Grid Power Supply Research Articles

Techno – economic and environmental design of a three – phase hybrid renewable energy system for UNVDA Ndop Cameroon using meta-heuristic and analytical approaches

A three – phase hybrid renewable energy system have been proposed in this study as an alternate current grid power supply for an agro – company in the North – West Region of Cameroon. In this study, an industrial load profile with an energy demand of 383.45 kWh/day, 72.79 kWp peak and a residential load with energy demand of 33.26 kWh/day, 2.7 kWp peak have been considered in solving the economic, technical and environmental aspects of the optimization problem. To achieve the best results, a two step methodology has been implored to design the system. The first method requires an analytical approach used to determine the required battery, inverter, diesel generator capacities and the number of three phase PV arrays (NF). The second methodology is a techno – economic and environmental analysis conducted for different number of NF using three meta-heuristic algorithms; ABC, GA and PSO. The obtained results from these methodologies showed that for different values of NF, the REF was in the range 62.9–99.8 % in the Photovoltaic hybrid system (PVHS). The lowest cost of energy was 0.1441 €/kWh at a final REF of 99.8 % compared to a standalone system with an energy cost of 0.1655 €/kWh. The PVHS consist of a 117 kW PV array, 30 kW inverter, 160 kW diesel generator operating at a load factor of 75 % and a battery bank capacity of 43.2 kWh. The Standalone option consist of a 126 kW PV array, 135 kW inverter and a battery bank capacity of 475.2 kWh. The large inverter capacity and battery bank in the standalone system accounts for the high energy cost compared to the PVHS. This study can be used to evaluate and validate the performance of hybrid renewable energy systems for agro – companies whose load profile lack time series data and require a three – phase supply for industrial applications.

Testing Algorithms for Controlling the Distributed Power Supply System of a Railway Signal Box

Trends in the use of renewable energy sources to power buildings do not bypass objects for which maintaining a power supply is critical. This also applies to railway signal boxes. The aim of the research work was to test the multisource power supply system for a railway signal box with power electronic converter systems and a DC bus, built as part of the research project. The assumption for powering the railway signal box building was to use renewable sources, energy storage devices, and a 3 kV DC traction network as the second required power supply grid. Both power grids were connected by power electronic converters, and the power values of the converters were set based on the calculated power balance values using the values measured at the system nodes and the set constraints. The tests primarily tested the response of the power supply system to changes in load power and power generated by the photovoltaic source, as well as the charge level of the energy storage devices. The correctness of the control algorithm’s operation was assessed based on the recorded power values in the power supply system nodes. The tests were carried out for 60 scenarios that covered all normal and emergency operating conditions. During the tests, delays in response to changes in the power supplied to the converters and the values of circular power flow between the power grid connections were recorded. The recorded delays ranged from 2 to about 50 s and the circular power flows did not exceed 1500 W. Based on the results of the tests, it was found necessary to improve the power measurement system in the power supply system nodes and to improve the quality of communication and the transmission time of measurement data transmission time.

Multi-objective online driving strategy optimization for energy storage tram considering battery life

Compared with the traditional overhead contact grid or third-rail power supply, energy storage trams equipped with lithium batteries have been developed rapidly because of their advantages of flexible railway laying and high regenerative braking energy utilization. However, trams may face expensive battery replacement costs due to battery degradation. Therefore, this paper proposes a multi-objective optimization method for the tram's driving strategy to reduce operational energy consumption and extend battery life. The method describes the optimization problem as second-order cone programming (SOCP). It uses the interior point algorithm for fast solving, thus obtaining the theoretical optimal speed trajectory in real-time. This feature enables the method to be applied online. To verify the effectiveness and robustness of the proposed method, we conducted simulations under actual operating conditions. The simulation results show that the proposed multi-objective optimization method can extend the battery life by 40 % compared to the single-objective optimization method for energy saving. As a result, the total cost of the whole life cycle is reduced by 6.54 %. Furthermore, this online optimization driving strategy method can effectively deal with unexpected conditions during the actual operation of the tram to ensure the secure operation, punctual arrival, and precise parking of trams. Finally, the effectiveness of the proposed method is further verified by a hardware-in-the-loop (HIL) test.

