Central Power Plants Research Articles

Multi-objective Harris Hawks optimization algorithm for selecting best location and size of distributed generation in radial distribution system

Distributed Generating Units (DGUs) are widely used in backup power, renewable energy integration, voltage regulation, and energy storage applications. The DGUs are small-scale power-generating units located near the load centers of a power system, as opposed to large, centralized power plants located far away. However, the DGUs must reduce power losses and environmental impacts and improve the voltage profile. This was achieved by effective optimization of the position and rating of DGU. However, the conventional optimization methods failed to optimize the power losses, voltage-current balancing issues, and harmonic distortions. So, this article presents the selection of the best location and size of DGU in radial distribution systems using a nature-inspired multi-objective Harris Hawks optimization (HHO) algorithm while considering improvements in the voltage profile and reductions in active power losses. The HHO algorithm is inspired by the supportive actions of intelligent birds, such as Harris Hawks, while searching for prey. The distinguished hunting process of Harris Hawks using other family members makes it unique, which is useful for searching for better quality solutions while optimizing multi-objective fitness functions. Fitness function is determined by considering each bus's voltage profile and branches' active power losses. The proposed method is tested on two circle distribution systems (69 bus and 118 bus). The results are compared to those obtained using some of the more well-known optimization techniques given by scholars in recent years. The optimization of seven DGU in 118 bus radial distribution systems resulted in 405.32 kW of active power losses, a 68.78% decrease in losses, and 0.9723 Vs of minimum voltage.

Efficient reduction of power losses by allocating various DG types using the ZOA algorithm

The continuous challenge of ensuring energy supply is a significant concern. Traditionally, utilities have addressed increasing load demands by building new central power plants or expanding existing ones. However, these methods are time-consuming and costly, providing only short-term solutions. Additionally, power plants are often far from load centers, resulting in higher power losses during long-distance transmission. The integration of distributed generation (DG), characterized by smaller scale and lower capital costs, with nearby consumers can effectively address these challenges. Due to the significant influence of DG penetration and their specific locations on the distribution system's performance, this study offers a novel Zebra Optimization Algorithm (ZOA). The suggested ZOA is used to optimize the capacity and position of various DG units connected to a radial distribution system to reduce power losses and study the stability of the system after DG allocation using the Voltage Stability Index (VSI). The evaluation is conducted using the IEEE 33-bus test system, considering various scenarios including single and multiple DGs of different types. The results demonstrate that in the best scenario, the ZOA can reduce losses by up to 94.25 % and improve the VSI from 0.69643 to 0.9605. These findings highlight the superior performance of the ZOA over other techniques in optimizing DG placement and sizing for power system performance.

Enhancing the AC network stability with a grid-forming control for single-stage PV inverter

This article proposes a PLL-less grid-forming (GFor) control for a PV central power plant topology designed to maintain the DC voltage and improve the AC voltage stability. The PV single-stage or central topology stands as the most widely adopted power plant structure. However, no GFor control capable of regulating the DC bus has yet been proposed for this layout. This work presents a PLL-less GFor control that can effectively control the DC voltage for a single-stage PV inverter, whether it operates at the Maximum Power Point (MPP) or with reserve. Moreover, this control can incorporate Maximum Power Point Tracking (MPPT) controls typically employed in grid-following structures. The primary advantage of this GFor control is the voltage support and stability it provides and the capability of working with a low Short Circuit Ratio (SCR). The performance and viability of the proposed control was analysed with several simulations of various faults (symmetrical and asymmetrical), frequency (large phase jump and frequency excursion with high ROCOF) and resource events (irradiation changes and DC voltage reference tracking analysis). The results demonstrate that the proposed GFor control presented not only meets the grid-code requirements but also exhibits the behaviour expected during the different analysed events.

A peer‐to‐peer joint energy and reserve market considering renewable generation uncertainty: A generalized Nash equilibrium approach

AbstractPeer‐to‐peer (P2P) energy trading enhances distribution network resilience by reducing energy demand from central power plants and enabling distributed energy resources to support critical loads after extreme events. However, adequate reserves from main grids are still required to ensure real‐time energy balance in distribution networks due to the uncertainty in renewable generation. This paper introduces a novel two‐stage joint energy and reserve market for prosumers, wherein local flexible resources are fully utilized to manage renewable generation uncertainty. In contrast to cooperative optimization methods, the interactions between prosumers are modelled as a generalized Nash game (GNG), considering that prosumers are self‐interested and should follow distribution network constraints. Then, linear decision rules are employed to ensure a feasible market equilibrium and develop a privacy‐preserving algorithm to guide prosumers toward the market equilibrium with a proven convergence. Finally, the numerical study on a modified IEEE 33‐power system demonstrates that the designed market effectively manages renewable generation uncertainty, and that the algorithm converges to the market equilibrium.

