Peak Load Reduction Research Articles

Analytical Prediction of Crushing Thin-Walled Square Tube with Static Axial Loads Using Elliptical Holes as Crush Initiators

In the structure of passenger vehicles there are components that absorb the impact load, which components are commonly thin-walled square tube. The design of the impact energy absorber model can be carry-out by experiment, simulation, and analysis. In the design of this impact energy absorbing component, an elliptical hole was used as a crush initiator to reduce peak loads and set the start of the bending pattern. Analytical predictions were made to reduce costs and speed up time to obtain mean load and peak loads values from the same shape model. In this study, a thin-walled square tubes model is used with an elliptical hole that have ratio of horizontal axis and vertical axis is from 3:7 until 7:3. The result of this study showed that the prediction of the peak load and average load by analytical means has a good conformity with the simulation. Keywords: Impact energy absorber, analytical, square tube, elliptical hole.

Optimizing Grid Performance in Trinidad and Tobago: The Role of Vehicle-to-Grid (V2G) Technology

This study investigates the impact of integrating 10,000 battery electric vehicles (BEVs) into the electrical grid of Trinidad and Tobago through three charging scenarios: non-incentivized charging, charging at work, and a Vehicle-to-Grid (V2G) program. The results reveal that non-incentivized charging exacerbates peak demand and grid strain, while workplace charging provides only modest peak demand mitigation. In contrast, the V2G scenario significantly reduces peak load impacts and enhances grid stability by leveraging BEVs as dynamic energy storage units that contribute to grid services during high-demand periods. The study proposes a V2G tariff scheme that includes compensation for battery degradation, aiming to incentivize participation and offset potential costs. Economic analysis shows that while V2G involves higher per-MWh costs than conventional storage technologies, it avoids the need for substantial capital investment in static energy infrastructure, presenting a cost-effective solution for energy management in island nations. The findings highlight the potential of V2G technology to facilitate sustainable energy transitions, emphasizing its role in enhancing grid resilience, optimizing renewable energy usage, and reducing carbon emissions. This research underscores the transformative potential of V2G systems as critical enablers of sustainable energy strategies in regions facing similar challenges to Trinidad and Tobago.

Passive and low-energy strategies to improve sleep thermal comfort and energy resilience during heat waves and cold snaps

Sleep is a pillar of human health and wellbeing. In high- and middle-income countries, there is a great reliance on heating, ventilation, and air conditioning systems (HVAC) to control the interior thermal environment in the bedroom. However, these systems are expensive to buy, maintain, and operate while being energy and environmentally intensive—problems that may increase due to climate change. Easily-accessible passive and low-energy strategies, such as fans and electrical heated blankets, address these challenges but their comparative effectiveness for providing comfort in sleep environments has not been studied. We used a thermal manikin to experimentally show that many passive and low-energy strategies are highly effective in supplementing or replacing HVAC systems during sleep. Using passive strategies in combination with low-energy strategies that elevate air movement like ceiling or pedestal fans enhances the cooling effect by three times compared to using fans alone. We extrapolated our experimental findings to estimate heating and cooling effects in two historical case studies: the 2015 Pakistan heat wave and the 2021 Texas power crisis. Passive and low-energy strategies reduced sleep-time heat or cold exposure by 69–91%. The low-energy strategies we tested require one to two orders of magnitude less energy than HVAC systems, and the passive strategies require no energy input. These strategies can also help reduce peak load surges and total energy demand in extreme temperature events. This reduces the need for utility load shedding, which can put individuals at risk of hazardous heat or cold exposure. Our results may serve as a starting point for evidence-based public health guidelines on how individuals can sleep better during heat waves and cold snaps without relying on HVAC.