Regional Grid Power Supply Radius Planning—A Sensitivity Constraint-Based Approach

Regional Grid Power Supply Radius Planning—A Sensitivity Constraint-Based Approach

Intelligent Diagnosis Method of Transformer Based on Oil Chromatographic Data

Abstract As one of the most important equipment in the operation of power system, ensuring the safe and stable operation of power transformer is a prerequisite for ensuring the normal supply of power grid. The failure of the power transformer will lead to the interruption of the power supply of the power grid and cause huge losses to the national economy. With the rapid development of China’s power grid scale and the continuous improvement of the intelligent construction of modern power system, the number of power equipment such as transformers is increasing. Therefore, it is necessary to make timely and accurate judgment on the status of key power transformation and distribution equipment in the power system, and grasp the operation of electrical equipment in real time, so as to ensure the reliability of power supply in the power system. This paper takes 220kV oil-immersed transformer as the research object. This paper considers the problems and characteristics of the current transformer fault diagnosis methods. By making full use of dissolved gas analysis (DGA) information in oil, a method for diagnosing faults in electrical transformers based on particle swarm optimization and generalized regression neural networks has been proposed. The simulation comparison experiment is carried out to select the most suitable transformer intelligent diagnosis method based on oil chromatographic data.

Techno-Economic Assessment of Liquefied Petroleum Gas-Powered Alternative Electricity Critical Infrastructure Development in Nigeria’s South-West Geopolitical Zone

The decentralization of electricity authority in Nigeria has made it expedient for the South-West Geopolitcal Zone to develop strategic power generation infrastructure. This study assessed the techno-economic viability of the liquefied petroleum gas-powered alternative electricity infrastructure option in Southwestern Nigeria as a mitigation strategy to endemic inadequate grid power supply under the region's integrated electric power programmes. An energy project planning and foresight analysis methodology was used. The study showed that a 25 MW stand-alone LPG-based CHP power plant would require 8.567 acres of land, consume approximately 15.459 million kg of Liquefied Petroleum Gas (LPG) annually, while generating 210,240 MWh of electricity annually. This power plant initiative was considered to have acceptable risk (Payback Period = 9 years 3 months; Return on Investment = 10.73%) and viability at the minimum tariff of $0.11/kWh. It also had considerable annual CO2 emissions and fuel cost savings (255.75 metric kilotonnes and $137.58 million respectively) relative to diesel-based alternative power generation. The study recommended that the viability of the power plant be improved by reductions in operations costs. The study concluded that the LPG plant initiative was technically feasible, economically viable and environmentally friendly, and suitable for deployment in the study area.

The new role of sustainable hydropower in flexible energy systems and its technical evolution through innovation and digitalization

Hydropower has played an important role in Europe in recent decades, offering a unique combination of safe, low-cost, and clean power generation. Today, it is still one of the largest renewable energy sources (RES), accounting for about 35 % of RES electricity generation. However, grid stability is threatened by the increasing amount of undispatchable RES. Flexibility and dynamics such as energy storage and rapid response are urgently needed to achieve EU policy goals. In such a context, hydropower can play a key role, not only as a provider of regulated renewable energy but also due to its ability to balance a renewable energy system in the short term and the medium/long term by pumped storage technology. All these aspects underline the new role of hydropower, which aims to strengthen grid stability and power supply resilience and to enable higher penetration of volatile RES. In this context, the aim of this paper is to demonstrate the role of hydropower at the European level as well as the needs and opportunities of modernization to fully exploit its potential. In particular, this study provides, the assessment of the today flexibility offered by hydropower to the power system at the European level by leveraging a database of information collected through the participants to the working groups of the COST Action Pen@Hydropower which includes stakeholders in the hydropower sector of 34 European countries. The study confirms the key role of hydropower in future energy scenarios with 30 % of the flexibility demand at all time scales met by hydropower. Furthermore, the paper presents a review of the digitalization solutions and innovative technologies that support the growth of a new generation of sustainable hydropower together with the modernization opportunities for existing hydropower plants. The results of this work have practical implications for stakeholders in the hydropower sector and policymakers as it provides evidence at the European scale of the role of hydropower technology in balancing the power system and the need to have supportive frameworks and adequate markets to fully exploit the European hydropower potential to achieve the energy transition goals.

