Total System Losses Research Articles

Comparative analysis of FACT devices for optimal improvement of power quality in unbalanced distribution systems

This study examines the performance of asymmetric three-phase distribution systems under the influence of FACT deives such as a static VAR compensator (SVC) and a unified power controller (UPC). Each suggested device’s operating principle is developed in this paper in order to provide the best model to be used in the power flow analysis. The performance of the IEEE-13 bus imbalanced distribution model is investigated using the Newton-Raphson method. To improve network asymmetry, an optimization analysis is carried out to ascertain how each proposed device will work. In this paper, the mode of operation of each device is determined every hour to flow the changing in loads according to their daily load curve. The genetic algorithm (GA) is utilized to determine the contribution of the unified flow controller to balance the loads between phases. The multi-objective function is constructed to combine the total system losses and the average voltage unbalance coefficient. The paper provides an optimal dynamic technique to optimally operate the unified power flow controller installed in the unbalanced three-phase distribution system.

Analysis of Transient Stability through a Novel Algorithm with Optimization under Contingency Conditions

Predicting the need for modeling and solutions is one of the largest difficulties in the electricity system. The static-constrained solution, which is not always powerful, is provided by the Gradient Method Power Flow (GMPF). Another benefit of using both dynamic and transient restrictions is that GMPF will increase transient stability against faults. The system is observed under contingency situations using the Dynamic Stability for Constrained Gradient Method Power Flow (DSCGMPF). The population optimization technique is the foundation of a recent algorithm called Training Learning Based Optimization (TLBO). The TLBO-based approach for obtaining DSCGMPF is implemented in this work. The total system losses and the cost of the individual generators have been optimized. Analysis of the stability limits under contingency conditions has been conducted as well. To illustrate the suggested approaches, a Standard 3 machine 5-bus system is simulated using the MATLAB 2022B platform.

Techno-economic, energy, and exergy analyses of invasive weed gasification for hydrogen enriched producer gas production

This research work deals with the examination of the techno-economic, exergy, and energy analyses of biomass gasification of the invasive weed Parthenium hysterophorus (PHP) using Steam - Carbon dioxide (CO2) as a gasifying agent with the support of simulation modeling for sustainable energy conversion process. The aim of this work is to simulate the gasification process through consideration of the impacts of various operating factors on gasification. This study attains the gradual increase in hydrogen (H2) concentration from 51% to 63% along with the rise in carbon monoxide (CO) from 14.5% to 19% using Aspen Plus simulation. CO2 falls concurrently from 24% to 13.5%. The findings demonstrate significant advancements over earlier studies in terms of both gas composition and overall system performance. A computational model has been developed for the estimation of energy performance indicators such as total energy input, and energy consumed per mass of biomass gasified, which are used in the determination of the system's energy efficiency. The exergy analysis of the system is performed to assess the system's total losses in terms of efficiency gathered from the system's exergy ratios. The economic analysis evaluates the system's economies of scale by gas production at ₹.15/kg and long-term sustainability. The proposed system has been found with the potential to produce a high yield of alternative energy from PHP with increased economic efficiency and lower environmental impact.

Optimal Power Quality Enhancement using a Radial Distribution System with an Improved Unified Power Quality Conditioner

