Seasonal Load Research Articles

Scenario-based multi-objective optimization strategy for rural PV-battery systems

Increasing the proportion of photovoltaic (PV) electricity in power systems is effective for achieving carbon neutrality. However, PV electricity is unstable and random, and direct connection to the grid reduces power quality and jeopardizes grid security. Herein, a scenario-based optimized sizing and management strategy for a rural PV-battery system is proposed for a village in Central China. The goal of this power system is not only to meet its own electricity demand without other energy supplies, but also to smoothly feed electricity into the grid. In this study, the possibility of applying the optimization strategies and evaluation methods of power plants in the design of rural power systems is explored. The PV power model, battery charging and discharging model, and farmer's energy use model are established respectively, and the constraints are combined with the nodal power balance principle, and then solved by simulated annealing algorithm with economy and grid interaction smoothness as the objective function. For optimal component sizing, this study considered various scenarios with different types of farmers, seasons, and weather to ensure that the performance of the objective function can be satisfied at any time throughout the year. This study proposed the objective function and evaluation index for smooth interaction with the grid for the first time. The simulation results showed that the required PV and battery capacities differed depending on farmer type, owing to different seasonal electrical loads and weather conditions. Compared to traditional PV-battery systems, the proposed system improves the smoothness of interaction with the grid by 87 %, while reducing transformer expansion pressure by approximately 50 kW. Therefore, based on rational capacity selection and optimization strategies, it is possible for a rural power system to become a virtual power plant.

Energy Trading in Local Electricity Markets With Behind-the-Meter Solar and Energy Storage

Distributed energy resources, especially residential behind-the-meter photovoltaics (BTM PV), have been playing increasingly important roles in modern smart grids. Residential netload, which is closely tied with customers' gross load consumption and weather, is usually the only data available for the market operator in a local electricity market (LEM). This paper seeks to design customized prices for an LEM that consists of an agent, BTM PV, energy storage (ES), prosumers, and consumers. The LEM agent who owns a community-scale ES system is responsible for operating the market, determining the internal price, and facilitating the energy sharing within the community. A hierarchical energy trading infrastructure is considered, where the LEM agent acts as the mediator between the external utility grid and customers. A two-stage decision-making framework, including both look-ahead ES scheduling and real-time customized price design, is developed for the agent's profit maximization. Besides, the impacts of netload forecasting and BTM PV disaggregation are also investigated. The customer's consumption behavior is modeled as a utility maximization problem. Compared with the benchmark uniform price design, it is found that the customized pricing scheme could further improve the LEM agent's profit by 4% to 130%, depending on the weather conditions and seasonal load patterns.

Effect of Different Nonstarter Compensatory Strategies on Training Load in Female Soccer Players: A Pilot Study.

In soccer, the day of the week with the highest external load is match day (MD), with starters (>60 minutes per match) showing higher levels of physical fitness and seasonal high-intensity loading. It is necessary, therefore, to determine training strategies to reduce the differences between starters and nonstarters. The aim of this study was to analyze and compare the external load of different training compensatory strategies with match external load in female nonstarters. A strategy combining small-sided games (SSG) and running-based drills (RBD) would reproduce match demands, with RBD leading to greater high-intensity running and SSG leading to a greater number of accelerations and decelerations. Descriptive and comparative study. Level 4. The training and match external load of 14 female players belonging to the same reserve squad of a Spanish First Division Club (Liga Reto Iberdrola) was registered. In the first session after the match (MD+1), nonstarters (<60 minutes in the match) performed 1 of 3 different compensatory strategies: RBD, SSG, or a mixed intervention combining the previous strategies (RBD+SSG). Starters carried out a recovery session. A marked difference in load was observed between the compensatory training strategies and MD. In comparison with MD, RBD showed greater high-intensity and sprint distances and lower acceleration, SSG showed less high-intensity running and sprint distances, lower peak velocity, and greater acceleration, and RBD+SSG registered lower accelerations. In addition, nonstarters covered greater high-intensity running and sprint distances in RBD and achieved higher accelerations in SSG. RBD and SSG compensatory strategies could be recommended to nonstarter female soccer players in MD+1 to compensate for match external load deficits. This study provides comprehensive information on the compensatory exercises of female soccer players, which can be useful for strength and conditioning coaches when developing recovery strategies during a microcycle.

