Energy Balance Strategy Research Articles

Energy balancing strategy for the multi-storage islanded DC microgrid based on hierarchical cooperative control

To simultaneously solve the problems of the state-of-charge (SOC) equalization and accurate current distribution among distributed energy storage units (DESUs) with different capacities in isolated DC microgrids, a multi-storage DC microgrid energy equalization strategy based on the hierarchical cooperative control is proposed. In the primary control layer, the link between the droop coefficient and SOC is established through a logarithmic function, and the droop coefficient is adaptively adjusted according to the SOC value in order to achieve fast SOC equalization. In the secondary control layer, by designing a coordinated state factor, only one PI controller is required to eliminate the influence of the line impedance on the accurate distribution of the output current and the DC bus voltage drop. In the communication layer, local nodes only need to communicate with neighboring nodes without the need for a central controller, and the dynamic consistency algorithm is used to obtain the average value information about the energy storage system (ESS). Finally, the feasibility and effectiveness of the proposed control strategy are verified by experimental analysis on the DC microgrid hardware-in-the-loop experimental platform.

Enhanced energy balancing and optimal load curtailment strategy for DC microgrid integration in hybrid AC/DC distribution networks

AbstractUnleashing the potential of distributed renewable energy sources (RESs), intelligent and autonomous microgrids are becoming pivotal in attaining net‐zero carbon emission goals. Hybrid AC/DC microgrids rise as cutting‐edge microgrid topologies, capitalising on the best of both AC and DC systems. However, the integration of intermittent renewables and uncertainties in loading poses stability challenges. Advanced bidirectional converter controls provide efficient power exchange, but in extreme contingencies, a resilient supervisory control framework (load management/load curtailment approach) is inevitable to withstand/avoid unplanned renewable disruptions/blackouts. Moreover, the operational paradigm shift towards achieving net‐zero emissions, isolated operation of RESs, and conventional load shedding methods are anticipated to encounter substantial challenges, necessitating the development of alternative strategies. In order to improve the stability of hybrid microgrid systems in islanding scenarios, this research presents an energy balancing and load curtailment strategy. The proposed method aims at optimising resource utilisation, prioritising essential loads, and executing an optimal load curtailment strategy (if required), thereby augmenting the stability of systems. Unlike a meta‐heuristic or exhaustive search, which depends on 2n − 1 possible combinations and become unworkable as load numbers increase, the suggested methodology is based on a mathematically modelled load restriction method. By including load criticality, this strategy effectively prevents blackouts even with an increasing number of loads, providing a significantly more useful and practical solution. Additionally, the proposed charging algorithm ensures that the energy storage system imports energy from the grid during off‐peak hours and maximises power generation from the DC subgrid. The efficacy of the proposed strategy is validated using a modified IEEE‐33 bus system as a test case for a hybrid AC/DC microgrid. Simulation results demonstrate the effectiveness of the MILP‐based load curtailment approach in maintaining system stability and preventing blackouts during unforeseen events.

Energy Efficient and Balanced Task Assignment Strategy for Multi-UAV Patrol Inspection System in Mobile Edge Computing Network

Energy Efficient and Balanced Task Assignment Strategy for Multi-UAV Patrol Inspection System in Mobile Edge Computing Network

Synchronization in fractional-order neural networks by the energy balance strategy

Synchronization in fractional-order neural networks by the energy balance strategy

Cooperation Mode and Operation Strategy for the Union of Thermal Generating Unit and Battery Storage to Improve AGC Performance

With the growing penetration of intermittent renewable energy resources in power systems, it is a challenge for automatic generation control (AGC) to maintain the required control performance. In recent years, battery energy storage systems (BESSs) have been installed in thermal power plants to provide frequency regulation service bundled with the traditional thermal generating units (TGUs). However, in real projects, the installed BESS typically works as parasitic equipment of the generating unit, which limits the coordination between the TGU and the BESS. In this paper, a complementary cooperation pattern is proposed for the TGU-BESS union to improve the dispatchability of its response to the AGC signal. Then, the correlation between the BESS's energy demand and the TGU's operation states is described by a data-driven method, which combines fuzzy c-means cluster, r-vine copula, and random forest. Finally, a rolling-horizon energy balance strategy is developed to make the control decisions for the TGU-BESS union in response to the stochastic AGC signal. The effectiveness of the proposed method is demonstrated using the historical data from a real union with a 9MW/4.5MWh BESS and a 350MW coal-fired generator.