Design Basis Document / Owner’s Technical Specification for Nitrate Salt Systems in CSP Projects

Work has begun on a Design Basis Document / Owner’s Technical Specification for parabolic trough and central receiver power plants using nitrate salt as the heat transport fluid and the thermal storage medium. A principal topic of recent interest is the failures of the hot salt tanks in central receiver projects. The paper outlines a hypothesis for the source of the failures, and discusses a range of possible solutions.

Pengolahan Citra Untuk Mengetahui Derajat Korosi Pada Insulator Dengan Metode Decision Tree

One of the important parts that ensures the availability of electrical energy supplies which takes place from the central power plant and then through the transmission line to distribution to the load is the insulator. However, over time, insulators can experience anomalies such as corrosion. Insulator corrosion can be caused by many environmental factors, including pollution, humidity, high temperatures and exposure to chemicals. Previously, maintenance personnel usually identified the level of corrosion on insulators visually by using their knowledge and experience through routine inspection activities to check the condition of the insulators. This technique, however, takes a long time and is often subjective. Therefore, in this research, the way to detect the degree of corrosion on insulators is by using image processing and using active contour segmentation to determine the degree of corrosion on insulators and using decision trees as a method to create a classification model for the degree of corrosion. This can help reduce reliance on subjective human judgment, increase the effectiveness of the recognition process, and optimize overall isolator maintenance efforts. The application created in this research has a user interface that makes it easier to process images of corrosion insulators. The front page, practice page, and test page comprise this interface. Meanwhile, the results of classification using a decision tree for the low category are in the ratio x1 < 0.082104, the medium category is in the ratio 0.082104 =< x1 < 0.15061, and the high category is in the ratio x1 >= 0.15061 with an accuracy result obtained of 93.33% for test image data and recall and precision values ​​obtained 100% results.

Genetic algorithm optimization of heliostat field layout for the design of a central receiver solar thermal power plant

The heliostat field layout in a central receiver solar thermal power plant has significant optical losses that can ultimately affect the overall output power of the plant. In this paper, an optimized heliostat field layout based on annual efficiency and power of 50 MW for the local coordinates of Quetta, Pakistan, is proposed. The performance of two different heliostat field layouts such as radial staggered and Fermat's spiral distribution are evaluated and different design points in a year are considered for the analysis. The field layouts are then optimized using a rejection sampling based Genetic Algorithm (GA). It considers the output power and mean overall efficiency for vernal equinox, summer solstice, autumnal equinox, and winter solstice as objective functions. The GA optimizes the heliostat field parameters, namely, security distance (DS), tower height (TH), heliostat width to length ratio (WR), and the length of heliostats (LH). The study system was developed in MATLAB for validation. It was observed that for the radial staggered layout, the number of heliostats decreased by 364 and the efficiency was improved by 8.52 % using GA optimization relative to unoptimized results field layout. The annual efficiency for Fermat's spiral configuration was improved by 14.62 % and correspondingly, the number of heliostats decreased by 434.

Electrification of the Orenburg village in 1959-1965

Relevance. The enormous scientific significance of this topic is caused by the correlation of the processes of electrification and modernization of the Soviet village: the widespread use of electricity allowed not only to improve the living conditions of peasants, but also to increase labor productivity. All this together had an impact on the overall level of economic development and contributed to scientific and technological progress. The 1950s and 1960s. They became crucial in relation to the topic under consideration, because it was then that quantitative and qualitative changes took place in comparison with the previous period: the continuous electrification of the village began by connecting collective farms and state farms to high-voltage centralized power plants. This process was most active during the implementation of the seven-year plan for the development of the national economy, which determines the choice of chronological framework.The purpose of the study: to study the process of electrification of the Orenburg village in 1959-1965. Rural electrification in this work is understood as the process of distribution and use of electricity in rural areas: in industrial needs, in households, household premises, cultural, educational and medical institutions.Objectives: to make a periodization of the electrification process of the Orenburg village in the era of the "thaw"; to identify the dynamics of the provision of collective farms and state farms of the Orenburg region with electricity; to trace the development of centralized power supply of the Orenburg village in 1959-1965 and the increase in the length of power transmission lines; to determine changes in the total electricity generation in the Orenburg region during the period under review.Methodology. The work used a set of general scientific and special methods and principles: the principle of objectivity, historicism, historical-comparative, chronological, statistical and other methods.Results. In the course of the study, the process of electrification of the Orenburg village in 1959-1965 was comprehensively studied, its features, results and difficulties were revealed.Conclusion. The continuous electrification of the Orenburg village, despite a number of difficulties, allowed the Orenburg Region not only to overcome the lag behind other administrative-territorial subjects of the Southern Urals, but also to fully provide collective farms and state farms with electricity.