Interference of ocean and land mass changes in seasonal crustal deformation of coastal stations: A case study in northern Australia

In tropical regions, alternation of rainy and dry seasons causes significant land hydrological mass changes. It brings “landward” seasonal crustal movements of coastal global navigation satellite system (GNSS) stations in rainy seasons. Here, we report that the coastal region of the Gulf of Carpentaria (GOC), northern Australia, behaves oppositely, i.e., they move “oceanward” during austral summer months despite large precipitations on land. Here we study seasonal gravity changes there with satellite gravimetry and analyze seasonal movements of GNSS stations in that region. During the austral summer, hydrological mass increases in nearby land areas. In addition to that, sea water mass within the gulf also increases due to east-southeastward seasonal winds. It has larger amplitudes than on land, and its peak comes a few months earlier, resulting in seasonal displacements of coastal GNSS stations driven predominantly by ocean mass changes. In this study, we emphasize the importance of seasonal horizontal crustal movements, i.e., the oceanward displacements of coastal stations there in austral summer clearly indicate the dominance of the excessive ocean mass over those on land. Such seasonal mass changes within GOC have been largely overlooked because of insufficient spatial resolution of satellite gravimetry. This study presents a model case for interpreting complicated seasonal surface deformation caused by significant seasonal load changes on land and ocean, often found in coastal areas of half-closed oceans in the world.

Projection of Sediment Loading from Pearl River Basin, Mississippi into Gulf of Mexico under a Future Climate with Afforestation.

Sediment load in rivers is recognized as both a carrier and a potential source of contaminants. Sediment deposition significantly changes river flow and morphology, thereby affecting stream hydrology and aquatic life. We projected sediment load from the Pearl River basin (PRB), Mississippi into the northern Gulf of Mexico under a future climate with afforestation using the SWAT (Soil and Water Assessment Tool)-based HAWQS (Hydrologic and Water Quality System) model. Three simulation scenarios were developed in this study: (1) the past scenario for estimating the 40-year sediment load from 1981 to 2020; (2) the future scenario for projecting the 40-year sediment load from 2025 to 2064, and (3) the future afforestation scenario that was the same as the future scenario, except for converting the rangeland located in the middle section of the Pearl River watershed of the PRB into the mixed forest land cover. Simulations showed a 16% decrease in sediment load for the future scenario in comparison to the past scenario due to the decrease in future surface runoff. Over both the past and future 40 years, the monthly maximum and minimum sediment loads occurred, respectively, in April and August; whereas the seasonal sediment load followed the order: spring > winter > summer > fall. Among the four seasons, winter and spring accounted for about 86% of sediment load for both scenarios. Under the future 40-year climate conditions, a 10% reduction in annual average sediment load with afforestation was observed in comparison to without afforestation. This study provides new insights into how a future climate with afforestation would affect sediment load into the northern Gulf of Mexico.

Spatiotemporal characteristics of upper-crust seasonal velocity changes in North–South Seismic Belt and South China block in China