Short-term solar photovoltaic power forecasting using ensemble forecasting strategy for renewable resources based power systems

Environmentally-friendly renewable energy sources have been developed and commercialized to mitigate impact of climate change on the environment. Solar photovoltaic (PV) systems have gained much attention as a power generation source for various uses, including the primary utility grid power supply. There has been a significant increase in both on-grid and off-grid solar PV installations. Because of the highly unpredictable nature of solar power generation, it is crucial to forecast solar power accurately for renewable resources-based power systems. In this research, a swarm-based ensemble forecasting strategy has been proposed to predict solar PV power by combining three strategies, i.e., particle swarm optimization-based gated recurrent unit (PSO-GRU), PSO-based long short-term memory (PSO-LSTM), and PSO-based bidirectional long short-term memory (PSO-BiLSTM). Bayesian model averaging (BMA) combines the output of the proposed strategy by aggregating the output of each swarm-based approach. The performance of the suggested approach is evaluated and verified using historical data of solar PV power which is acquired from Griffith University, Australia. Python 3.11 is used to validate the performance of the proposed ensemble strategy and compared it with several competing strategies. The proposed ensemble strategy outperforms other comparative strategies in terms of RMSE, NRMSE, and MAE.

Power Supply Unit Planning of Distribution Network Including Energy Storage based on N-1 Criterion

In order to realize effective load transfer in medium voltage distribution network when N-1 fault occurs, a method of power supply unit division is proposed. Firstly, according to the content and characteristics of grid planning of distribution network, the principle of power supply unit division is proposed. Then, based on the grid planning of distribution network, the method of power supply unit division is established. Finally, the calculation results show that the division of power supply units based on the power supply grid and energy storage planning improves the line connection rate, meets the N-1 safety check, and improves the safety and reliability of the medium-voltage distribution network.

Powerless in the storm: Severe weather-driven power outages in New York State, 2017–2020

The vulnerability of the power grid to severe weather events is a critical issue as climate change is expected to increase extreme events, which can damage components of the power grid and/or lessen electrical power supply, resulting in power outages. However, largely due to an absence of granular spatiotemporal outage data, we lack a robust understanding of how severe weather-driven outages, their community impacts, and their durations distribute across space and socioeconomic vulnerability. Here, we pair hourly power outage data in electrical power operating localities (n = 1865) throughout NYS with urbanicity, CDC Social Vulnerability Index, and hourly weather (temperature, precipitation, wind speed, lightning strike, snowfall) data. We used these data to characterize the impact of extreme weather events on power outages from 2017–2020, while considering neighborhood vulnerability factors. Specifically, we assess (a) the lagged effect of severe weather on power outages, (b) common combinations of severe weather types contributing to outages, (c) the spatial distribution of the severe weather-driven outages, and (d) disparities in severe weather-driven outages by degree of community social vulnerability. We found that across NYS, 39.9% of all outages co-occurred with severe weather. However, certain regions, including eastern Queens, upper Manhattan and the Bronx of NYC, the Hudson Valley, and Adirondack regions were more burdened with severe weather-driven outages. Using targeted maximum likelihood estimation, we found that the frequency of heat-, precipitation-, and wind-driven outages disproportionately impacted vulnerable communities in NYC. When comparing durations of outages, we found that in rural regions, precipitation- and snow-driven outages lasted the longest in vulnerable communities. Under a shifting climate, anticipated increases in power outages will differentially burden communities due to regional heterogeneity in severe weather event severity, grid preparedness, and population socioeconomic profiles/vulnerabilities. As such, policymakers must consider these characteristics to inform equitable grid management and improvements.

Research on Optimal Operation of Power Generation and Consumption for Enterprises with Captive Power Plants Participating in Power Grid Supply–Demand Regulation

Wind and solar power curtailment and the difficulty of peak regulation are issues that urgently need to be addressed in the process of China’s new electric power system. Enterprises with captive power plants (ECPPs) are large-capacity power consumers and producers, with significant optimization and adjustment potential on both the supply and demand sides. This paper aims to promote the active participation of ECPPs in grid supply–demand regulation and proposes an optimization model for the power generation and consumption of ECPPs based on a day-ahead, intra-day two-stage dispatching model. First, targeting demand response scenarios, mathematical models for analyzing the potential of ECPPs to participate in power grid supply–demand regulation are proposed. Then, an optimization model for ECPP generation and consumption with load regulation is established, and a two-stage dispatching model is proposed to fully mobilize the regulation flexibility of ECPPs. Finally, a robust dispatching model considering price uncertainty is established based on information gap decision theory. The case results show that ECPPs can reduce the curtailment rate in a region by approximately 9%, alleviate the peak pressure of the power grid, reduce carbon emissions by 1373.55 tons, and promote low-carbon development for themselves. Meanwhile, considering price uncertainty strengthens the risk resistance capability of ECPPs and provides a basis for their willingness to participate in supply–demand regulation.