Lessons learnt from a full-scale installation of energy walls

The possibility of equipping diaphragm walls as ground heat exchangers to meet the full or partial heating and cooling demand of overlying or adjacent buildings has been explored in recent years [1, 2, 3, 4]. In this extended abstract a specific installation of energy diaphragm walls is described and the lessons learnt during the implementation discussed.
 The construction site is located in the city of Torino, in the campus of the Politecnico di Torino, where a new underground car park is under construction. The structure consists of four underground floors to be used as a car park for the staff at the academic site. The area of the excavation corresponds to a rectangle 173 m long and 35 m wide. The excavation is supported by more than 170 diaphragm walls. The maximum depth reached by the bulkheads is 17,65 m, while the excavation reaches approximately 15 m below the current ground level and above the water table. The ground at the site is an alluvial deposit consisting of sand and gravel locally cemented to form layers of conglomerate [5]. The construction process involves excavation by means of clamshell buckets, filling by bentonite slurry, lowering of the steel cage in two sections and bottom up filling by concrete.
 To boost the sustainability of its campuses, the Politecnico decided to make effective use of energy geostructures and to equip all single diaphragm walls with heat exchangers. A series of PE-Xa (cross-linked polyethylene) pipes of reduced diameter (32 mm) was introduced to allow the circulation of a heat transfer fluid.
 Considering that the steel cage of the diaphragm walls is constituted of two elements, the pipes were binded to the lower section of the rebar cages while laying in the construction site, before being lowered into the excavation. Two U-shaped pipes are installed for each diaphragm wall so that a distance of 60 cm separates each pipe. The inner pipes will be connected to the inlet, while the external pipes will be connected to the outlet. Pipes were placed on site with spacers to ensure the adequate passage of the concrete aggregates and avoid problems due to contacts with the ground at the excavation contour (Figure 1(a)). A distance of about 10 cm is achieved thanks to the spacers. An extra length of pipes is fixed to the rebar cage for later use.
 The steel cage is lifted by the crane and then lowered into the excavation. Once in place, it is hung to be connected with the upper part of the cage. Then lowering starts again. In this case, the extra pipe, previously hung onto the lower steel cage are unrolled and connected to the upper part of the steel cage by hand by the workers. This process requires the lowering of the cage to be interrupted systematically to allow for the workers to quickly make fast connections (Figure 1(b)). Once the whole steel cage is within the ground, the pipes are placed at rest with a protective coating. All pipes will be connected to inlet and outlet header pipes running outside the car park excavating area and directed to the central thermal power plant of the campus.
 The pipes’ condition was tested several times during the installation. First, a visual check, a pressurization and an emptying were performed before connecting the pipes to the lower part of the steel cage. Then, the pipes were filled with water before concrete casting and kept under pressure at 4 bar for 12 hours minimun during curing. The installation was considered successful if the pressure didn’t reduce by more than 0.1 bar. Despite the design considered the risk of losing up to 10% of the pipes due to unpredictable failures (e.g. crush, failures, contact, etc.), the final result, due to the careful workmanship, was that none of them had to be abandoned.
 The excavation of the area started in 2022, while completion and commissioning of the underground car park are expected for 2024. Connection of the heat exchangers to the heating system will take place after completion resulting in the largest application of energy walls in Italy.