Massive electric power distribution over long distances with consequential Power Quality (PQ) challenges such as voltage sags and power losses are some of the significant attributes of a Radial Distribution Network (RDN). Deployment of Power Angle Regulated (PAR) based Unified Power Quality Conditioner (UPQC) in a distribution network is also securing attraction because of the latest recorded achievements and improvements in Voltage Source Inverter (VSI) built power electronic systems. However, optimal allocation of this kind of device to mitigate PQ problems remains a challenge for achieving set objectives. Consequently, this study considers the best possible allocation of PAR and Improved-UPQC know as I-UPQC in the distribution network to enhance power network performance. The identification of optimal location is achieved through the application of hybridization of the Genetic Algorithm and Improved Particle Swarm Optimization (GA & IPSO). The deterministic approach is based on the weight factor of various objective functions. The allocation is attained with a selection of reactive power control between inverter connected in parallel and series and control angle variables of the device through its dynamic involvement of total system loss derivatives. Performances of the I-UPQC based distribution system during diverse power transfers are observed. Convergence characteristic of deterministic approach at different disturbance percentages is analyzed and presented. Imaginary power circulation enhanced the voltage-associated challenges at the range of 0.949 to 0.9977. Hence, power dissipation minimized to 1.15 percent compared to the initial 3.35 percent, according to results of I-UPQC allocation in RDN utilizing mathematical and optimization technique. Additionally, the network losses, voltage dip, and minimum bus voltage profile all fall within the regulatory standards of less than 2%, 5%, and 5%, correspondingly. Also, the performance of the compensated network for both ordinary and optimized scenarios indicated the fitness of the projected method in accomplishing an operational optimization of RDN, specifically for voltage profile (VP) improvement and I-UPQC's series and shunt inverter share imaginary power.

Analysis of Power System Transient Stability of the Nigerian 330-kV Electricity Grid

Faults on power system are inevitable and can occur at any time resulting into transient instability. Transient instability can cause loss of synchronism and possible damage to power equipment and consumer loads. Therefore, this study analyzed the transient stability (TS) of the Nigerian 330-kV, 34-bus power network. Power flow and swing equations describing the system steady and transient states were respectively analyzed using Newton-Rahpson and Runge-Kutta, fourth order numerical techniques to provide linear solution due to their non-linearity. Simulations were done and swing curves for different fault conditions obtained. The critical clearing time at which the simulated faults were cleared was determined. The results of load flow analyses revealed that buses 6, 10, 13, 14, and 17 with respective voltage magnitude of 0.937, 0.921, 0.938, 0.829 and 0.780 per unit violated voltage tolerance limit of 0.95 to 1.05 p.u. The system total active and reactive power losses were 57.62 MW and -70.62 MVar respectively. The obtained swing curve showed that for fault on bus 11 [line 9-11] generators 2, 3 and 7 lost synchronism after 1.0 s but other generators retained their stability. Similarly, for fault on bus 13 [line 10-14] generators 3 and 7 lost synchronism but other generators retained stability after 0.4 s. These results indicate that faults occurrence on generating stations of power system is unavoidable, but the clearance time must be short (few seconds) to avert total system collapse and loss of synchronism.

Heat loss optimization and economic evaluation of a new fourth generation district heating triple pipe system

In response to the heat loss caused by the temperature difference between the heating pipes and external environment during the pipe transportation, heat contradiction between the total heat loss of the piping system and heat transfer between tubes, as well as economic balance between the cost of heat loss and cost of material loss. Based on TOTS (Two-supply/One-return, triple pipe structure) heat loss theory of the fourth-generation district heating system, this paper optimizes structure of pipes by setting dimensionless characteristic parameters θ and β. Finally, a mathematical model is proposed to calculate economic efficiency of pipeline network by considering the cost of initial construction material loss and operation heat loss of the pipe. Results show that, from energy perspective, comprehensive heat as system energy consumption evaluation index is positively correlated with θ, decreases first and then increases as β increases. Total heat loss of system dominates comprehensive heat. Lowest comprehensive heat of system is 18.12 w/m for θ of 0.1945 and β of 0.0739. From economic perspective, total system loss cost as system economic evaluation index is positively correlated with both θ and β. Total system heat loss cost dominates total system loss cost. Lowest total system loss cost is $29.39/m for θ of 0.1945 and β of 0.0509.

