Location Of Substations Research Articles

Optimizing offshore wind farm power collection systems using innovative multimodal strategy

This study aims to optimize the electrical layout of offshore wind farms using advanced algorithms and discusses significance of multimodality in offshore cable design. To achieve this, a multimodal optimization approach is introduced which provides a set of optimized solutions for decision-making. The methodology, termed as Nearest Better Neighbor Clustering-Particle Swarm Optimization (NBNC-PSO), leverages the diversity inherent in multimodal algorithms to yield a range of feasible optimized solutions. The approach begins by calculating costs associated with cables within an offshore wind farm collector system, including cable investment, energy loss, and construction costs by considering the wake impact on the wind turbines. The algorithm then facilitates the exploration of various topological structure, optimal cable type selection, cable connections, substation locations proposing multi-optimized modals. By considering changing wind directions and algorithm parameters, the approach enhances the flexibility and robustness of offshore wind farm designs. The proposed method achieves a 14.42% cost reduction under actual wind conditions, and the largest reduction of 15.89% in cost is observed when the wind direction is shifted by 90°.

Optimal planning of HV/MV substation locations and sizes considering battery energy storage systems for peak shaving

Optimal planning of HV/MV substation locations and sizes considering battery energy storage systems for peak shaving

Optimal Substation Placement: A Paradigm for Advancing Electrical Grid Sustainability

The critical importance of optimal substation placement intensifies as the world experiences sustained economic expansion and firmly pursues the decarbonization process. This paper develops an integrative approach to determining the optimal location for a new substation considering the evolving power framework. To this end, a projected 2% national load growth is taken into account, in accordance with the foresight of the Romanian authorities, emphasizing the need to place new substations to enhance the grid’s sustainability. Leveraging the Weibull distribution, a dataset is generated to simulate the anticipated load increase, starting from real power datasets in Romania. Two algorithms are designed for optimal substation positioning: geometric (center-of-gravity-based) and machine learning (K-means clustering). The primary comparison criterion is the minimization of power losses during energy distribution. The results reveal the machine learning approach (i.e., K-means clustering) as the superior alternative, attaining a 60% success rate in minimizing the power losses. However, acknowledging computational constraints, the concurrent utilization of both algorithms is advocated for optimal substation location selection, indicating a potential improvement in outcomes. This study emphasizes the critical need for advanced algorithms, stressing their role in mitigating power losses and optimizing energy utilization in response to evolving load patterns and sustainability goals.

Electrical substations mapping for possible communication technologies using QGIS and Google Earth Pro

The visualization of mapping has aided researchers in gaining a better understanding and studying a specific area in a variety of professions. One of the well-known visualization software for mapping is the Geographic Information System (GIS). This work demonstrates the integration between an open-source GIS technology, named QGIS, and the Google Earth Pro programme in the mapping and analysis of electrical distribution substations. This integration shows the electrical substation data, the possible communication technology ranking, and a map that can be displayed and visualized based on the demographics. The QGIS in this study is used to reclassify the demographics into three main demographics: urban, suburban, and rural areas. On the other hand, the Google Earth Pro programme is used to map and visualize the overall electrical distribution substations alongside the communication technology ranking, based on the three main demographics. A case study using QGIS and Google Earth Pro was carried out in Area X, Malaysia for this investigation. Substation locations in Area X are mapped using Google Earth Pro, and the area’s demographics are categorized as part of the process. The features also enable the technology ranking to be displayed upon clicking the respective color-coded areas, where red represents urban area, yellow represents suburban and green represents rural This integration deems beneficial for future references on electrical distribution substations alongside the possible communication technologies.