Design and Development of Renewable Energy Battery Storage System

Abstract: Storage alternatives are becoming more critical as energy systems become more decentralised, specialised, and dependent on sporadic clean sources. This is because stable grids and supplies depend on reliable storage. Compressed Air Energy Storage is one technique that is still not being fully utilised. The development of renewable energy over the past 20 years has not been a complete success for grid operators. Decentralized assets that deliver power into the grid at unpredictable intervals are replacing the outdated model of energy production in massive, centralised power plants. The need for effective, sustainable, and affordable energy storage technologies is mostly motivated by the ensuing instability and grid management difficulties. Compressed air-based electricity storage is one of the technologies whose potential has not yet been fully realized. The idea of compressed air energy storage (CAES) is not new. These technologies are currently receiving increased attention due to the need to stabilize the grid, and are moving towards commercial viability thanks to market forces and carbon emission regulation.

PSO tuned interval type-2 fuzzy logic for load frequency control of two-area multi-source interconnected power system

Nowadays, most of modern power systems integrate concentrated renewable energy resources power plants like solar and wind parks in addition to central conventional plants. The output power from these concentrated renewable energy resources varies continuously according to weather conditions like solar irradiance value or wind speed and direction, the variation for their output power may be in mega watts. In this work, Robust secondary load frequency controller (LFC) based on one of artificial intelligent technique which called interval type-2 fuzzy logic controller (IT2FLC) has been proposed for two-area multi-source interconnected power system with central solar park power plants in each area while considering non-linearities in the power system. IT2FLC has accommodated vagueness, distortions and imprecision for the power system input signals which caused by weather fluctuations and system non-linearities. In addition to LFC, another controller based also on IT2FLC has been proposed to control the output power from the central solar parks in each area of generation during cloudy periods instead of maximum power point tracking method (MPPT) in order to enhance the stability for the power system during disturbance periods. In order to enhance the performance of the proposed LFC, particle swarm optimization technique (PSO) has been utilized to optimize the proposed LFC gains to minimize the steady state error, over/under shooting value, settling time and system oscillation for the investigated power system frequency. The performance and the superiority of the proposed PSO tuned IT2FLC is evaluated and compared with another LFC based on PSO tuned cascaded PID controller while applying severe demand load and solar irradiance changes. the simulation has been carried out using matlab/simulink program.

Electric Vehicle Charging Station Automation

Electric vehicles are a promising class of drive trains in the coming years especially in urban regions it is revolution helpful in shifting the decentralized exhaust emission in mega-cities to centralized power plants in rural areas. An intelligent system can be used to manage all the systems using automation technology. Searching for charging stations for electric vehicles is an important issue for drivers which needs the implementation of a smart charging infrastructure network. The automation helps to check the charging slot availability and booking slot for electrical vehicle charging. It is important to reduce waiting time as well as provide improved efficiency. Our system is intended for locating nearby charging stations and slot booking according to waiting time and availability of charging stations. The booking process is automated to improve efficiency in accessing the charging station facilities.

Energy Management of Grid-Connected Microgrids Using an Optimal Systems Approach

Microgrids (MGs) are a growing energy industry segment and represent a paradigm shift from remote central power plants to more localized distributed generation. Controlling MGs represents a challenge mainly due to their complexity and the different properties each asset in the MG has. Various methods have been proposed to address this challenging problem of MG control. Some of these methods are considered the optimal operation of MG assets. Other works are based on a systems approach and address the scalability and simplicity of synthesizing a MG’s energy management system (EMS). <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -variables based logical control strategies, which are practical methods to model control strategies in MGs, can make the control structure more scalable. However, this method is not optimal. On the other hand, Switched Model Predictive Control (S-MPC) is an advanced method utilized to control power systems while satisfying several constraints to achieve an optimal solution based on various criteria. Nevertheless, its implementation is not straightforward. Therefore, to overcome these existing problems, this paper proposes a novel systems approach method called an extended optimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -variable method developed by combining the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -variable based control method with the S-MPC method. This unique method has demonstrated a significant improvement in optimizing an MG’s energy management and enhanced the adaptation and scalability of a control structure of the MG. Our results show that the proposed extended optimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -variable method: (i) reduces the operational cost of MG by nearly 35%; (ii) reduces the usage of the battery energy storage system by 42%, and (iii) enhances the practicality of photovoltaic (PV) usage by 28%. Our novel extended optimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -variable technique also increases the adaptation and scalability of the control structure of the MG significantly by translating the results of S-MPC to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -variable method.