Voltage profile improvement and power loss minimization of new haven injection substation for optimal placement of DG using harmony search algorithm optimization technique

The main importance of a power grid is to transfer electrical energy from the production to the consumption, while maintaining an acceptable reliability and voltage quality for all customers. The role of electrical power distributions to have centralized plants distributing electricity through Distributed Generation (DG) which reduces the Power Loss on transmission and distribution station and also improve voltage profile by optimization. This research work analyzes New Haven injection substation for optimal placement of DG generation based on wind power renewable energy source to the Distribution network and voltage stability using Harmony Search Algorithm. The model developed was simulated using MATLAB/SIMULINK software. The work applied new improved Harmony Search Algorithm for integration of renewable energy generation in the distribution network with positive impact on the operation of the voltage stability between 0.95 to 1.05p.u and reactive power distribution improvement through minimization of line losses. The total power system Loss without and with DG are 338.712KW and 307.9KW. Also, the voltage profiles of the sixteen faulty buses are stabilized for efficient performance of substation. Hence, the percentage of power system improvement is 27.23%. Therefore from the results, there is reduction of power Loss when DG is applied and optimised in the power system.

End-to-End Direct-Current-Based Extreme Fast Electric Vehicle Charging Infrastructure Using Lithium-Ion Battery Storage

An urgent need to decarbonize the surface transport sector has led to a surge in the electrification of passenger and heavy-duty fleet vehicles. The lack of widespread public charging infrastructure hinders this electric vehicle (EV) transition. Extreme fast charging along interstates and highway corridors is a potential solution. However, the legacy power grid based on alternating current (AC) beckons for costly upgrades that will be necessary to sustain sporadic fast charging loads. The primary goal of this paper is to propose a sustainable, low-loss, extremely fast charging infrastructure based on photovoltaics (PV) and co-located lithium-ion battery storage (BESS). Lithium-ion BESS plays a pivotal role in our proposed design by mitigating demand charges and operating as an independent 16–18 h power source. An end-to-end direct current power network with high voltage direct current interconnection is also incorporated. The design methodology focuses on comprehensive hourly EV-load models generated for different types of passenger vehicles and heavy-duty fleet charging. Appropriate PV-BESS sizing, optimum tilt, and temperature compensation techniques based on 15 years of irradiation data were utilized in the design. The proposed grid-independent DC power networks can significantly improve well-to-wheels efficiency by minimizing total system losses for fast charging networks. The network power savings for low, medium, and high voltage use cases were evaluated. Our results demonstrate 17% to 25% power savings compared to the traditional AC case.

Optimal allocation of a wind turbine and battery energy storage systems in distribution networks based on the modified BES-optimizer

Recently, incorporating renewable energy resources (RERs) like wind turbines (WTs) in a distribution network is rapidly increased to meet the load growth. However, distribution networks have been facing many challenges to withstand the intermittent output power of RERs. Battery energy storage (BES) is used with RERs to smoothly inject the output power to the grid by RERs. Therefore, this paper proposes an effective strategy for optimal allocation of WT and BES in RDS to decrease the total system losses. In addition, a modified bald eagle search (BES-optimizer) is proposed to obtain the preferable allocations of WT and BES simultaneously in the radial distribution system (RDS) considering the probabilistic distribution of the WT and load demand. IEEE 69-bus RDS is utilized as a test system. Based on the obtained results, installing WTs with BES gives better results than installing WTs alone in the RDS. However, the proposed algorithm proved its efficiency to obtain the best global results compared with other well-known techniques.

DEVELOPMENT OF ANN CONTROLLED UPFC BASED PROTECTION MODEL FOR NIGERIAN 330KV POWER LINES

This paper, proposed the use of artificial neural network (ANN) based UPFC for transmission network loss minimization. The overall effect of power losses on the system is a reduction in the quantity of power available to the consumers. Power loss leads to high cost of power generation, transmission and distribution. Unlike exiting up change and regulating transformer techniques for loss reduction, FACTS devices have fast switching capability and can be subjected to very free control algorithms for more optimal performance in loss reduction application in power systems. The neural network was modeled to output the firing angle to enable the FACTS device effectively control the adsorption and injection of reactive power for transmission loss reduction. The Nigerian 330KV power grid was used as a case study for the evaluation of the proposed power loss reduction system A digital model of the case study power system with the proposed neural network controlled UPFC integrated was created in the MATLAB/SIMULINK programming environment. Genetic algorithm was used for the optimal placement of the FACTS device in the MATLAB/SIMULINK model of the Nigerian 330KV transmission system. Simulation carried out involved alteration of power flow in order to cause different levels and distribution of losses in the network. With each variation, load flows was carried out to evaluate the distribution of losses and the active and reactive loss reduction achieved by the proposed system. The simulation and evaluation were carried out under two scenarios: (i) with the UPFC installed and (ii) without the UPFC installed. With each variation of the load at the bus, load flow is run to determine total system loss either with the UPFC installed or without the UPFC installed. Results obtained showed that the proposed system achieved an average active power loss reduction of 12.8416% and an average reactive power loss reduction of 21.82%.