Investigating mechanisms and characteristics of the non-tectonic deformation has crucial implications for evaluating the subsurface stress evolution. In this study, we continuously tracked the seasonal velocity changes of Rayleigh wave at 2–10 s with the ambient noise interferometry and discrete wavelet decomposition, in different regions along the actively deforming North–South Seismic Belt (NSSB) and the stable Guangdong region in the South China block in China. The seasonal velocity changes exhibit strong lateral variations across different regions, with much larger seasonality (annual periodicity) and amplitude along the NSSB than those in the stable Guangdong region. There are also small-scale lateral variations inside of each region and generally larger amplitudes of the seasonal velocity changes at greater depth, but the phases (peaks, mostly in winter or summer) at different depths are consistent. The mechanism of the seasonal changes is most likely the direct loading effect of the precipitation, as indicated by consistency in their phases. However, the amplitudes of the seasonal velocity changes seem not controlled by the amount of precipitation, but are more dependent on the tectonic deformation at the different scales, from the correlation between the amplitude of the velocity change and the absolute strain rate. We demonstrate that the crustal media in the regions with larger tectonic background stress are more sensitive to the seasonal loadings. The new finding also highlights the role of the external seasonal loadings in the modulation of seismic activities and risk evaluations. Keypoints•Seasonal seismic velocity variations are found in different regions in China, likely from direct hydrological loadings of precipitation.•The spatial pattern of the seasonal velocity changes is consistent with the distribution of tectonic deformation at multi-scales.•The amplitude of the seasonal velocity changes is more dependent on the magnitude of local deformation than the amount of precipitation.

Long-term nitrate-nitrogen reductions in a large flood control reservoir

Flood-control reservoirs are common in the U.S. and several are located in highly agricultural regions of the Midwest. In this study, a mass balance of annual and seasonal NO3-N concentration and load reductions was calculated for Lake Red Rock, a large flood-control reservoir located on the Des Moines River downstream of the City of Des Moines, Iowa. Utilizing rare long-term upstream and downstream NO3-N monitoring records extending back in time 42 years and combining this with estimates from tributary inputs, Lake Red Rock reservoir was found to remove an average of 7,379 Mg NO3-N per year, representing 12.4 % of the NO3-N inputs to the reservoir. Annual variations in NO3-N loss rate varied considerably (-2.9 % to 41.3 %) and were significantly related to annual reservoir water retention time. Combining study results with literature data, annual NO3-N reduction in Midwestern flood-control reservoirs was logarithmically related to average annual water retention time. Although flood-control reservoirs are designed primarily for flood protection, manipulating the reservoirs to achieve longer water retention times, particularly during periods of high NO3-N concentrations and loads, could be a strategy to alleviate impairments at downstream water suppliers and help state and federal agencies meet NO3-N reduction goals.

Co-Treatment of Winery and Domestic Wastewaters in Municipal Wastewater Treatment Plants: Analysis of Biodegradation Kinetics and Process Performance Impacts

Winery wastewater (WWW) handling strategies often include co-treatment at municipal wastewater treatment plants (WWTPs). Despite this, definitive information regarding oxidation kinetics and process and performance impacts due to co-treatment is lacking. A combined Michaelis–Menten–University of Cape Town kinetic model has been found to best describe the pH-inhibited aerobic biological oxidation of WWW by heterotrophs in activated sludge from four municipal WWTPs. The specific rate of substrate consumption was highest in biomass that had been exposed to WWW (57.3 mg COD/g MLVSS·h) compared to biomass that had not (20.7 mg COD/g MLVSS·h). Bench-scale aerobic co-treatment trials confirm that sorption is a key removal mechanism, with up to 98% chemical oxygen demand and 97% total organic carbon removal after 6 h of reaction time. The WWW solids are quickly incorporated into the biological floc and may improve settleability at loading rates above 75 mg WWW suspended solids/L bioreactor volume at the expense of significantly increasing the observed yield. The aerobic-activated sludge system at municipal WWTPs can effectively co-treat WWW, provided the organic loading rates are limited and the WWTP is designed to accommodate the seasonal loadings of winery wastewater. The identified mitigation measures can be used by co-treating facilities to optimize the co-treatment performance of WWW along with domestic wastewater.

