Power Subsystem Research Articles

Complementary Analysis and Performance Improvement of a Hydro-Wind Hybrid Power System

Hydropower as a flexible regulation resource is a rare choice to suppress the ever-increasing penetration of wind power in electrical power systems. The complementary characteristics and performance improvement of a hydro–wind hybrid power system based on a mathematical model of the hybrid power system is studied in this paper. This established model takes into account the stochastic variation in wind speeds in the wind power subsystem and the hydraulic–mechanical–electrical coupling characteristics of the hydropower subsystem. The complementary analysis is conducted based on the evaluation variables outputted by the established model, such as the wind power, hydro-regulation power, hydraulic power, and frequency. To make full use of the regulation capability of the hydropower system, the optimization of parameter settings is also carried out to improve complementary performances of the hybrid power system. The results from the complementary analysis show the detailed characteristics of hydro–wind coordinated operation under different types of real wind speeds. Here, 95% of installed hydro-capacity is used to complement the power shortage of the intermittent wind energy under the low wind speed. Alternatively, only around 66% of the installed hydro-capacity can be utilized to cope with the fluctuation in wind power under the medium and high wind speeds before the optimization of parameter settings. The recommended values and change rules of the control, hydraulic, and electrical parameters for the hydropower system are subsequently revealed from the analysis of parameter settings to contribute to a stable and safe hybrid power system. The results show that the optimized parameter can increase the maximal regulating capacity of the hydropower system by nearly 9 MW, approximately a sixth of the total installed hydropower capacity. The method and results obtained in this paper provide theoretical and technical guidance for the safe and economical operation of power stations.

Dual-time-scale zone economic model predictive control of micro gas turbine cogeneration systems

The utilization of decentralized micro gas turbine combined heat and power (MGT-CHP) units is considered as a prospective technique in power generation due to its high levels of fuel utilization rates and low emissions. However, the inherent strong coupling and complex timescale multiplicity make it challenging to realize optimal operation. To this end, this paper first establishes a precise mechanism model to attain a thorough understanding of the system properties. By conducting singular perturbation theory, the complex nonlinear system is decomposed into a fast power subsystem and a slow heat subsystem. Then, a dual-time-scale zone economic model predictive control (D-ZEMPC) algorithm, which is comprised of a fast EMPC and a slow EMPC, is applied to achieve dynamic synergy between heat and power supply by actively coordinating the two sub-controllers. Moreover, a zone tracking method is introduced for room temperature control, thereby yielding increased freedom in balancing the economic profits and thermal comfort. The simulation results in three scenarios along with the qualitative and quantitative discussions show that compared with the other two centralized EMPC algorithms, the proposed D-ZEMPC can significantly alleviate computational loads and reduce the simulation time by over 64.5 % while maintaining required thermal comfort with minimum fuel consumption.

Assessing the thermoeconomic performance of a solar-powered trigeneration system with an upgraded transcritical carbon dioxide unit

With the intervention of the industry in every aspect of human lifestyle on the one hand, and the prompt reduction in fossil fuel and their harms to the environment, including global warming, on the flip side, the importance of renewable sources of energy has been revealed more than ever. The presented study attempted to investigate a new configuration for a trigeneration configuration based on a solar renewable source. The proposed system comprises a parabolic trough solar collector segment to drive a transcritical carbon dioxide power and refrigeration subsystem, a dual-pressure organic Rankine cycle, and a thermal vapor compression process combined with a multi-effect desalination unit. The suggested configuration is carefully inspected from thermodynamic and economic perspectives, encompassing an analysis of a certain condition and a detailed parametric evaluation. Four decision parameters are employed for the parametric evaluation, in conjunction with two scenarios from a multi-objective particle swarm optimization combined with a linear programming method for multidimensional preference analysis as a decision-maker. The examination outputs bring out a net output power of 12.147 MW, a 7.707 MW cooling load, a 4.448 kg/s freshwater, and energetic and exergetic efficiencies of 15.286 % and 10.192 %, respectively. Moreover, examining the system's performance from an economic perspective reveals a total product cost rate of 954.249 $/h, leading to a 4.694-year payback period. This study optimizes energy usage and minimizes waste, offering industrial applications such as reducing fossil fuel dependence and lowering greenhouse gas emissions. It supports sustainable development and facilitates the global transition to cleaner energy sources.