Energy Management Strategy for Optimal Sizing and Siting of PVDG-BES Systems under Fixed and Intermittent Load Consumption Profile

Advances in PV technology have given rise to the increasing integration of PV-based distributed generation (PVDG) systems into distribution systems to mitigate the dependence on one power source and alleviate the global warming caused by traditional power plants. However, high power output coming from intermittent PVDG can create reverse power flow, which can cause an increase in system power losses and a distortion in the voltage profile. Therefore, the appropriate placement and sizing of a PVDG coupled with an energy storage system (ESS) to stock power during off-peak hours and to inject it during peak hours are necessary. Within this context, a new methodology based on an optimal power flow management strategy for the optimal allocation and sizing of PVDG systems coupled with battery energy storage (PVDG-BES) systems is proposed in this paper. To do this, this problem is formulated as an optimization problem where total real power losses are considered as the objective function. Thereafter, a new optimization technique combining a genetic algorithm with various chaotic maps is used to find the optimal PVDG-BES placement and size. To test the robustness and applicability of the proposed methodology, various benchmark functions and the IEEE 14-bus distribution network under fixed and intermittent load profiles are used. The simulation results prove that obtaining the optimal size and placement of the PVDG-BES system based on an optimal energy management strategy (EMS) presents better performance in terms of power losses reduction and voltage profile amelioration. In fact, the total system losses are reduced by 20.14% when EMS is applied compared with the case before integrating PVDG-BES.

In Vitro Evaluation of Nebulized Pharmaceutical Aerosol Delivery to the Lungs Using a New Heated Dryer System (HDS).

The objective of this study was to develop a new heated dryer system (HDS) for high efficiency lung delivery of nebulized aerosol and demonstrate performance with realistic in vitro testing for trans-nasal aerosol administration simultaneously with high-flow nasal cannula (HFNC) therapy and separately for direct oral inhalation (OI) of the aerosol. With the HDS-HFNC and HDS-OI platforms, new active synchronization control routines were developed to sense subject inhalation and coordinate drug aerosol delivery. In vitro experiments were conducted to predict regional drug loss and lung delivery efficiency in systems that included the HDS with various patient interfaces, realistic airway models, and simulated breathing waveforms. For the HDS-HFNC platform and a repeating breathing waveform, total system loss was < 10%, extrathoracic deposition was approximately 6%, and best-case lung delivery efficiency was 75-78% of nebulized dose. Inclusion of randomized breathing with the HFNC system decreased lung delivery efficiency by ~ 10% and had no impact on nasal depositional loss. For the HDS-OI platform and best-case mouthpiece, total system loss was < 8%, extrathoracic deposition was < 1%, and lung delivery efficiency was > 90% of nebulized dose. Normal vs. deep randomized oral inhalation had little impact on performance of the HDS-OI platform and environmental aerosol loss was negligible. In conclusion, both platforms demonstrated the potential for high efficiency lung delivery of the aerosol with the HDS-OI platform having the added advantages of nearly eliminating extrathoracic deposition, being insensitive to breathing waveform, and preventing environmental aerosol loss.

Optimal Locations and Sizes of Shunt FACT Devices for Enhancing Power System Loadability Using Improved Moth Flame Optimization

In this article, the optimal allocation of compensation devices in power systems is determined using Improved Moth-flame Optimization (IMFO) algorithm. The main objective of this study is to maximize power system loadability, reduce total power system losses and enhance the voltage profile through finding the optimal locations and sizes of Static VAR Compensator (SVC) and Thyristor Controlled Compensator (TCSC). The methodology of this article is based on Continuation Power Flow (CPF) which is merged with IMFO in Optimum Power Flow (OPF) problem restricted by equality and inequality constraints. The proposed algorithm is implemented to regulate the required control variables. Both of single and multi-objective functions are applied on 57-IEEE bus test system to prove the performance of the proposed algorithm. The acquired simulation results by IMFO are compared with Moth Flame Optimization technique (MFO) and Multi Verse Optimizer (MVO) to emphasize the robustness of the proposed algorithm.