Modelling and Validation of Typical PV Mini-Grids in Kenya: Experience from RESILIENT Project

PV-based mini-grids are identified as a feasible and, often, only economically viable option for the electrification of Kenyan remote and scattered rural areas, where connection to the national grid is challenging, and the related costs are high, if not prohibitive. This paper presents the analysis of typical Kenyan PV mini-grids by using some results of the work in the project “Reliable, Efficient and Sustainable Mini-Grids for Rural Infrastructure Development in Kenya (RESILIENT)”. After presenting average annual and seasonal daily load profiles of residential and small commercial mini-grid customers identified from the measured demands, the paper introduces the main mini-grid components and their models, including a simplified, but reasonably accurate, model of a mini-grid battery storage system based on the manufacturer’s charge–discharge curves. All mini-grid components are assembled in a scalable and easily reconfigurable simulation model of an actual Kenyan PV mini-grid, and they are implemented for the evaluation of PV mini-grid performance and the potential for expansion and connection of additional residential and small commercial customers. During the validation of the developed simulation model using available measurement data, an empirical approach for adjusting the PV system output power is specified for a more accurate match with the measurements. The presented results indicate the importance of the information on the actual control algorithms and control settings of the mini-grid energy management systems, on the thermal dependencies and characteristics of both PV generation system and battery storage system, and on the availability of on-site measurements of temperature and input solar irradiance. The developed PV mini-grid model can be used for further analyses, such as to study the techno-economic performance of different mini-grid configurations, to identify the optimal sizing of mini-grid components, and to specify efficient control and operation schemes based on the locally available resources.

Susceptibility of Microseismic Triggering to Small Sinusoidal Stress Perturbations at the Laboratory Scale

AbstractSmall transient stress perturbations are prone to trigger (micro)seismicity. In the Earth's crust, these stress perturbations can be caused by various sources such as the passage of seismic waves, forcing by tides, or hydrological seasonal loads. A better understanding of the dynamic of earthquake triggering by stress perturbations is essential to improve our understanding of earthquake physics and our consideration of seismic hazard. Here, we study an experimental sandstone‐gouge‐filled fault system undergoing combined far field loading and periodic stress perturbations (of variable amplitude and frequency) at crustal pressure conditions. Microseismicity—in the form of acoustic emissions (AEs)—strains, and stresses, are continuously recorded in order to study the response of microseismicity as a function of loading rate, amplitude, and frequency of a periodic stress perturbation. The observed AE distributions do not follow the predictions of either a Coulomb failure model, taking into account both constant loading and oscillation‐induced strain rates, or a rate and state model. A susceptibility of the system's AE response to the amplitude of the confinement pressure perturbation is estimated, which highlights a linear relation between confinement pressure amplitude and the AE response amplitude, observations which agree with recent higher frequency experimental results on dynamic triggering. The magnitude‐frequency distribution of AEs is also computed. The Gutenberg‐Richter b‐value oscillates with stress oscillations. Our experiments may help complement our understanding of the influence of low inertia stress phenomena on the distribution of seismicity, such as observations of dynamic triggering and seismicity modulation by tides or hydrological loading.

Seasonal peak load prediction of underground gas storage using a novel two-stage model combining improved complete ensemble empirical mode decomposition and long short-term memory with a sparrow search algorithm

Accurate seasonal peak load (SPL) prediction of underground gas storage (UGS) is of great significance for enterprises to formulate scheduling plans. In this work, a novel two-stage model is proposed to predict it. First, improved complete ensemble empirical mode decomposition (ICEEMDAN) is used to decompose the seasonal peak load into several intrinsic mode function. Second, the highest frequency components are smoothed by using Gaussian smoothing (GS), and second highest frequency component is decomposed into several components by applying wavelet transform (WT). Third, long short-term memory (LSTM) optimized by improved sparrow search algorithm (ISSA) is utilized to predict them, and the prediction results of these components are recombined to obtain the final prediction results. Finally, the historical data of Wen 23 in the Zhongyuan gas storage group is taken as a case, and three key issues are discussed. The results: (1) Utilizing ICEEMDAN, GS, WT, and ISSA can effectively improve the prediction performance of the LSTM; (2) The prediction performance of one-step is better than that of multi-step; (3) The comprehensive error and stability evaluation index is reasonable. The following conclusion is reached: the established prediction model can be used as a reference for the development of the UGS scheduling platform.