Probabilistic prediction-based multi-objective optimization approach for multi-energy virtual power plant

Virtual power plants (VPPs) are encountering multiple challenges due to market uncertainties and power network instability. In this paper, a novel probabilistic prediction-based multi-objective optimization framework for VPP is proposed to maximize operating profit while minimizing pollutant emissions and voltage deviations in the distribution network, which considers the uncertainties of wind power and electricity price. In this framework, the VPP that participates in the energy and ancillary service markets firstly aggregates the wind farms, the electric vehicle charging stations (EVCS), and the combined cooling, heating, and power subsystems to improve the utilization efficiency and operational flexibility of multiple energy sources. Then, a new Pareto optimizer, called multi-objective hybrid sand cat swarm optimization and strength firefly algorithm, is proposed to tackle the multi-objective optimization model of VPP. The proposed hybrid algorithm utilizes the advantages of sand cat swarm optimization and strength firefly algorithm mechanisms to facilitate local exploitation and global exploration. Finally, a new deep reinforcement learning probabilistic prediction approach based on quantile regression deep deterministic policy gradient is modeled to evaluate the uncertainties. The proposed models and methods have been thoroughly discussed on a modified distributed network. It is calculated that compared with the VPP without EVCS, the operating profit of the proposed VPP increases by 18.69%, and the emissions and voltage deviation of the proposed VPP are reduced by 3.42% and 10.44%, respectively. Experimental results also prove that the performance of the proposed Pareto optimizer and probabilistic prediction approach is superior to other benchmark techniques.

Enhanced hybrid energy storage system combining battery and supercapacitor to extend nanosatellite lifespan

The power limitations of nanosatellites, particularly during peak demand periods such as data transmission and maneuvering, hinder their operational capabilities. Traditional Electrical Power Subsystems relying solely on batteries face challenges in delivering the necessary power density and maintaining battery life, especially during eclipses. This study proposes an innovative Hybrid Energy Storage System for a 3U nanosatellite, integrating high-energy-density batteries with high-power-density supercapacitors, using an active parallel hybrid topology with two bidirectional converters and an optimal power management strategy. Using MATLAB and Simulink models, the study optimizes the Hybrid Energy Storage System by focusing on minimizing the capacity rate and depth of discharge to extend battery life. Simulation results show a 53.42% reduction in depth of discharge compared to a battery-only system, indicating a significant extension of battery life. Additionally, the proposed system allows for a minimal 2.08% increase in overall mass while maintaining enhanced performance. This research fills a critical gap in the literature by exploring active Hybrid Energy Storage System topologies for spacecraft applications, beyond the traditional passive and semi-active configurations. The innovative power management strategy ensures efficient energy utilization, significantly enhancing the reliability and efficiency of nanosatellite missions. The findings offer a practical solution to improve mission performance and extend the operational lifespan of nanosatellites, paving the way for more robust and capable small satellite deployments.

Energy, exergy, economic, and environmental analyses and optimization of a multigeneration system considering high-temperature island environment

Renewable energy based multigeneration systems help satisfy the diverse demand for marine resources exploration in off-grid island area, where the storage of fluctuating renewable energy for continuous power supply becomes necessary. Therefore, this paper proposes a solar-driven multigeneration system for island environment integrated with energy storage and production of electricity, cooling, heating, and freshwater. The system comprises an ejector power subsystem, a multiple-effect distillation subsystem, and a CO2 binary mixture-based compressed gas energy storage subsystem. The system performance from the perspectives of energy, exergy, economics, and environment, as well as the impact on performance of the working fluid and several key system parameters, are investigated in this paper. According to the results, an increase in the mass fraction of organic in the CO2 mixture leads to an improvement in system energy efficiency and exergy density at the cost of lower system power efficiency. Increasing the high-pressure tank pressure enhances system performance except for system power efficiency. Increased low-pressure tank pressure leads to improved system energy efficiency and exergy density, accompanied by lower system power efficiency and exergy efficiency. When the ambient temperature increases from 298 K to 303 K, the system energy efficiency noticeably decreases, whereas an increase in direct normal irradiance improves various system performance indicators. Among several mixtures, CO2/R32 mixture was chosen for further analysis and optimization for its wider operating range with R32 mass fraction and better system performance. The optimal operating point had system energy efficiency, exergy density, and modified levelized cost of energy of 1.281, 22.216 kWh/m3, and 0.131 $/kWh, respectively. The proposed system in this research is proven to be a novel technical solution to meet the diverse energy demands on unique island environments.

Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach

In this paper, an equilibrium-heuristic online prediction optimization approach is proposed for multi-market peer-to-peer (P2P) electricity–hydrogen trading of integrated energy systems (IESs) with uncertainties. First, the IES, consisting of a hydrogen energy storage subsystem and a combined cooling, heating, and power subsystem, is constructed in the distribution network to improve energy utilization and market efficiency. Then, a bi-level optimization model for IESs, participating in the P2P electricity–hydrogen energy trading, the real-time electricity, and the ancillary service markets, is proposed, in which the top-level model can be formulated as a P2P electricity–hydrogen trading pricing model through the social welfare maximization problem, and the lower-level model is used to maximize the IES operating profit. To effectively solve the bi-level model, the game equilibrium-based ADMM distributed algorithm is used to obtain the P2P trading volume and prices of the top-level model, and a new hybrid heuristic algorithm, called hybrid sand cat swarm optimization and improved honey badger algorithm (SCIHB), is proposed to solve the lower level model. SCIHB utilizes a hybrid mechanism and an adaptive learning rate parameter to balance local exploitation and global exploration. Furthermore, a new online learning probabilistic prediction method based on the hidden Markov model and wavelet transform is introduced to describe the uncertainties of wind power, electricity prices, and frequency regulation prices. Finally, case studies are conducted on an IEEE 33-bus test system, and the numerical results verify the effectiveness of the proposed P2P trading model and solution approach.

Digital twin method and application practice of spacecraft system driven by mechanism data

Spacecrafts are large-scale systems characterized by various on-orbit configurations, multi-disciplinary coupling, and complex mission modes. Research and exploration on the data-driven spacecraft digital twins development methods must be carried out to satisfy various requirements such as spacecraft on-orbit condition monitoring and risk warning, fast flight conditions predictions, intelligent failure location, and virtual verification of failure. In this paper, significant progress is made in multiple key technologies, such as cyber-physical system modeling and simulation, hybrid modeling and model evolution through mechanism-data fusion, and interactive virtual-reality perception and mapping. The spacecraft digital twins’ model is constructed, and the spacecraft digital twin’s platform is designed and developed. Multiple digital twins’ application scenarios, such as on-orbit mission simulation and emulation, real-time interactive monitoring, and fast operating condition prediction, are supported. The research results are applied to the key on-orbit operation tasks, such as entering orbit, rendezvous and docking, position conversion, and astronaut exiting, enabling system-level digital operation for the sub-systems of spacecraft such as energy, power, control, and communication sub-systems.

Thermodynamic, economic, exergoeconomic analysis of an integrated ocean thermal energy conversion system

This paper proposes an integrated ocean thermal energy conversion (OTEC) system that couples power generation, refrigeration, and desalination. Based on the mathematical model, the thermodynamic, economic, and exergoeconomic performances are explored by evaluating several crucial parameters such as the ammonia-water concentration of the power subsystem (Xgen), the turbine inlet pressure (Pturb), etc. The results indicate that integrated OTEC system significantly improve the exergoeconomic performance since the efficient utilization of the exhausted cold seawater. The integrated system can achieve maximum net output power of 16.79 kW, refrigeration capacity of 268.87 kW, freshwater production of 53.22 t/d, as well as exergetic efficiency of 31.69% when the power subsystem's flow rate is 1.0 kg/s. Moreover, there is a maximum net output power when Pturb is under 800 kPa, and increasing Pturb leads to higher optimal Xgen. The maximum net output power, for instance, is 2.18 kW, 4.62 kW, and 9.79 kW when Pturb value is 600 kPa, 700 kPa, and 800 kPa, respectively, with corresponding optimal ammonia concentration values of 0.73, 0.83, 0.93. Furthermore, the maximum exergetic efficiency increases as Pturb enlarges. The maximum exergetic efficiency rises from 20.40% to 31.69% when Pturb increases from 600 kPa to 950 kPa. Besides, compared to the single OTEC plant's levelized cost of energy at 3.56 $/(kWh), the integrated system's can be as low as 0.098 $/(kWh).