Fund portfolio networks: A climate risk perspective

Within Europe, investment funds are more exposed to climate-sensitive economic sectors than banks, insurers, and pension funds. However, few climate-related financial risk assessments of the fund sector have been conducted. We use 8 trillion EUR of fund portfolio holdings to help fill this gap, using the network of portfolio overlaps. Funds with more polluting portfolios (brown funds) invest across more firms than funds with cleaner portfolios (green funds). This apparent diversification hides a concentration risk: brown funds are more closely connected with each other (have more similar portfolios) than green funds, which tend to herd less (have less similar portfolios with each other). This suggests that, in the event of a widespread climate-related financial shock, brown funds will face greater stress levels than green funds. A climate risk scenario exercise confirms this: among total system losses of 443 billion EUR, brown funds' losses are typically between two and three times higher than green funds' losses. Brown funds also have more systemic impact: because they play a more central role in the investment fund network, brown funds contribute twice as much towards system-wide losses as green funds. These findings suggest that, despite the growing attention paid to sustainable investing, systemic vulnerabilities remain and many funds' portfolio diversification approaches do not yet adequately incorporate climate risk.

Comparative Life Cycle Assessment of Different Cooling Systems for High-Temperature Superconducting Power Cables

This study conducts a comparative life cycle assessment of two different types of cooling systems for a 1 km long, 10 kV concentric three-phase high-temperature superconducting cable. In an open cooling system, the required cooling energy is provided by evaporating liquid nitrogen in a subcooler resulting in a constant loss of liquid nitrogen. As a consequence, liquid nitrogen must constantly be reproduced and transported to the cooling unit. Alternatively, a closed cooling system can be used in which liquid nitrogen is electrically re-cooled using a cryocooler. This results in a higher on-site electricity consumption but simultaneously removes any liquid nitrogen losses. It is shown that the use of a closed cooling system does not only reduce the total system losses but also improves the environmental performance by 4–24% depending on the examined environmental impact category. If the cryocooler is powered by renewable energies only, the environmental savings can be increased even further.

Demand-side management and its impact on utility and consumers through a game theoretic approach

The modern smart grid facilitate improved demand flexibility, but the self-optimizing nature of participating users will impact the effectiveness and stability of the demand-side management (DSM) program. In this article, the DSM is modeled as a non-cooperative game between users. To ensure the effectiveness and stability of the solution, the existence of Nash equilibrium (NE), its quality and multiplicity are thoroughly investigated for the system model consisting home appliances, distributed energy storage (DES) and dispatchable generation (DPG). The payoff function of the formulated game is not strictly convex due to addition of DES and DPG. Therefore, the proximal decomposition algorithm (PDA) is utilized to get the NE of the game. The convergence of PDA has a strong dependency on system parameters. A rigorous mathematical proof is provided for the condition of convergence of the PDA. The formulated DSM model has been utilized for analyzing its impact on the users as well as distribution utility. In the case of former, its impact on the user’s energy bill, profile of DES and DPG, comfort and privacy concern are investigated. In latter case, its impact on system performance parameters such as system peak-to-average ratio (PAR), bus voltage, total system loss, bus voltage deviation index, voltage stability indices, and system reliability parameters are studied. The IEEE-33 bus distribution system is considered for the assessment of the proposed study. The obtained result shows a significant reduction in the energy bill and PAR and improved system performance parameters.