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Grid-interactive efficient buildings (GEBs) optimize their operations by using flexible load techniques, such as precooling, to reduce peak electricity demand. However, precooling effectiveness depends on factors like building properties, weather, and utility rates. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. On top of that, we investigated the impact of building thermal mass, outdoor air conditions, and energy price profiles on the optimal precooling strategy. Our results show substantial cost savings and peak load reduction potential in buildings with heavy thermal mass, with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings, peak load reduction, and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

Seismic performance evaluation and numerical analysis of CFDST long columns with local corrosion under eccentric compression

In this study, the seismic performance of locally corroded CST and CFDST long columns was evaluated by quasi-static tests. The effects of four levels of corrosion and two types of cross-sections on damage patterns, horizontal load-displacement curves, and seismic indexes were assessed. ABAQUS software was used to conduct extended simulations on long columns of CFDST, analyzing the impact of each parameter on seismic performance. Experimental results indicated that the horizontal load-displacement hysteresis curves of the CFDST long columns within the specified corrosion parameters exhibit robust characteristics, demonstrating improved seismic performance and energy dissipation capacity while preventing sudden damage due to local buckling. The parametric analysis showed that increasing the diameter-to-thickness ratio of the outer steel pipe and decreasing the hollow ratio significantly impact the peak load, whereas increasing the axial compression ratio and eccentricity results in non-uniform specimen damage and reduced peak load.

Real-time cyber/physical interplay in scheduling for peak load optimisation in Cyber–Physical Energy Systems

This paper is about reducing the power consumption of Cyber–Physical Energy Systems (CPESs) composed of many loads through the usage of a scheduling technique inspired by the real-time-computing domain; the electric-load coordination guarantees a more efficient operation of the entire system by avoiding unnecessary concurrent activation of loads and thus limiting the peak load. We represent the power loads themselves as “physical” components and the computing devices that coordinate them as “cyber” components and formally derive the relationship between the operations in cyber and physical domains as the interplay between the schedules enforced on each component: indeed, the schedule of the loads – generated by combining a two-dimensional bin-packing and an optimal multi-processor real-time scheduling algorithm – influences the timing of the processing tasks that are dedicated to the activation/deactivation of loads themselves. We also consider non-schedulable loads by introducing a policy to cope with the presence of such loads. Numerical simulations and experiments confirm the good performance of the proposed peak load reduction method. The usage of real-time scheduling in this context provides inherent resource optimisation by limiting the number of concurrent loads that are active at the same time, thus directly reducing the overall peak load; moreover, thanks to the limited computational complexity of the algorithms, it scales to large systems, overcoming the scalability issues of common optimisation methods. Numerical simulations and experiments confirm the good performance of the proposed peak load reduction method.

Elastic wave suppression through additively manufactured petal lattice metamaterials

Lattice-core sandwich structure metamaterials are lightweight alternatives to monolithic materials that can present better mechanical, thermal, and energy dampening performance. Manufacturing lattice metamaterials to follow curved surfaces can pose a challenge, as the lattices rely on their geometric orientation to the substrate for their mechanical properties. This work rationally designed a lattice structure where the surface is broken up into “petals” connected to the underlying lattice, which localizes the petals’ impact response. This design opens a pathway for implementation of lattice-core sandwich structures onto complex surface geometries. These petal structures were evaluated for their energy absorption efficiency experimentally by utilizing pressure waves generated with nanosecond lasers and computationally via finite element modeling. The lattice structures exhibited a two-orders-of-magnitude decrease in transmitted pressure compared to their constituent steel at equivalent mass. Furthermore, localizing energy absorption into petal structures provided a 44% reduction in peak load compared to a continuous “single-petal” design.

Design and assessment of energy infrastructure in new decarbonized urban districts: A Spanish case study

New urban districts have great potential to reduce greenhouse gas emissions by electrifying energy demand in various sectors, such as transportation and buildings. This paper proposes a novel approach that combines different energy models to plan the infrastructure for supplying the energy demand of new, decarbonized, and highly electrified urban districts on a real-world scale. First, a model for energy management in buildings is used to plan and operate equipment for heating, cooling, and solar photovoltaic distributed generation. Second, a model that plans electric vehicle charging infrastructure determines the number and types of charging stations. Then, a large-scale distribution network planning model designs a cost-efficient electricity distribution grid to supply the district. A case study is presented for a new urban district in Madrid, Spain, to demonstrate how this approach can be applied to energy infrastructure planning in a real-world context. This case study presents different scenarios of energy efficiency performances in buildings and penetration levels of solar installations, electric vehicles, and heating and cooling systems. The results show that even in a high electrification scenario, improving energy efficiency in buildings through a district heating network based on heat pumps can lead to a lower peak electricity demand. This peak load reduction allows for integrating more electric vehicles, avoiding further investments in the electricity distribution network. In addition, the results confirm that a highly electrified scenario, which combines energy-efficient buildings with high integration of solar and electric vehicles, significantly reduces non-renewable energy consumption and greenhouse gas emissions.