Characterization of a NEG cartridge under high pressure conditions

The development of advanced sintered pumping elements based on the ZAO® alloy, characterized by a high affinity towards hydrogen and its isotopes, make Non Evaporable Getter (NEG) pumps particularly appealing for applications in fusion research, which typically deal with large fluxes of these gaseous species. NEG getters show high pumping speeds and capacity, excellent reliability with ability to withstand a high number of loading and unloading cycles without showing any type of failure, ease of integration within a complex system (such as a fusion reactor) because of their high specific properties and the simplicity of the mechanism that regulates its operation. These properties make NEG technology particularly suitable for the development of compact, efficient and easily scalable solutions, which are also very safe, since the release of absorbed hydrogen is prevented in the case of power outage or subsystem failures, as it can occur only by providing an adequate amount of heat to the getter material. This paper reports the results of an experimental campaign conducted on a new type of NEG pump, aimed to obtaining an accurate characterization in response to different operating conditions. Hydrogen pumping speed was investigated in a range of pressures of particular interest for the activities of the Divertor Tokamak Test facility (between 0.1 and 10 Pa). The influence of nitrogen absorption and getter material operating temperature on the pumping performances of the NEG pump were also examined. Finally, numerical simulations have been performed to estimate the nominal pumping speed of the NEG pump, that is, the one acting at the absorbing surface, stripped of the effects of the conductance of the paths from the pump NEG to the pressure gauges.

Design and development of a CanSat for air pollution monitoring with RSSI based position retrieval system

A CanSat is a miniature satellite system designed to be launched and operate in a manner similar to a satellite but on a much smaller scale. The term “CanSat” is derived from the combination of “Can” (referring to the soda can-sized container often used for the prototype) and “Satellite.” These small and cost-effective systems are typically used for educational purposes and scientific experiments. The main objective of this study is to present the design of CanSat, which is intended to track air pollution. The total weight of the CanSat includes the weight of the sensors, communication equipment, and other subsystems, which makes up the CanSat's total weight of 150 g. The data transmission rate can vary depending on the capabilities of the communication equipment used, but typically ranges between 1 and 10 transmissions per second. The Xbee communication protocol is commonly used for telemetry, typically at either 2.4 GHz or 900 MHz, but not both simultaneously. The major components of the CanSat are the power and sensor subsystems. The appropriate sensors are chosen by considering the main design elements, and typically include sensors to measure temperature, humidity and gases that can identify various pollutants to collect data on local air quality. CanSat is also equipped with a location retrieval system to ensure it can be recovered after launch. However, the type of system used can vary depending on the specific design. Power conservation techniques are employed to ensure that the CanSat can operate for as long as possible. Component selection is also carefully considered to make the CanSat more portable, affordable, and able to gather data on air pollution effectively.

Теоретико-методологічні аспекти становлення комунікативної системи публічного управління

The article establishes the need for the formation of a system of administrative communications to ensure the coordination of activities of subjects of state, municipal, public authorities, and mass media in the management of social processes. It has been proven that the formation of effective public communication, the communicative complex of the public power subsystem, is possible by reforming the public administration system. The theoretical and methodological principles of forming the administrative communications system were defined, and its structural and functional model was developed. Emphasis is placed on the theoretical description of the communicative process in modern scientific discourse, which uses various, and sometimes mutually exclusive, hypotheses, positions, and approaches; quite often, communication as a process is considered a relatively narrow sphere of human activity, and the application of the used models for local self-government seems problematic. Attention is paid to the fact that in the conditions of public administration reform in Ukraine, one of the urgent tasks is the modernization of the public communications system, bringing it closer to the standards of the EU and leading countries of the world, building an effective model of communication activities of state authorities. The subject and methods of communicative interaction of social subjects implementing communicative public policy are defined. The importance of communication in state administration and local self-government is also proven by its (communication) feature, which is a reliable and constant supplier of valuable information, which is then used in the management process. Public administration communications should be considered as a set of subsystems of informational and motivational interactions. It is noted that, in general, it is appropriate to define the communication system of public administration as mutually agreed complexes of communicative horizontal and vertical, internal and external, formal and informal interactions of subjects of public space (bodies, organizations, institutions, and representatives of state, self-governing, public, media authorities and citizens ) at the central, regional and local levels, thanks to which the coordination of the activities of the subjects regarding the management of social processes is achieved. Keywords: communicative interaction, communicative strategy, public administration bodies, state administration, mass communication media, civil society institutions, communicative system of public administration, local self-government.