Advanced intelligent optimization for electric vehicle charging stations integrated with photovoltaic system and battery storage in commercial buildings

This paper presents a sophisticated four-stage optimization and intelligent control algorithm tailored for two-way electric vehicle charging (EVC) stations integrated with advanced photovoltaic systems and fixed battery energy storage in commercial buildings. The primary objective is to minimize operating costs while prioritizing customer satisfaction within a dynamic and uncertain energy landscape. Our algorithm optimizes the scheduled charging and discharging of electric vehicles (EVs), local battery storage (BS) units, grid power supply, and deferred loads to balance instantaneous supply and demand. The first stage focuses on developing optimal energy management plans for the day ahead, considering factors such as projected energy production, anticipated EVC demand, and building energy consumption patterns. Building on this foundation, the second stage introduces multilayer EV charging price structures and optimizes participation rewards for discharging, dynamically addressing EV charging patterns and price sensitivities. Approaching the commissioning timeline, the third stage refines energy management plans for the upcoming hours using real-time data and forecasts, adapting to evolving conditions for optimal resource allocation. The final stage involves real-time control and the implementation of optimized programs, dynamically adjusting charge/discharge processes, grid interactions, and load deferral to maintain supply-demand balance and minimize operating costs. Our algorithm enhances system resilience in unpredictable conditions, providing compelling incentives for active EV user participation. Coordinating the integrated system efficiently, including the commercial building’s energy load, ensures reliable service to customers while reducing costs. Extensive case studies and a comparative analysis validate the algorithm’s efficiency in significantly reducing operating costs and enhancing resilience to uncertainty. The paper concludes by highlighting the algorithm’s pioneering role in intelligent EV charging station (CHS) management, offering a cost-effective, customer-oriented, and dynamic energy control strategy for advancing global energy practices.

Design and application research of portable reversible thermochromic patches in grid power supply systems

This study aims to develop a novel portable reversible thermochromic patch and evaluate its potential applications in temperature monitoring and indication. The film is based on the concept of electronic charge transfer thermochromic coatings, enabling accurate detection of high temperatures. Experimental results demonstrate that when the temperature of the monitored device’s circuit reaches 70 °C or above, the color of the film changes from deep blue to colorless, indicating potential overheating in the power grid. Using salt spray corrosion testing and cycle performance testing, we validate the film’s excellent corrosion resistance in harsh natural environments and its provision of reliable color indication. The film possesses portability and ease of attachment to various electrical devices and circuits requiring temperature sensing. By connecting the color information of the film to a computer system, we can achieve digital temperature monitoring, providing potential applications in future smart grid development.

Research on uninterruptable power supply technology for auxiliary winding of electric locomotive while passing the neutral section

PurposeAuxiliary power system is an indispensable part of the train; the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways, which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters. Powered by DC-link voltage of traction converters, the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking. Meanwhile, powered by traction transformers, the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.Design/methodology/approachUninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied. Failure reasons why previous solutions cannot be realized are analyzed. An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper. The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive. This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.FindingsThis scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid. Control objectives of uninterrupted power supply technology are proposed, which are no overvoltage, no overcurrent and uninterrupted power supply.Originality/valueThe control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section. Furthermore, this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

A novel intelligent control approach for wind energy conversion systems with synchronous reluctance generators

SummaryThis study addresses a significant research gap in the field of wind energy, focusing on the underutilized potential of synchronous reluctance generators (SynRG) in wind power conversion systems (WPCS). Despite notable advancements in wind energy controls, the capabilities of SynRG within these systems have not been fully explored. In response, we introduce an innovative model‐free control (MFC) approach, termed intelligent proportional (iP), specifically designed and optimized for WPCS equipped with SynRG. This research encompasses the modeling, control, and simulation of SynRG‐based WPCS, aiming to optimize system performance and enhance the quality of grid power supply. The proposed vector control (VC) method utilizes a MFC approach (VC‐iP) to address the limitations inherent in traditional VC methods with proportional‐integral (PI) controllers (VC‐PI). Although widely used for their simplicity, VC‐PI methods often lead to power fluctuations and decreased power and current quality, consequently reducing overall system efficiency. In contrast, VC‐iP markedly enhances power quality and system efficiency, especially in situations involving fluctuating power demand and variable wind speeds. The efficacy of VC‐iP is demonstrated through simulations in two distinct test scenarios that include variations in power demand and random wind speed fluctuations. The results affirm the superiority of VC‐iP in maintaining stable, high‐quality power output from WPCS. This method notably minimizes fluctuations, improves current quality, reduces harmonic distortion and steady‐state error, ensures reliable grid integration, and contributes to a more efficient and sustainable energy system.