A Hybrid Feature Pyramid CNN-LSTM Model with Seasonal Inflection Month Correction for Medium- and Long-Term Power Load Forecasting

Accurate medium- and long-term power load forecasting is of great significance for the scientific planning and safe operation of power systems. Monthly power load has multiscale time series correlation and seasonality. The existing models face the problems of insufficient feature extraction and a large volume of prediction models constructed according to seasons. Therefore, a hybrid feature pyramid CNN-LSTM model with seasonal inflection month correction for medium- and long-term power load forecasting is proposed. The model is constructed based on linear and nonlinear combination forecasting. With the aim to address the insufficient extraction of multiscale temporal correlation in load, a time series feature pyramid structure based on causal dilated convolution is proposed, and the accuracy of the model is improved by feature extraction and fusion of different scales. For the problem that the model volume of seasonal prediction is too large, a seasonal inflection monthly load correction strategy is proposed to construct a unified model to predict and correct the monthly load of the seasonal change inflection point, so as to improve the model’s ability to deal with seasonality. The model proposed in this paper is verified on the actual power data in Shaoxing City.

Impact of demand side management approaches for the enhancement of voltage stability loadability and customer satisfaction index

This research work presents the tri-level optimization framework for the optimal scheduling of grid-connected and autonomous microgrids to diminish power losses and maximize loadability. Since the network's voltage profile depends on the loading level, the flexible load shaping-based demand-side management strategy is incorporated to investigate its impact on microgrid loadability. With the consideration of uncertain parameters related to renewable power generation, load demand, and power loss, voltage limit constraints, the resultant problem is formulated as a stochastic mixed-integer non-linear problem to enhance microgrid loadability and optimize daily operating costs. The interdependency of demand side management program and microgrid loadability is investigated. The seasonal load profiles covering the weekend and weekday loads in winter, summer, and spring/fall seasons are examined in this research work. The enhanced versions of the distribution networks IEEE-33 and IEEE-69 based microgrid test systems are chosen to evaluate the proposed framework in both off-grid and autonomous modes of operation. Simultaneously, the overall customer satisfaction index is evaluated and improved according to the seasonal load profiles winter weekday, winter-weekend, summer-weekday, summer-weekend, spring-weekday, and spring-weekend by 8.68%, 7.97%, 16.7%, 19.62%, 17.14%, 20.50% respectively. The recently reported Whale Optimization Algorithm is adopted to solve the proposed optimization problem, and the obtained simulation results are validated by comparing them with popular metaheuristic algorithms. The computational burden on the utility is reduced for optimal scheduling of grid-integrated microgrid to extract maximum power by maintaining network voltage profile.

Life cycle cost assessment for thermal insulation of above-ground spherical container with different capacities in hot fluid storage processes

Due to environmental and economic reasons, thermal energy saving has gained more importance especially in industry. This study is concerned with the application of insulation to improve thermal energy storage in spherical shaped containers positioned high above the ground. For this purpose, the thickness of the insulation applied to spherical containers of different diameters was optimized for convection and radiation heat transfer using life cycle cost analysis. In Turkey, the mechanism of storing the thermal energy of water at different temperatures in four different climatic conditions in Turkey (Ankara, Antalya, Erzurum, and Istanbul) in a container has been investigated. The results of the study show that the optimum insulation thickness and energy savings rise as the water storage temperature and the diameter of the container increase. While there is a 46% increase in the optimum insulation thickness for the vessel diameter from 0.5m to 3m in 20 °C water, a 69% increase is achieved in 100 °C water. Similarly, 85% and 114% increases were found for the optimum insulation thickness from 20 °C to 100 °C for 0.5m and 3m, respectively. In climates with the lowest heating degree-hours (Antalya), the highest energy savings are achieved with the lowest insulation thickness. To accurately determine seasonal storage heat load, a revised heating degree-hour method using hourly solar-air temperature data is recommended. This provides a 13% increase in energy savings.