Preliminary evaluation of NEG materials in view of CMSB replacement in HCPB TER architecture

CMSB (Cryogenic Molecular Sieve Beds) operated at 77 K is used for tritium recovery in the reference design of HCPB (Helium Cooled Pebble Bed) TER (Tritium Extraction and Removal) system. However, this technology has two main drawbacks: large consumption of liquid nitrogen and the controlling of tritium stream sent to the Tritium Plant, during the regeneration of the CMSB, in such way to avoid large variations in the gas flow rate.This paper reports on a preliminary evaluation for CMSB replacement by non-evaporable getter materials for tritium recovery. The advantages of NEG technology are the high specific pumping speed and capacity and the ability to withstand a large number of absorption/desorption cycles. In addition, NEG do not release hydrogen unless power is supplied to heat them, addressing an important safety issue related to uncontrolled release in case of power outage or subsystem failures.

Eco-Energy Sensor Networks

This project perpetual environmentally powered sensor networks aims to develop a system for harvesting energy from the renewable environmental energy source using the embedded systems technology. Utilizing environmental energy sources holds great appeal as a power supply for low- power wireless sensor networks.This has become a major problem now a days as the proposed system involves human intervention. This project is aiming to pinpoint the best hardware selections that align with the requirements of a particular application. The primary goal is to optimize the hardware to precisely cater to the needs and demands of the given application. The primary design obstacle involves minimizing stress on storage components while maintaining a straightforward hardware and software structure. This design is a smart system that integrates streamlined, efficient hardware with robust software. This system will actively oversee the power subsystem to ensure continuous operation

Hybrid continuous-discrete time control strategy to optimize thermal network dynamic storage and heat-electricity integrated energy system dynamic operation

The heat-electricity integrated energy system (HE-IES) presents a promising opportunity for increasing renewable energy generation by fully utilizing the dynamic heat storage capabilities of the thermal network (TN). However, the dynamic characteristics of the TN and the response characteristics of devices in the HE-IES present challenges to system operation and control. To address these challenges, this study proposes a novel multi-layer control strategy that divides the system based on the component response status. The first layer aims to minimize the operating costs of the HE-IES, disregarding any dynamic effects. The second layer optimizes the dynamic operation of thermal subsystems by employing a TN’s Taylor expansion model and continuous-time generalized predictive control. The third layer focuses on optimizing the power subsystem to enhance the share of renewable energy generation, using discrete-time model predictive control. To the best of our knowledge, this is the first study that utilizes continuous time models to control the dynamic operation of TNs and their thermal subsystems. Through case analysis, the proposed model achieves a 34.5% reduction in operating costs compared to a single-layer control strategy and a 2.7% reduction compared to a discrete-time multi-layer control strategy. These findings highlight the favorable economic performance of the proposed model. Additionally, the utilization of continuous-time model allows for effective capturing dynamic performance of the TN and enhances its role in system operation.

Efficiency improvement strategy of fuel cell system based on oxygen excess ratio and cathode pressure two-dimensional optimization

Improving the commercial fuel cell system efficiency is critical to reducing hydrogen consumption and improving the operational economy. This paper studies the power consumption pattern of the air supply subsystem, the most power-consuming auxiliary components, aiming to improve the system’s efficiency. A method was proposed to get the extremum of the system net power by optimizing the oxygen excess ratio and cathode pressure. Mathematical models describing the fuel cell stack and air supply subsystem power characteristics were developed based on the mechanism analysis and estimation of unknown parameters. Then, a system net power model for energy efficiency optimization was developed. The operating conditions for optimal efficiency at a specific current density can be obtained by numerical calculation. To verify the method’s effectiveness, a series of experiments were conducted, and the results show that the proposed method can maximize system net power output at various current density conditions. Compared with the conventional oxygen excess rate based one-dimensional optimization, the two-dimensional method can improve system efficiency by 2.06%, offering a good application prospect.

