancing Green Energy Integration in Power Systems for Enhanced Sustainability: A Review

Online Estimation of Disturbance Size and Frequency Nadir Prediction in Renewable Energy Integrated Power Systems

The displacement of conventional synchronous generation by Inverter-Based Resources (IBRs) poses critical challenges to the frequency stability of Renewable Energy (RE) integrated power systems. An increased shift towards green energy by integrating RE sources that provide little or no inertia results in a high Rate of Change of Frequency (RoCoF) and deteriorated frequency nadir/zenith following a credible system disturbance. Prediction of frequency metrics, such as frequency nadir and RoCoF, immediately after disturbances will help grid operators to take preventive/corrective actions, such as the deployment of faster frequency control, to ensure secure and stable grid operation. This paper presents an easy-to-implement analytical method to estimate disturbance size in a power system immediately following a contingency which is then used for predicting frequency nadir. The proposed estimation method uses active power measurements from a limited number of monitoring nodes and an adaptive bus admittance matrix of the system for the disturbance size estimation. The estimated disturbance size is then used to predict frequency nadir using a Neural Network (NN) based method. The performance and accuracy of the presented approach are evaluated using a standard IEEE 39 bus system and a real-life Gujarat power system in India through extensive simulations in DIgSILENT PowerFactory, considering various cases of disturbance size, type, and location.