Peak Load Shifting Control for a Rural Home Hotel Cluster Based on Power Load Characteristic Analysis

The large-scale rural home hotel clusters have brought huge pressure to the rural power grid. However, the load of rural home hotels not only has the inherent characteristics of rural residential buildings but is also greatly impacted by the occupancy rate, which is very different from conventional buildings. Therefore, the existing peak shifting strategies are difficult to apply to rural home hotels. In view of the above problems, this study took a typical visitor village in Zhejiang Province as the research object, which had more than 470 rural home hotels. First, through a basic information survey and power load data collection, the characteristics of its power load for heating, cooling and transition months were studied, and a “No Visitors Day” model was proposed, which was split to obtain the seasonal load curve for air conditioning. Then, combined with the characteristics of the air conditioning power load and the natural conditions of the rural house, a cluster control peak-load-shifting system using phase change energy storage was proposed, and the system control logic was determined and established. Finally, the collected power load data was brought into the model for actual case analysis to verify its feasibility and the effect of peak-load shifting. The results showed that due to the influence of the number of tourists, the electricity loads on weekends and holidays were higher, especially the electricity load of air conditioning equipment in the heating and cooling seasons. An actual case was simulated to verify the peak-shifting effect of the proposed regulation strategy; it was found that the maximum peak load of the cluster was reduced by 61.6%, and the peak–valley difference was 28.6% of that before peak shifting.

Visualising electricity demand: use and users of a 3D chart from the 1950s

Showing electricity demand by the hour, day, month and year, this 3D chart offers a rich visualisation of energy data in the UK from the years 1951–54. Acquired by the Museum of Science & Industry, Manchester, the object is significant as a tangible record of past practice, both of the electricity supply industry and its consumers. In this paper, we offer a close inspection of the object, and following its clues, we generate ideas about the chart’s use and users. In addition to commenting on the rhythmic patterning of daily and seasonal loads, we reflect on the role of the object at the time of its construction, in terms of forecasting, price-setting and load-shifting, and lobbying and demonstration. The object literally materialises electricity demand, providing a distinctive 3D representation, and in so doing prompting questions about how demand changes over time, and in time, and how our practices of everyday life constitute this demand. We conclude by offering a new interpretation of the object as a tool, as well as historical data.

Smart power consumption in energy digital economy: A perspective of the value co-creation mechanism

Residential load is one of the important components of the seasonal peak load of the power grid, and it is increasing each year, with a huge demand response potential. With the development of the energy digital economy, the demand response of the new power system shows the characteristics of multi-stakeholder participation. The development mode based on the value co-creation has become a prominent support for market-oriented reform, and the need for the promotion of smart electricity use is increasingly prominent. In order to realize the in-depth exploration of residents’ demand response potential and the sustainable development of “value co-creation” of smart electricity consumption with the participation of multi-stakeholders, this study adopts both the social network analysis method and the counterfactual analysis approach to reveal the general characteristics of agents promoting the residents to participate in the value co-creation of smart electricity positively. The results show that 1) for social network, both the absolute resource advantage and the structural hole have obvious positive guidance on the agent; however, the incentive effect of the relative resource advantage is not significant; 2) for individual nodes , the role positioning of each agent has obvious guiding function for realizing the value co-creation; and 3) for interrelationship among main agents, the functional relationship has a significant degree of interdependence.

Combined GRACE and GPS to Analyze the Seasonal Variation of Surface Vertical Deformation in Greenland and Its Influence