Temperature-dependent pinned joint tensile behavior and failure analysis of CF/PEKK composites

The pinned joint tensile properties and failure behaviors of carbon-fiber-reinforced polyetherketoneketone (CF/PEKK) composites are sensitive to application temperatures. Herein, this study investigated the temperature-dependent mechanical behavior of CF/PEKK composites in a pinned joint configuration, emphasizing the impact on tensile behavior and bearing strength. Utilizing Solvay’s CF/PEKK prepreg with a quasi-isotropic stacking sequence, tensile tests were conducted at [Formula: see text]C and 230∘C. At [Formula: see text]C, increased load-pin displacement stiffness was observed, attributed to reduced polymer chain mobility, leading to increased peak load and concentrated bearing area around the pin contact region. Conversely, at 230∘C, a substantial reduction in stiffness and peak load was evident, emphasizing the severe deterioration of pin-load strength. Fracture analysis revealed distinct failure modes at different temperatures, highlighting localized compressive failure at [Formula: see text]C and severe permanent bearing failure at 230∘C. Understanding these temperature-dependent behaviors is critical for optimizing CF/PEKK composite applications in diverse industrial settings, providing insights for enhanced performance and reliability. The findings offer valuable information on the material’s behavior under extreme temperature conditions, contributing to the design and application of CF/PEKK composites in various industrial scenarios.

OVERVIEW AND ANALYSIS OF EQUIPMENT FOR OIL PRODUCTION BY PRESSING AND GRANULATION

The article is devoted to the development of a feed granulator. Granular feed is considered as a promising product for animal husbandry due to their high nutritional value. The description of the feed granulator as the basis for the production of pellets from fodder crops is given. One of the key elements of the granulator is a matrix, which is a steel part with many holes through which the nutrient mass is passed under pressure during granulation. The matrices are divided into planar and annular. Granulators by design are also divided into roller, drum, disc, blade, vibrating and rotarycentrifugal. Granulators can also be domestic and industrial, which differ from each other in different overall dimensions and performance. To date, the production of granulators is carried out at some plants in Russia. Based on the message of the President of the Republic of Kazakhstan, it follows that Kazakhstan needs to establish its own production of equipment for processing raw materials of the agro-industrial complex, including feed pellets. In the course of our research, we have developed a feed granulator. The design of the developed granulator will reduce peak loads on the working bodies, increase reliability, and improve the feed mixture supply to the area of operation of the working bodies. The granulator consists of a base (housing), shafts, an unloading blade, a die, a washer, a screw with an internal hexagon, a spring lock washer, a nut, a screw with an internal hexagon, bearings, a lock washer, a prismatic key, a ring, a screw, a roller and a distribution blade. The developed feed granulator has a simple design and compact appearance. Its design will allow the production of granular feed of good quality and optimal consistency.

A Traumatic Impact Immediately Changes the Mechanical Properties of Articular Cartilage.

To investigate whether and how a single traumatic impact changes the mechanical properties of talar articular cartilage. A marble was placed on the joint surface and a weight was dropped on both medial and lateral caprine talus to create a well-defined single focal impact. The mechanical properties of intact and impacted talar cartilage were measured with a micro-indenter. Elastic (storage) and viscous (loss) moduli were determined by oscillatory ramp and dynamic mechanical analysis protocols. We found significant differences between ankles and within the same ankle joint, with the medial talus having significantly higher storage- and loss moduli than the lateral talus. The storage- and loss moduli of intact articular cartilage increased with greater indentation depths. However, postimpact the storage- and loss moduli were significantly and consistently lower in all specimens indicating immediate posttraumatic damage. The deeper regions of talar cartilage were less affected by the impact than the more superficial regions. A single traumatic impact results in an immediate and significant decrease of storage- and loss moduli. Further research must focus on the development of non- or minimally invasive diagnostic tools to address the exact microdamage caused by the impact. We speculate that the traumatic impact damaged the collagen fibers that confine the water-binding proteoglycans and thereby decreasing the hydrostatic pressure of cartilage. As part of the treatment directly after a trauma, one could imagine a reduction or restriction of peak loads to prevent the progression of the cascade towards PTOA of the ankle joint.