Compact Transformers for Offshore Wind Power Plants Applications

The location of step-up offshore substations for offshore wind power plants forces power transformers to be placed on a platform. This offshore platform means a new cost (avoided in a conventional onshore substation) which grows with the transformer weight and footprint surface. As a result, the weight and footprint surface of transformers are new parameters that must be considered in the optimization process of power transformers for offshore wind power plants. The use of compact transformers should lead to the reconsideration of the platform design criteria as compact transformers can reduce significantly the investment cost [1]. The total cost of the transformer, platform and electrical losses have to be evaluated as a whole in order to find the optimal solution. Up to now, no special value has been given to the most compact solution, but the results show that compact solutions have an important impact into the overall economic evaluation.

Multi-Objective Optimization to find the Location and Power Capacity of DC Traction Substations to supply the MRT System with Multi-Train

Multi-Objective Optimization to find the Location and Power Capacity of DC Traction Substations to supply the MRT System with Multi-Train

A site selection framework for urban power substation at micro‐scale using spatial optimization strategy and geospatial big data

AbstractThe world is facing more energy crises due to extreme weather and the rapidly growing demand for electricity. Siting new substations and optimizing the location of existing ones are necessary to address the energy crisis. The current site selection lacks consideration of spatial and temporal heterogeneity in urban power demand, which results in unreasonable energy transfer and waste, leading to power outages in some areas. Aiming to maximize the grid coverage and transformer utilization, we propose a multi‐scene micro‐scale urban substation siting framework (UrbanPS): (1) The framework uses multi‐source big data and the machine learning model to estimate fine‐scale power consumption for different scenarios; (2) the region growing algorithm is used to divide the power supply area of substations; and the (3) location set coverage problem and genetic algorithm are introduced to optimize the substation location. The UrbanPS was used to perform siting optimization of 110 kV terminal substations in Pingxiang City, Jiangxi Province. Results show that the coverage and utilization rate of the optimization results under different power consumption scenarios are close to 99%. We also found that the power can be saved by dynamic regulation of substation operation.

Offshore Wind Farm Layout Optimisation Considering Wake Effect and Power Losses

The last two decades have witnessed a new paradigm in terms of electrical energy production. The production of electricity from renewable sources has come to play a leading role, thus allowing us not only to face the global increase in energy consumption, but also to achieve the objectives of decarbonising the economies of several countries. In this scenario, where onshore wind energy is practically exhausted, several countries are betting on constructing offshore wind farms. Since all the costs involved are higher when compared to onshore, optimising the efficiency of this type of infrastructure as much as possible is essential. The main aim of this paper was to develop an optimisation model to find the best wind turbine locations for offshore wind farms and to obtain the wind farm layout to maximise the profit, avoiding cable crossings, taking into account the wake effect and power losses. The ideal positioning of wind turbines is important for maximising the production of electrical energy. Furthermore, a techno-economic analysis was performed to calculate the main economic indicators, namely the net present value, the internal rate of return, and the payback period, to support the decision-making. The results showed that the developed model found the best solution that maximised the profits of the wind farm during its lifetime. It also showed that the location of the offshore substation played a key role in achieving these goals.

Substation Placement for Electric Road Systems

One option to avoid range issues for electrified heavy vehicles, and the large individual batteries for each such vehicle, is to construct electric road systems (ERS), where vehicles are supplied with electricity while driving. In this article, a model has been developed that calculates the cost for supplying an ERS with electricity from a regional grid to a road in the form of cables and substations, considering the power demand profile for heavy transport. The modeling accounts for electric losses and voltage drop in cables and transformers. We have used the model to exhaustively compute and compared the cost of different combinations of substation sizes and locations along the road, using a European highway in West Sweden as a case study. Our results show that the costs for building an electricity distribution system for an ERS vary only to a minor extent with the location of substations (10% difference between the cheapest cost and the average cost of all configurations). Furthermore, we have varied the peak and average power demand profile for the investigated highway to investigate the impact of a specific demand profile on the results. The results from this variation show that the sum of the peak power demand is the most important factor in system cost. Specifically, a 30% change in the peak power demand for the road has a significant impact on the electricity supply system cost. A reduction in the geographical variation of power demand along the road has no significant impact on the electricity distribution system cost as long as the aggregated peak power demand for all road segments is held constant. The results of the work are relevant as input to future work on comparing the cost–benefit of ERS with other alternatives when reducing CO2 from road traffic—in particular from heavy road traffic.