Application of Covariance Matrix Adaptation‐Evolutionary Strategy for Modified Constrained Optimal Power Flow Problem Incorporating Valve Point and Emission Effect

A prevailing problem in power and energy subsystems is the smooth operation of electric energy systems. This work presents recent, efficient, and reliable evolutionary algorithm for solving the optimal power flow (OPF) analysis. All various practical complex equality and inequality constraints, namely, bus voltages, real powers of the generator buses, tap settings of the transformers and the reactive power generations, shunt compensation, and emission, are considered for the real‐world scenario. Primary feature in a gas power plant that raises a lot of computational shortcomings with nonlinear structure in fuel cost is valve point effect. The existing research works have not factored the valve point effect and lack the accuracy in the fuel cost minimization and do not reflect the various practical complexities such as valve point and emission effects in the OPF problem formulation. This paper, for the first time, introduces modified OPF problem formulation incorporating valve point effect and applies covariance matrix adaptation‐evolution strategy (CMA‐ES) for solving the modified OPF problem. The algorithm is scrutinised and tested on a modified IEEE‐30‐bus platform for various OPF objectives such as cost minimization, transmission loss, and total voltage deviation, subjected to practical constraints. Load flow analysis has been carried out using the Newton–Raphson method. This work aims to lay the foundation in such a way that it can be applicable in a real‐world scenario for any number of buses.

Comprehensive assessment and sustainability improvement of a natural gas power plant utilizing an environmentally friendly combined cooling heating and power-desalination arrangement

Considering the significant waste heat generated by existing natural gas power plants, it is imperative to implement eco-friendly combined process designs to ensure their long-term sustainability. The present paper introduces and investigates a novel integrated process aimed at achieving multiple generational advantages within an environmentally friendly framework, with the ultimate goal of enhancing sustainability. The new structure incorporates a natural gas power plant, high-temperature and low-temperature organic Rankine cycles, a combined cooling and power subsystem, and a water desalination unit to produce power, heating, cooling, and freshwater simultaneously. This system is simulated within the Aspen HYSYS software and examined from energy, exergy, economic, environmental, and sustainability perspectives. Furthermore, parametric studies evaluate the impact of the overall system's various environmental, economic, and operational conditions. It is found that the production capacities of power, hot water, chilled water, and freshwater are 179,265.17 kW, 387.8 kg/s, 563.6 kg/s, and 21.4 kg/s, respectively. Hence, the overall energy and exergy efficiencies improve to 66.06% and 42.95%, respectively. The financial estimation also reveals a cost of energy of 0.1084 $/kWh and a total net present value of 818.67 M$. It is also determined that the cost per unit of destroyed exergy is equal to 7.156 $/GJ.

Organisation of the Structure and Functioning of Self-Sufficient Distributed Power Generation

During the operation of solar and wind power plants, it is necessary to solve issues related to the guaranteed capacity of these plants, as well as the frequency stabilisation in the power system where they operate, and maintain an operating mode of self-sufficiency conditions. One of the solutions to these problems is the use of energy storage systems. This article proposes a mathematical model for the study of frequency and power regulation processes in power systems with distributed generation, which includes renewable energy resources and energy storage systems. The novelty of the model lies in the possibility of determining energy cost indicators based on instantaneous energy power data. The model allows us to estimate the conditions under which distributed generation becomes self-sufficient. The results of the model calculations of two variants of power system operation, which includes wind generators with a capacity of 1500 MW, demonstrate the ability of the proposed model to accurately reproduce the dynamics of the frequency stabilisation process. The calculation results of the energy-economic indicators of a real power system combined with a powerful subsystem of wind generation and a battery-type energy storage system prove the competitiveness of self-sufficient renewable energy power plants.

Spacecraft fault detection and identification techniques using artificial intelligence

The complexity of spacecraft systems and their missions is increasing, requiring higher levels of performance and innovative solutions. It is essential to have onboard autonomy with minimal faults to ensure reliability, availability, and safety. Fault Detection and Identification (FDI) is critical in identifying spacecraft faults before they cause major failures. However, FDI design and application are challenging due to the space environment and the reliance on system information. To improve accuracy, speed, and noise robustness, modern FDI methods based on Artificial Intelligence (AI) techniques have been developed. This paper investigates the latest FDI techniques in the spacecraft attitude determination and control subsystem (ADCS) and electrical power subsystem (EPS). The article discusses various FDI methodologies and frameworks, highlighting their advantages, drawbacks, and the significance of AI implementation. Additionally, the paper presents a thorough analysis and comparison of the different methods.