Optimal management of microgrid energy by considering demand side management plan and maintenance cost with developed particle swarm algorithm

This paper introduces a pioneering approach to power system optimization by integrating microgrids and demand-side management, with a focus on its novel contributions. Emphasizing cost reduction, the study targets effective demand management through load shifting. A unique microgrid energy management system is proposed for peak-shaving, leveraging the cost advantages of lower controllable unit expenses. The system actively involves microgrid units in responsive load management, reducing peak consumption during high-demand periods. Evaluation of various demand-side management techniques, especially peak-time rebate programs, is conducted through presented indices measuring the energy management solution's effectiveness. To address the complexity, a particle swarm-based algorithm is introduced for computational efficiency. Validation of the proposed method and model in diverse scenarios showcases significant cost reduction, demonstrating the practicality and innovation of the integrated microgrid and demand-side management strategy. The study highlights a substantial reduction in peak load through load response program participation. At a 20 % participation rate with a 10-cent incentive, there's a significant decrease in peak load during specific hours. With increasing participation and incentives, peak load reduction intensifies, reaching optimal results at a 40 % participation rate and a 20-cent incentive.

Stacked ensemble learning approach for PCM-based double-pipe latent heat thermal energy storage prediction towards flexible building energy

Dynamic performance prediction of the PCM-based double-pipe latent heat thermal energy storage (LHTES) system plays an important role for building peak load shifting. This study presents a stacked ensemble learning framework for the phase change performance prediction of LHTES systems. The proposed model has a two-layer structure involving base and meta models: Regression Tree, Support Vector Regression and Linear Regression. Sensitivity analysis has been utilized for the feature extraction considering possible geometrical and physical parameters of LHTES systems with a fixed PCM volume that can store 0.94 kWh of energy within 255 min. Case studies show that the proposed model outperforms the base models in terms of both prediction accuracy and robustness. Compared with base models, the proposed model has a maximum 7.82% (charging) enhancement in Mean Absolute Percentage Error (MAPE) over all-range data sets and a maximum 16.43% enhancement in MAPE for the initial discharging stage, and has more stable predictive results within the high accuracy zone (accuracy > 95%) with a maximum 7.3% (charging) increase in the distribution density over all-range data sets and a maximum interquartile range reduction of 25.6% (middle discharging stage) in Mean Absolute Error. Application of the proposed model achieved more building peak load reduction.

An innovative method for building electricity energy management in smart homes based on electric vehicle energy capacity

The surging demand for electricity, fueled by environmental concerns, economic considerations, and the integration of distributed energy resources, underscores the need for innovative approaches to smart home energy management. This research introduces a novel optimization algorithm that leverages electric vehicles (EVs) as integral components, addressing the intricate dynamics of household load management. The study’s significance lies in optimizing energy consumption, reducing costs, and enhancing power grid reliability. Three distinct modes of smart home load management are investigated, ranging from no household load management to load outages, with a focus on the time-of-use (ToU) tariff impact, inclining block rate (IBR) pricing, and the combined effect of ToU and IBR on load management outcomes. The algorithm, a multi-objective approach, minimizes the peak demand and optimizes cost factors, resulting in a 7.9% reduction in integrated payment costs. Notably, EVs play a pivotal role in load planning, showcasing a 16.4% reduction in peak loads and a 7.9% decrease in payment expenses. Numerical results affirm the algorithm’s adaptability, even under load interruptions, preventing excessive increases in paid costs. Incorporating dynamic pricing structures like inclining block rates alongside the time of use reveals a 7.9% reduction in payment costs and a 16.4% decrease in peak loads. In conclusion, this research provides a robust optimization framework for smart home energy management, demonstrating economic benefits, peak load reduction potential, and enhanced reliability through strategic EV integration and dynamic pricing.

Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response (DR), a load aggregator (LA) can integrate these loads for scheduling. In this study, a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR. First, based on the operational characteristics of flexible loads such as electric vehicles, air conditioners, and dishwashers, their DR participation, the base to calculate the compensation price to users, was determined by considering these loads as virtual energy storage. It was quantified based on the state of virtual energy storage during each time slot. Second, flexible loads were clustered using the K-means algorithm, considering the typical operational and behavioral characteristics as the cluster centroid. Finally, the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load. The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys, thereby improving the load management performance.