Оптимизация размещения трансформаторных подстанций в городских микрорайонах с использованием генетического алгоритма и алгоритмов трассировки ЛЭП на карте

To define the placement of electric substations when designing power supply schemes in urban neighborhood is a challenging task since it is necessary to consider spatial restrictions when choosing routes for electric power lines. Thus, the selection of the substation distribution is usually limited by comparison of several variants. In the scientific literature, problems of optimization are usually considered without taking into account real environmental restrictions for the electric power transmission lines. And it significantly reduces the adequacy of the models used. Thus, the study of the possibilities to use both combinatorial optimization methods and the construction of minimum cost routes in the GIS environment to select the optimal layout of electrical substations when designing power supply schemes for urban neighborhood is relevant. The methods to determine the shortest paths on the graphs and the genetic algorithm search are used for the research. The map of the electric lines of Ivanovo city has been used as base data for calculation. A new method has been developed to determine the optimal number and placement of transformer substations to power a lot of buildings on the digital city map. A wave algorithm of cost surfaces is used to estimate the cost of laying cable electric power transmission lines from the consumer to any location of the transformer substation. A genetic algorithm is used to select the network structure. The research results have confirmed the possibility to determine the best transformer substation distribution using GIS with given spatial restrictions.

Optimization of grounding resistance in multitrain DC subway system based on MOEA/D‐DE

AbstractCurrently, in multitrain DC subway system, abnormal increase of rail potential (RP) and stray current (SC) has seriously threatened the safe operation of the system. Over voltage protection device (OVPD) is generally chosen to control the RP, but its action process may increase the amplitude of SC seriously. Here, the grounding resistance of OVPD is optimized by a proposed multi‐objective decomposition algorithm based on differential evolution (MOEA/D‐DE) to suppress the rise of RP and SC synergistically. Firstly, the simulation model of the DC subway system with multitrain is built, the power flow calculation is conducted, and the dynamic RP and leakage current (LC) at the location of traction substation are obtained. Secondly, the double objective optimization model of maximum RP and LC is established and solved by MOEA/D‐DE. Finally, the effectiveness of the proposed method is verified based on the data of Guangzhou Metro Line 2. Results show that the SC of the system can be controlled effectively with OVPD grounding mode after optimization, and integrated control of RP and SC can be accomplished.

Topological Optimization of an Offshore-Wind-Farm Power Collection System Based on a Hybrid Optimization Methodology

This paper proposes a hybrid optimization method to optimize the topological structure of an offshore-wind-farm power collection system, in which the cable connection, cable selection and substation location are optimally designed. Firstly, the optimization model was formulated, which integrates cable investment, energy loss and line construction. Then, the Prim algorithm was used to initialize the population. A novel hybrid optimization, named PSAO, based on the merits of the particle swarm optimization (PSO) and aquila optimization (AO) algorithms, was presented for topological structure optimization, in which the searching characteristics between PSO and AO are exploited to intensify the searching capability. Lastly, the proposed PSAO method was validated with a real case. The results showed that compared with GA, AO and PSO algorithms, the PSAO algorithm reduced the total cost by 4.8%, 3.3% and 2.6%, respectively, while achieving better optimization efficiency.

SEGMENTATION OF ELECTRICAL SUBSTATIONS USING DEEP CONVOLUTIONAL NEURAL NETWORK

Abstract. The location of electrical substations is one of the factors affecting the improvement of electrical energy distribution, as well as the management and control of this energy source. Less cost and manpower will be spent through automating the process of detection and segmentation of these features with the help of deep neural networks and the potential of existing high spatial resolution satellite images. In this study, a deep encoder-decoder neural network was used. This network is one of the most updated deep learning methods in image processing and segmentation. This network has been trained in three RGB bands with the help of high-resolution satellite images (∼1m) and eventually segmented the areas related to electrical substations with relatively high accuracy. As the results of this convolutional neural network, the IOU and Precision parameters were obtained, and their values were 88.2 and 93.7%, respectively, indicating the efficiency of the proposed deep learning method in the segmentation of existing satellite images.