Development of novel optimal operating maps for combined cooling, heating, and power systems

Following Thermal Load (FTL)/Following Electricity Load (FEL) strategy plays a critical role in combined cooling, heating, and power systems (CCHPs) to balance multi-energy supply and load, develop advanced optimal strategy, and optimizing system design and configuration. However, this study found that the conventional FEL/FTL is misemployed as the optimal operating foundation by overlooking the thermal energy wastage during the power generation process. Additionally, this study highlights that current operating schemes relying on FEL/FTL may result in substantial global energy waste due to the disregard for factors such as power generation type, power grid efficiency, optimal cooling supply scheme, and correct operating boundary. In this study, mathematical deduction and case study are performed to demonstrate that the conventional deployment of FEL/FTL is misapplied as optimal solutions. Further, an accurate and comprehensive methodology to derive optimal operating guidelines for diverse CCHP configurations is proposed. The optimal operating maps are derived by comparing primary fuel consumptions under FEL, FTL, and power grid supply schemes. Optimal cooling supply schemes are derived to determine the overall optimal operating strategy. The key findings indicate that the proposed methods for supplying electricity, cooling, and heating offer significant advantages over conventional approaches. Further, the case studies emphasize the potential for primary energy savings of up to 26.6% in hybrid CCHPs. The proposed methodologies serve as valuable references for revising existing research results and pave the way to develop optimal operating solutions for interactive CCHPs.

SIMULATION MODELING OF MULTI-PORT DC-DC CONVERTER IN MPPT SOLAR BATTERY CONTROLLERS UNDER NEURAL NETWORK CONTROL

Photovoltaic generation system - energy system, designed to convert useful solar energy through photovoltaic systems. It can consist of several components, including a solar array, DC/DC and DC/AC semiconductor converter, battery, filter or transformer, control system (CS). Depending on the application, photovoltaic systems can be operated as part of a self-contained power plant or operate on a network. Thus, it is possible to distinguish several basic configurations of photovoltaic generation systems. The standalone generation system is the most common configuration of photovoltaic generation systems, which contains rechargeable batteries (AB). This system is completely independent of the centralized power supply networks and is suitable for comfortable energy supply to consumers. The use of AB makes it possible to increase the reliability of the photovoltaic system and to extend the possibilities of using e.g. battery power is used during insufficient light or when the load exceeds the generation of solar cells. The scope of such configurations are lighting systems of residential and non-residential objects, power supply of houses and buildings, security systems and emergency power supply, power supply of remote residential and non-residential objects, Power supply to spacecraft, etc. Autonomous generation systems typically contain two transducers. The DC/DC converter acts as a battery charge controller. The control system for such a transducer may include the function of tracking the maximum power point for the maximum use of solar energy. The excess energy will be stored in AB. The DC/AC converter converts the DC current energy into the AC energy of the required frequency and voltage. The advantage of such a system is the possibility of using solar energy, both during the day and at night, due to the power of AB and the possibility of using the system at remote sites where there is no grid power supply. The disadvantage of such a system is the loss of double conversion of solar energy and the high cost of batteries. Artificial Neural Network (ANN) provides an alternative way to solve complex problems. A neural network, with the right structure, can compute the values of any continuous function with some predetermined accuracy. The neural network requires no knowledge of the internal parameters of the solar module, learns quickly, has the ability to optimize and approximate. Therefore, the use of INS to track the maximum power point is relevant and of practical and scientific importance. Keywords: multi-port DC converter, artificial neural network (ANN), rechargeable batteries (AB), pulse width modulation (PWM), solar panels (SP), MOSFET power keys