Efficient distributed concentrating solar power system with ammonia-based chemical heat pump

Recently, distributed renewable energy system has become a flexible, reliable and environmentally friendly alternative to the conventional large-scale centralized power plant. This paper proposed a distributed concentrating solar power system coupled with an ammonia-based chemical heat pump. The proposed system is able to upgrade the solar thermal energy absorbed from 450 °C to 650 °C. To design a concentrated solar module, consisting of a Linear Fresnel Reflector field and a Compound Parabolic Collector, for the proposed system, a three-dimensional optical model is developed with SolTrace software. Moreover, the optical model has been validated by comparing the model predicted results with the data from the reference. As for the ammonia decomposition membrane reactor in the system, a three-dimensional reactor model is developed with COMSOL software, which is capable of simulating both ammonia decomposition and hydrogen permeation processes under solar irradiation. With an experimental prototype of the membrane reactor, experiments have been conducted to validate the reactor model. With the validated model, the effects of the reactor length, reactor inlet temperature and ammonia flow rate on the thermochemical conversion efficiency of the reactor have been investigated parametrically. The results show that the reaction conversion increases with the reactor length increasing, while thermochemical conversion efficiency decreases. The thermochemical conversion efficiency increases with reactor inlet temperature and/or ammonia flow rate increasing, which reaches the maximum of 34.9 % in our study. By integrating an ultra-supercritical double reheat power cycle, the system with a low concentration ratio of ∼ 24 can achieve a high solar to power efficiency of ∼ 18.3 %, which surpasses the peak efficiency of a typical concentrating solar power plant with a concentration ratio of ∼ 30.

Distributed energy strategy using renewable energy transformation in Kinmen Island: Virtual power plants that take the military camps as the mainstay

Kinmen island, also known as Quemoy island, is a famous Cold War island on the west side of Taiwan strait which is less than 2 km away from China but under the governance of Taiwan that is 210 km away. The geographical location and political issues make Kinmen a typical island with isolated power grids. Considering Taiwan's 2025 green-energy penetration rate goal of 20%, the implementation of Kinmen Low-Carbon Island 2.0, and transformation of idle military camps into energy-oriented utilizations, this study focuses on employing Kinmen Island's natural resources. Peak sun-hours and military camps are utilized to develop a virtual power plant based on renewable energy, where the resulting distributed energy strategy reduces the demand for fuel oil in existing centralized power plants. The proposed energy management system regulates an energy storage system to compensate for the intermittent power fluctuations of renewable energy at the power-generation end, reducing the burden of backup capacity and balancing the overall power system. This study proposes a customized framework for connecting, transforming, and developing military facilities for Kinmen island to move toward a low carbon island. Evaluation by this study illustrates Kinmen island is capable of achieving 50% renewable energy by building an average of 127.22 kW PV in each of the 850 military camp. And by building an average of 276.47 kW PV in each of the 850 military camp, the goal of 100% renewable energy if also feasible.

Multi-dimensional numerical analysis of flow instabilities in 3D-shaped honeycomb absorbers

Considered a valid alternative to other receiver types, open volumetric receivers for central tower power plants have been developed and researched for multiple decades. 3D-Shaped absorber geometries, made possible by modern manufacturing technologies, particularly offer the promise of high thermal efficiencies. Yet, volumetric absorbers carry the inherent risk of flow instabilities, which can lead to a total failure of the receiver due to local overheating. Therefore, a numerical, multi-dimensional methodology for the flow stability analysis of volumetric absorbers is proposed. The first stage of the methodology applies an 1D LTNE continuum model to quantify the general pressure loss characteristic of an absorber and identifies critical pressure drop levels with potential for flow instability. These levels are tested as part of the second analysis stage using a discrete 3D CFD model against different irradiation and flow perturbations. If the absorber is able to compensate the disturbances, its flow behavior is deemed stable. Otherwise, the absorber geometry is considered susceptible to local overheating due to flow instability.The new methodology has been validated against two reference absorbers with known stable resp. unstable flow behavior. Further, the new approach was applied to analyze the flow stability of two 3D-shaped honeycomb absorber geometries. It was shown that the geometric features of 3D-shaped absorbers can directly improve the flow stability, but do not prevent instabilities automatically. Therefore, a flow stability analysis should be included in design/optimization processes of new volumetric absorbers alongside a maximization of the thermal efficiency.