Optimizing wind farm cable layout considering ditch sharing

AbstractWind power is becoming an important source of electrical energy production. In an onshore wind farm (WF), the electrical energy is collected at a substation from different wind turbines through electrical cables deployed over ground ditches. This work considers the WF layout design assuming that the substation location and all wind turbine locations are given, and a set of electrical cable types is available. The WF layout problem, taking into account its lifetime and technical constraints, involves selecting the cables to interconnect all wind turbines to the substation and the supporting ditches to minimize the initial investment cost plus the cost of the electrical energy that is lost on the cables over the lifetime of the WF. It is assumed that each ditch can deploy multiple cables, turning this problem into a more complex variant of previously addressed WF layout problems. This variant turns the problem best fitting to the real case and leads to substantial gains in the total cost of the solutions. The problem is defined as an integer linear programming model, which is then strengthened with different sets of valid inequalities. The models are tested with four WFs with up to 115 wind turbines. The computational experiments show that the optimal solutions can be computed with the proposed models for almost all cases. The largest WF was not solved to optimality, but the final relative gaps are small.

Determination of the service area and location of transformer substations in the city power supply system

The article proposes a theoretically based approach to determining the service areas and location of transformer substations (TS) in the case depending on the intensity of the electric load based on the area specified in the city power supply system. Rational use of service areas and determination of the optimal area by location will help regulate the city's power supply. As a result of the scientific approach in the article, the targeted use of a transformer substation in the municipal power supply system will achieve orderly development in the city, as well as a reduction in the waste of electricity in distribution power networks.

Efficient Strategies for Scalable Electrical Distribution Network Planning Considering Geopositioning

This article presents a heuristic model to find the optimal route or layout of a subway electrical distribution network, obtaining full coverage of users in different scenarios and respecting technical criteria such as maximum distance to avoid voltage drop and capacity. In this way, the location of the transformer substations is achieved through an analysis of candidate sites. The medium voltage network will connect each transformer to a minimum spanning tree (MST), reducing the cost of materials associated with constructing the electrical grid. This work considers the latitude and longitude of each house and electrical count. Georeferenced scenario information is taken from the OpenStreetMap platform to provide an authentic context for distance and location calculations in the deployment of the power grid. The heuristic model offers to decrease time in solving the electrical network layout. As input variables, different powers of the "multi-transformer" transformers are considered to minimize the number of transformers and solve the power supply, reducing the transformers’ oversizing and minimizing the transformers’ idle capacity. The experimentation showed that none exceeded the limit allowed in an urban area of 3.5%.

Offshore Wind Farm Layout Optimization Considering the Power Collection System Cost

The paper proposes a method for optimizing the layout of offshore wind farms to increase their efficiency by reducing the effect of aerodynamic shading, minimizing electrical losses in cable lines of the system for receiving and transmitting electrical energy generated by wind turbines to the electrical grid of the power system. The task is reduced to determining several parameters that define the geometric dimensions and shape of the layout grid with pre-installed tur-bine locations. This approach, in contrast to the coordinate-wise search method, makes it possible to build symmetrical grid layouts of wind power plants, which in practice are more convenient in terms of maintenance and operation. Together with the optimization of the layout, the search for the optimal location of the offshore transformer substation and the synthesis of the scheme of cable joints between wind power plants has been carried out. To solve this problem, a heuristic algorithm was used to search for a minimum spanning tree with a restriction on the conductivity of connections, which made it possible to build realistic schemes and more adequately assess their technical and economic characteristics. As the results of testing the proposed methodology on the example of optimizing the layout of the Horns Rev 1 wind farm have shown, the use of this approach has reduced the cost of the electrical system by 10–12 %. This is 7–11 % higher than the result obtained by using the MST algorithm, which performs the construction of a circuit of cable joints of a simplified topology. The change in the size and shape of the boundaries of the wind farm site resulted in an increase in the estimated electricity generation by 2.3 % and a decrease in its cost by 4 %. When optimizing the layout of wind turbines within the fixed boundaries of the site, these indicators are improved by only 1 and 2 % as compared to the original scheme.