A Comparison of Metaheuristic Techniques for Solving Optimal Sitting and Sizing Problems of Capacitor Banks to Reduce the Power Loss in Radial Distribution System

The losses in the radial distribution system are inevitable which needs to be minimized for the proper transmission of power to the end customers. This problem can be solved by the allocation of capacitor banks at proper locations with appropriate sizing. These allocations need an efficient approach for the performance enhancement of RDS. In this paper, several metaheuristic techniques such as particle swarm optimization (PSO), Harmony search, Bat, Cuckoo, and Grey‐wolf (GW) algorithms are employed to find the size of capacitor banks. Loss sensitivity analysis is considered for the indication of candidate buses where a capacitor has to be installed to reduce the total system losses and ultimately increase efficiency. Cost‐effectiveness, power loss minimization, and voltage enhancement can be determined and compared for these 5 techniques and are implemented on the IEEE‐34 bus system to illustrate the efficacy of each of them. The results show the advantages and drawbacks of the techniques separately. The simulations are carried out in MATLAB.

Multi-Objective Immune-Commensal-Evolutionary Programming for Total Production Cost and Total System Loss Minimization via Integrated Economic Dispatch and Distributed Generation Installation

Economic Dispatch (ED) problems have been solved using single-objective optimization for so long, as Grid System Operators (GSOs) previously only focused on minimizing the total production cost. In modern power systems, GSOs require not only optimizing the total production cost but also, at the same time, optimizing other important objectives, such as the total emissions of the greenhouse gasses, total system loss and voltage stability. This requires a suitable multi-objective optimization approach in ensuring the ED solution produced is satisfying all the objectives. This paper presents a new multi-objective optimization technique termed Multi-Objective Immune-Commensal-Evolutionary Programming (MOICEP) for minimizing the total production cost and total system loss via integrated Economic Dispatch and Distributed Generation installation (ED-DG). This involved the application of a weighted-sum multi-objective approach that combined with an optimization technique called Immune-Commensal-Evolutionary Programming (ICEP). The proposed MOICEP has been compared with other multi-objective techniques, which are Multi-Objective-Evolutionary Programming (MOEP) and Multi-Objective-Artificial Immune System (MOAIS). It was found that MOICEP performs very well in producing better optimization results for all the three types of Economic Dispatch (ED) problems compared to MOEP and MOAIS in terms of cheap total production costs and low total system loss.

Optimal Design of Barangay Rogongon Microgrid System

In this research, specifically an electrical distribution system design of the proposed microgrid in a remote barangay, Brgy. Rogongon, in Iligan City, is presented. Due to limited access and limited-service electrical utility grid, about 10 % of the Philippine household population at a development disadvantage. Through the project, potential sites for hydropower and solar PV installations as well as distribution pathways were identified using Geographic Information (GIS). Household surveys were conducted to obtain the 5 yr projected load demand and the results are presented in thematic maps. The electrical distribution system of the microgrid was designed and simulated using Just Another Electrical Distribution Network Software (JAED.NS). The system simulation showed an acceptable 5.94 % estimated total system loss which implies that the designed electrical distribution system is feasible.

Optimal Battery Energy Storage System Based on VAR Control Strategies Using Particle Swarm Optimization for Power Distribution System

We designed a battery energy storage system (BESS) based on the symmetrical concept where the required control is by the symmetrical technique known as volt/var control. The integration of BESS into the conventional distribution has significantly impacted energy consumption over the past year. Load demand probability was used to investigate optimal sizing and location of BESS in an electrical power system. The open electric power distribution system simulator (OpenDSS) was interfaced with MATLAB m-file scripts and presented by using time series analysis with load demand. The optimal BESS solution was adapted by using a genetic algorithm (GA) optimization technique and particle swarm optimization (PSO). The simulation results showed that the BESS was directly connected to the power grid with GA and PSO, and it was observed that BESS sizing also varied for these two values of 1539 kW and 1000 kW, respectively. The merit of those values is the power figure of the system, which is necessary for installation. Therefore, optimal sizing and location of the BESS are helpful to reduce the impact from the load demand to the total system loss and levelling of the energy demand from the power system network. The integration of the BESS can be applied to improve grid stability and store surplus energy very well. The grid increased the stability of the power system and reduced the impact from the large scale of BESS penetration.