ОПРЕДЕЛЕНИЕ ПРОГНОЗИРУЕМЫХ ЗНАЧЕНИЙ НЕСИНУСОИДАЛЬНОСТИ НАПРЯЖЕНИЯ НА ОСНОВЕ СТАТИСТИЧЕСКОГО АНАЛИЗА

A significant problem of ensuring the quality of electricity, including the sinusoidal voltage in the distribution grids of energy systems and power supply grids, arose with the growth and use of equipment with a nonlinear load characteristic. Modernization of production and an increase in its energy efficiency are associated with the use of such electrical equipment. In this regard, in the last decade, the problem of the higher harmonics has become one of the important consequences of global innovative development throughout the world and in Russia in particular. However, the creation of conditions for the operation of all electric receivers in a power system with poor quality of electrical energy causes certain difficulties. (Research Purpose) The research purpose is determining the predicted values of non-sinusoidal voltage based on statistical analysis in distribution grids. (Materials and methods) Methods for analyzing non-sinusoidal voltage and finding deviations from established norms are considered. Studies of non-sinusoidal voltage in distribution grids have been carried out, and critical values of indicators and a constant component have been determined. (Results and discussion) Additional losses from the influence of higher harmonics in distribution electrical grids account for about 4 percent of losses at sinusoidal voltage. In the grids of agro-industrial enterprises, as well as in the grids of traction substations, similar losses reach 17 percent. The maximum value for the entire measurement period is taken as the basis for the measurement result of the harmonic component voltage coefficient, since this approach does not take into account one-time emissions, which in the general structure do not affect the operation mode of electrical equipment. Measurements were carried out in all electric grids on the low and medium voltage side in the Irkutsk region, and the paper presents the results of measurements in the southern electric grids of Irkutsk and its suburbs. (Conclusions) Studies have revealed the presence of a constant component of the coefficient of harmonic components and single emissions exceeding the average operating values. The main regularities of the non-sinusoidal voltage coefficient for the measurement period and the effect on the operating modes of electrical equipment connected to distribution grids are determined.

ОЦЕНКА ВЕРОЯТНОСТИ НЕСАНКЦИОНИРОВАННОЙ ПОДАЧИ НАПРЯЖЕНИЯ В СЕЛЬСКИХ ЭЛЕКТРИЧЕСКИХ СЕТЯХ 0,4-10 КВ

One of the causes of electrical injuries in rural power grids of 0.4-10 kilovolts is the unauthorized power supply, which is caused by various causes: the fall of a wire from one power line to another (disconnected), incorrect connection of an electric generator in a private household, etc. At the same time, the occurrence of a power supply in the 0.4 kilovolt grid due to reverse transformation at the 10/0.4 kilovolt transformer substation leads to the appearance of a voltage in the 10 kilovolt grid and poses a danger of electric shock both in 0.4 and 10 kilovolt grid. However, it is not possible to identify the number of cases of unauthorized power supply based on statistics or other data due to the fact that this information is not recorded until the accident occurs. Therefore, the definition of cases of unauthorized voltage supply is actual. (Research Purpose) The research purpose is estimating the probability of unauthorized power supply in electrical grids of 0.4-10 kilovolts. (Materials and methods) Methods of expert survey and processing of its results were applied. 74 experts serving rural power grids of 0.4-10 kilovolts were interviewed, who were asked questions about actual cases of unauthorized power supply and the expectation of meeting with such cases. Based on the results of the survey, the specific probabilities of the unauthorized power supply per kilometer of the line were determined (Results and discussion) The actual number of cases of unauthorized power supply recorded by experts has been determined, which amounted to 91 cases over five years, and the specific value is 0.011 cases per kilometer of lines per year. The assessment was carried out taking into account the total length of the grid serviced by experts - 1704 kilometers. The specific value of the probability of unauthorized power supply was determined according to experts (0.0056 cases per kilometer of lines per year). (Conclusions) The number of cases of unauthorized power supply predicted by experts is lower than the actual one, which confirms the need for additional training of personnel of power grid organizations on this issue.

A study of distribution grid topology and its optimization in planning and operation

Abstract This paper combines the characteristics of a distribution network grid, analyzes the topology and application scenarios of a typical grid, and puts forward the design requirements for the optimization of radial DC distribution network grid structure. Based on the constraints of grid optimization, a Pareto multi-objective planning method is selected, and a multi-objective genetic algorithm is designed to improve the grid reliability index of the distribution network grid planning steps. Analyze the parameters of the example, encode the initial 110kV distribution network frame, carry out the optimal solution of the multi-objective genetic algorithm, compare the iteration number and convergence of different genetic algorithms, and obtain the best economic effect of the optimization of the distribution network frame structure. Analyze the power supply reliability index of distribution networks with different grid switching schemes and explore the degree of reliability influence on grid switching and power supply capacity. The optimal solution is obtained in 10 iterations of the algorithm, that is, the objective function is 65.2421 million yuan, and the optimal solution is reached in the interval of the number of iterations [0,100], and the fitness value is in the range of 2 × 104 million yuan.