Determining the Optimal Location of Substations for Electric Distribution

Substation optimization involves positioning a substation(s) at the most suitable point with minimum cost. In this study, multiple data were collected from the Turkish Electric Distribution Incorporated Company (TEİAŞ) for the substation in the Eryaman region. The substations will be placed at straight points. Using the capacity of the substations, power, voltage drops, and service interruptions were calculated for a 10-year planning period. Each criterion represents one constraint. The established model serves the following objectives: determining the optimal point and size of the substations in the given planning period by minimizing costs and satisfying the demand of the sectors without service interruption. The model is solved in GAMS and optimal results are obtained. Our results demonstrate that by installing the two substations at the given locations the energy demand of the Eryaman region will be satisfied. To test the model’s applicability for larger systems, the number and the capacity of the substations and the transformers are increased. The results show that optimality has been maintained and that the model remains valid.

Monitoring of power transformers using thermal model and permission time of overload

<p><span>This paper presents the problem of increasing the reliability of electricity</span> supply to consumers. Uninterrupted power supply to electricity consumers depends on the reliability of power supply system in general and power transformers in particular, the accident rate of which is quite high. The causes of the problem are the location of transformer substations at a considerable distance from the service centers, their spreading out over a large area, missing information about the current modes of their operation and so on. One of the ways to solve this problem is development and implementation a system for continuous diagnostics of power transformers. Failure analysis of power transformer based on fault tree is considered, the diagnostic parameters are determined. The insulation wear rate and permission operating time under overload have been defined with help of equivalent heat circuit. It is proposed to use a permission time as a parameter to diagnose the operation mode and increase the efficiency of maintenance of substations through remote monitoring based on the global service mobile (GSM) network. Remote diagnostics allows to receive an information about emergency situation timely. It helps to reduce operating costs, to ensure the reliability and quality of electricity supply for consumers.</p>

Topological structure reengineering regional electric power systems

This paper analyses the topology of a regional power system distribution grid. This research improves the efficiency of the electric power system's operation by using upgrading the redesign (reengineering) methods of topological structures within distribution grids. The research object is an electric power system that consists of generation, transmission and distribution parts and requires reengineering. The subject of research is the re-engineering of the topology of the power system distribution grid. To achieve the research purpose, modifications of k-means algorithm as well as the small step algorithm based on the statistical analysis, clustering and minimum spanning tree development methods of Prim and Kraskal are used. The modifications described in this paper allow for optimization of the network based on user needs, properties of the operating grid elements, and other additional constraints for flexibility and generality. Given the varying parameters, this method provides the means to redesign parts of the distribution grid, keeping its certain elements safe from displacement, but also the means to redesign the whole distribution grid, including changes to the number and location of transformer substations and transmission lines. Conclusions. To solve the problem of determining the territorially close groups of consumers in the paper, it was proposed to use the k-means clustering algorithm. This algorithm allows us to divide consumer sets into clusters, so that coordinates of their centres will be recommended as locations of transformer substations. The modernization of the k-means algorithm was proposed by developing procedures for adding and combining clusters using different strategies for determining starting centroids. Based on this, a method for reengineering the topological structures of regional electric power systems in terms of the possibility of their fundamental restructuring was developed. The results of this research may be useful to various enterprises, organizations or institutes dealing with the elaboration or design of electric power system development on the corporate, regional or local level.