The effect of energy storage on the Residual Load Duration Curve (rLDC) of a system with high Renewable Energy contribution

This paper evaluates how energy storage acting in a system with a very high contribution from variable Renewable source can reduce peak loads. The methodology uses observed demand and renewable generation data to construct scenarios of increasing renewable contribution complemented by energy storage. The analysis is based on the concept of creating load duration curves for the period over which a set of storage technologies can act to reduce peak loads by storing energy during low loads. The models used here are developed on the premise that different types of storage are deployed for different purposes. For the scope of this work, three types were used. The first to manage loads within a day, the second acting over a period of a week, and the third at a much longer, seasonal scale

Energy profiles and electricity flexibility potential in apartment buildings with electric vehicles – A Norwegian case study

Energy flexibility in buildings has the potential to reduce the grid burden of neighbourhoods, yet its practical implementation remains limited. This paper presents a data-based case study from Norway, examining the electricity flexibility potential of electric vehicles, within the context of apartment building loads and PV generation. The results highlight the significant electricity flexibility potential in apartment buildings with EVs, where EV charging can be shifted in time by means of a shared energy management system. Energy profiles are presented, showing how EV charging can increase the average electricity use in apartments by a factor of 1.5 and the power use by a factor of 3.5 to 8.6. Furthermore, the study demonstrates how electricity flexibility KPIs of optimised EV charging in apartment buildings are affected by different energy tariffs, PV generation, V2G technology, and the location of the billing meters. The simulated scenarios showed a maximum reduction of peak loads of 45 %, while a maximum of 38 % of the EV charging was covered by PV generation. The study confirms that residential EV charging emerges as a viable frontrunner in the practical realization of end-user flexibility, paving the way for effective solutions in real-life applications.

Престелген түйіршіктерді өндіру құрылғысын жетілдіру

The article is devoted to the development of a device for the production of pressed granules. Granular feed is considered as a promising product for animal husbandry due to their high nutritional value. The description of the feed granulator as the basis for the production of pellets from fodder crops is given. One of the key elements of the granulator is a matrix, which is a steel part with many holes through which the nutrient mass is passed under pressure during granulation. The matrices are divided into planar and annular. Granulators by design are also divided into roller, drum, disc, blade, vibrating and rotary-centrifugal. Granulators can also be domestic and industrial, which differ from each other in different overall dimensions and performance. To date, the production of granulators is carried out at some plants in Russia. Based on the message of the President of the Republic of Kazakhstan, it follows that Kazakhstan needs to establish its own production of equipment for processing raw materials of the agro-industrial complex, including feed pellets. In the course of our research, we have developed a feed granulator. The design of the developed granulator will reduce peak loads on the working bodies, increase reliability, and improve the feed mixture supply to the area of operation of the working bodies. The granulator consists of a base (housing), shafts, an unloading blade, a die, a washer, a screw with an internal hexagon, a spring lock washer, a nut, a screw with an internal hexagon, bearings, a lock washer, a prismatic key, a ring, a screw, a roller and a distribution blade. The developed feed granulator has a simple design and compact appearance. Its design will allow the production of granular feed of good quality and optimal consistency.

Assessing Peak Load Reduction Potential on Distribution Network: A Case Study of Residential Households in Freetown, Sierra Leone

Assessing Peak Load Reduction Potential on Distribution Network: A Case Study of Residential Households in Freetown, Sierra Leone

Control strategy and capacity optimization of energy-storage-based railway power conditioner

Electrified railroad has the characteristics of high safety factors, high comfort, large transportation capacity, and less time-consuming, which is an effective means to solve traffic congestion. However, with the rapid development of China’s electrified railroad, harmonic, negative sequence and other power quality problems have also been widely concerned, while more and more regenerative braking energy in the traction power supply system can not be effectively utilized. The input of railroad power regulators makes the power quality problem be solved effectively, this paper studies the control strategy of traditional railroad power regulators. Combined with the actual working conditions of railroad vehicles, the simulation model of traction network, vehicles, and railroad power conditioner is established, and the load characteristics of traction substation are simulated by this model. Secondly, for a domestic substation field collection data processing to obtain the actual train operation load changes, to the battery energy storage device life within the maximum economic returns as the optimization goal, for the peak load reduction judgment threshold and the capacity of the battery energy storage device through the genetic algorithm to process the data of previous years to optimize the design.