Effect of Actual Recuperators’ Effectiveness on the Attainable Efficiency of Supercritical CO2 Brayton Cycles for Solar Thermal Power Plants

One of the most promising concentrated solar power technologies is the central receiver tower power station with heliostat field, which has attracted renewed research interest in the current decade. The introduction of the sCO2 recompression Brayton cycles in the near future installations instead of the Rankine cycle is very probable, due to the prospects of a significant efficiency improvement, process equipment size and capital cost reduction. In this study, energy and exergy analysis of a recompression Brayton cycle configuration for a central receiver power station are performed. Special emphasis is given to the computation of actual performance for the High-Temperature Recuperator and the Low-Temperature Recuperator. The results define realistic thermal and exergetic efficiency limits for the specific cycle configurations applied on a central receiver solar power plant with variable turbine entry temperature. Thermal efficiency, predicted with the improved accuracy of heat exchanger computations, does not exceed the 50% target. Overall, a realizable total power plant efficiency of 37% at 900 K turbine entry temperature is predicted, which is a significant improvement on the current state-of-the-art with steam Rankine cycles.

Numerical Investigation of Concentrated Solar Central Billboard with Hexagonal Tubes.

The solar receiver is the most important component of any central solar tower power plant (CSP) system. A numerical analysis of four billboard geometry designs of the central tower receiver was undertaken in this study. On the receiver, the surface area, heat transfer fluid (HTF), and intensity of beam radiation were all constant. The mass flow rate of HTF was modified, and the temperature gain was used as a metric to determine the most efficient design based on the analytical results. Four different models of vertical tube receivers were designed and analyzed. In the analysis, the surface area of the receivers was the same. When compared to the vertical variable circular tube receiver design, the vertical variable hexagonal tube receiver design achieved a marginally higher temperature for the HTF fluid at lower mass flow rates.

Distributed Energy Resources Electrical Systems: Current status and Future prospective

Distributed generation (DG) is an approach that utilizes small scale technologies to generate electricity close to the consumer side. Generally, DG can provide high reliability, high security, low cost electricity, and less environment impact. This paper gives an overview of some of the most significant issues related to the distributed generation (DG). It discusses different aspects of DG, such as definitions, technologies, motivation for moving to DG, some drawbacks associated with the centralized systems which have led to DG. DGs challenges, standards and polices are also presented. In addition, the economic impact and a price comparison between central power plants and DGs are discussed. Also a case study was conducted in order to study the impact of using distributed generations in Edmonton downtown. Three distributed generations, combustion turbine types with 25 MW capacities each have been implemented in Edmonton power system. The total cost estimations have been studied in this case, and the results have revealed that this type of distributed generation is inexpensive and more economic compared with price from the utility. It was estimated from the calculation that the price for the energy is about ¢6.27/kWh while the current electricity price from the utility is ¢8.561/kWh, for long term estimation it is found that the proposed CTs in this project has 11 years for a payback period, after that the project start earning money which is relatively good and wroth investment. The second part of the study analyses the impact of DGs on the system losses using Power-World software, and the result have proven that the loss is significantly decreases when the DG systems are in operation, hence DGs help reducing the costs that associated with the system’s losses.

A Hierarchical Information Extraction Method for Large-Scale Centralized Photovoltaic Power Plants Based on Multi-Source Remote Sensing Images

In the context of global sustainable development, solar energy is very widely used. The installed capacity of photovoltaic panels in countries around the world, especially in China, is increasing steadily and rapidly. In order to obtain accurate information about photovoltaic panels and provide data support for the macro-control of the photovoltaic industry, this paper proposed a hierarchical information extraction method, including positioning information and shape information, and carried out photovoltaic panel distribution mapping. This method is suitable for large-scale centralized photovoltaic power plants based on multi-source satellite remote sensing images. This experiment takes the three northwest provinces of China as the research area. First, a deep learning scene classification model, the EfficientNet-B5 model, is used to locate the photovoltaic power plants on 16-m spatial resolution images. This step obtains the area that contains or may contain photovoltaic panels, greatly reducing the study area with an accuracy of 99.97%. Second, a deep learning semantic segmentation model, the U2-Net model, is used to precisely locate photovoltaic panels on 2-m spatial resolution images. This step achieves the exact extraction results of the photovoltaic panels from the area obtained in the previous step, with an accuracy of 97.686%. This paper verifies the superiority of a hierarchical information extraction method in terms of accuracy and efficiency through comparative experiments with DeepLabV3+, U-Net, SegNet, and FCN8s. This meaningful work identified 180 centralized photovoltaic power plants in the study area. Additionally, this method makes full use of the characteristics of different remote sensing data sources. This method can be applied to the rapid extraction of global photovoltaic panels.