The geophysical effects are the main factor that causes the nonlinear motion of the station, and a comprehensive analysis of the relationship between the GRACE seasonal load deformation and the GPS station coordinates is helpful to study the physical mechanism that causes the nonlinear motion of the station. Aiming at the continuous GPS coordinate time series in Greenland, this paper comprehensively analyzes the correlation between GRACE seasonal load deformation and GPS station coordinates. First, in order to improve the accuracy of GPS station coordinates, the principle component analysis (PCA) method was used to eliminate the common mode error (CME) of the station coordinates. The results show that this method effectively reduces the uncertainty of the station coordinates time series. Secondly, when extracting seasonal signals, it is found that the singular spectrum (SSA) method can effectively obtain the time-varying part of seasonal signals, and its extraction effect is better than that of the least square fitting (LSF) method. Finally, the seasonal relationship between GRACE load deformation and GPS station coordinates is analyzed from the aspects of time series change, correlation, and WRMS reduction. It is found that there are differences in the amplitude and phase parts of the time series. The mean value of correlation is 0.73, the maximum reduction of WRMS is 55.20% (QAQ1 station), and the minimum is −22.69% (KMJP station), indicating that most stations mainly exhibit seasonal load deformation, while individual stations cannot effectively reflect. In addition, the influence of GRACE seasonal load deformation on the station coordinate parameters is quantitatively analyzed. The results show that the best noise model of the station is mainly WN + FN, which effectively reduces the velocity uncertainty of the station coordinate, and weakens the seasonal term oscillation.

Анализ загрузки и распределения потерь электроэнергии в силовых трансформаторах напряжением 6-10 кВ

Power transformers 6-10/0.4 kV feeding 0.4 kV rural electric networks operate with low load factors. This leads to significant electricity losses. Optimization of the load of 6‑10/0.4 kV power transformers will increase their energy efficiency. To assess the load and loss of electricity in power transformers with a higher voltage of 6‑10 kV of rural electric networks in the Orel district of electric networks (DEN) of the branch of PJSC Rosseti Tsentr - Orelenergo, the authors carried out an analysis of statistical data obtained from operational and technological group dispatcher logs on the load of power transformers 6‑10/0.4 kV of electric networks for 2016‑2022. As a result, it was found that 880 power transformers (74% of the total number) operate with a load factor of less than 20%. Among the 6‑10/0.4 kV power transformers with rated powers of 63, 100, 160, and 250 kVA, the load factor of less than 20% accounts for 72‑77%. It is established that in power transformers 6‑10/0.4 kV of the Orel DEN, annual losses of idle power are 1.8‑2.9 times higher than the short circuit losses. It is revealed that the share of idling losses for different nominal capacities of power transformers 6‑10/0.4 kV is 65‑74% of the total annual electricity losses. The assessment of the load of power transformers is necessary to develop a number of measures to reduce electricity losses in the 0.4 kV electrical networks of the Orel DEN: disconnecting transformers with seasonal loads; replacing underloaded and overloaded transformers with transformers of the required capacity; re-equipping the fleet of 6‑10 kV power transformers with modern power transformers with energy efficiency of class X2K2 and higher.

МІСТОФОРМУЮЧА РОЛЬ УНІВЕРСИТЕТІВ: ВПЛИВ НА СОЦІАЛЬНО-ЕКОНОМІЧНИЙ ТА ПРОСТОРОВИЙ РОЗВИТОК МІСТ

The article presents the results of an evaluation of universities’ role in shaping cities and impact on their socio-economic and spatial development. Using the examples of Lund and Cambridge as university cities, it examines the positive and negative aspects of studentification. Universities exert a multifaceted influence on city development manifested in economic dynamics, demographic shifts, spatial changes, and community cohesion issues. The specifics of contemporary social, economic, and spatial aspects of "studentification" are highlighted through the case studies of Lund and Cambridge. Concentration of students, constituting nearly a third of residents, emerges as the primary outcome of university influence, affecting population dynamics, shaping age structure, and mitigating population aging. Universities’ pivotal role lies in knowledge production and high-quality personnel training, fostering innovative economic sectors within cities. Assessing universities’ spatial impact on city development, GIS-generated heat maps illustrate the distribution of bicycle infrastructure and service areas in urban spaces. The correlation between bicycle parking, entertainment venues, eateries, and other service facilities concentration with university infrastructure and main student accommodation places is evident. Challenges in city development encompass seasonal load on the city environment and infrastructure, the "city and mantle" phenomenon fostering conflicts between residents and students over urban planning, new housing construction, and use of public spaces, alongside issues of gentrification and spatial segregation. Conducting a SWOT analysis of Lund and Cambridge as university cities, this article outlines their development strategies.