Online Energy Balancing Strategy Based on Lyapunov Optimization in Mobile Crowdsensing

In Mobile crowdsensing (MCS), the battery of participants is often limited. When participants perform too many sensing tasks resulting in insufficient remaining energy, they will exit the MCS system. This paper mainly addresses the energy balancing problem to prolong the system lifespan. By this means, it can ensure adequate participants and promote the completion of tasks. First, it formulates a discrete time optimization model, which transforms above problem into the online control of task admission and allocation. In addition, this model uses remaining energy variance of the participants to measure the degree of balance. Next, an online energy balancing strategy (OEBS) is proposed based on the Lyapunov optimization, which can realize energy balance without utility loss. Finally, an approximate optimal policy is presented based on the linear programming and genetic algorithm to solve above optimization problem. Experiments show that OEBS effectively maintains adequate participants, prolongs the lifespan of MCS system and maximizes the system utility even when there are few participants with multiple tasks. Specifically, the lifespan in OEBS is longer than that in utility optimization algorithm (UOA) and LP-relaxation algorithm significantly. The total utility in OEBS is more than that in UOA. OEBS can maximizes average utility of system by adjusting <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V$</tex-math></inline-formula> . In addition, the energy balancing ability of OEBS is always effective as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$V$</tex-math></inline-formula> changes.

Intermittent Fasting and Its Effects on Weight, Glycemia, Lipids, and Blood Pressure: A Narrative Review.

Metabolic syndrome (MetS) has become a significant public health concern globally. Weight managementis crucial in controlling MetS risk factors, making energy balance and weight loss strategies important in nutrition recommendations. Intermittent fasting (IF) has gained traction as a dietary approach for weight management and cardiovascular risk reduction. However, the effects of IF on cardiovascular risk factors have been inconsistent in previous studies. This review aims to summarize the effects of various types of IF on body mass index (BMI), glycemia, lipid profile, and blood pressure, while providing insights into their clinical implications. A comprehensive search of interventional studies and meta-analyses was conducted, and the results were analyzed. The findings indicate that different types of IF lead to mixed effects. Time-restricted eating (TRE) and alternate-day fasting (ADF) consistently showed decreases in BMI, while the outcomes of intermittent energy restriction (IER) were more uncertain. The effects of IF on glycemia and lipid profile were also variable, with TRE and ADF generally showing positive results. However, the impact of IER remained inconsistent. More research is needed to understand the long-term effects and optimal implementation of IF for managing metabolic syndrome and cardiovascular risk factors.

Energy management and balance strategy for underwater glider fleet with VMD-SSA-LSSVM model and central type double-level framework

The management of energy has gained enormous attention as an efficient way to prolong the endurance of unmanned vehicle fleet. During ocean observation and exploration, the variation of the equipped sensor will cause uneven energy consumption for different underwater gliders (UGs), which will lead to the premature accomplishment of the planned mission. Therefore, a novel energy management and balance strategy for the UG fleet is proposed in this paper. Firstly, a new VMD-SSA-LSSVM model is presented to predict the energy consumption of UG based on sea trial data acquired in the northern South China Sea. Besides, the prediction results are compared with those of other benchmark methods and proved their effectiveness. Afterwards, a novel central type double-level framework is established based on low energy adaptive clustering hierarchy protocol to balance the energy of UG fleet, and double-level managing strategies are provided for minor or major energy adjustment based on the energy consumption model. Then the simulation is carried out to verify the effect on different sizes of UG fleet with energy balancing strategy, and the observation efficiency is defined and quantified by many indexes comprehensively. Finally, the simulated results with real data of UG fleet are given, verifying that the energy balance strategy could prolong the endurance by about 4.6% and improve the observation efficiency by about 7%.

Cost-Optimal Sector Integration and Energy Balancing Strategies for Reaching Carbon Neutrality

Sectoral integration will play a major role in the clean energy transition to increase the utilisation rates of available renewable energy sources (RES). Preliminary studies have shown that the decarbonisation of power generation can be reached through well-developed technical solutions such as the integration of hydro, wind, and solar energy. However, emissions in the buildings, transport, and industrial sectors remain stubbornly high. Therefore, the electrification of these sectors and interconnection through smart grids have been identified as promising future development trends to avoid the usage of fossil fuels. The TIMES optimisation model is used to evaluate the future cost-effective pathways for reaching carbon neutrality in the Latvian energy sector. The model includes both the end-use sectors such as transport, buildings, industry and agriculture and the energy sector with a well-developed database of existing and future RES and storage technologies. The modelling framework allows for identifying the cost-optimal future energy mix by considering the electrification potential of each sector. Therefore, it allows analysing of the impact of different policy strategies at sectoral integration levels and the necessity for additional energy storage capacities. The preliminary results show that one of regret-free solutions for reaching the energy efficiency targets in 2030 is the wide expanse of heat pump utilisation in residential buildings instead of inefficient biomass boilers. The building heat supply transformation also brings higher power consumption and interacts with the wider utilisation of wind power. In addition, sensitivity analyses have been performed to evaluate the impact of high uncertainties related to fuel costs, resource availability and other conditions.

Application of direct energy balance control in Supercritical Unit Coordinated Control System

The direct energy balance control strategy is analyzed and combined with the characteristics of supercritical units. The direct energy balance strategy is reconstructed. The reconstructed direct energy balance signal is applied to the boiler master control feedforward in the coordinated control, taking a power plant’s coordinated control system as an example, t. Thus, it is applied to the control of supercritical units, which improves the regulation quality of the control system in a steady and dynamic state, and effectively solves the problems of large fluctuation of mainstream pressure, locked increase, and decrease of load command, frequent withdrawal of coordinated control and unqualified AGC index.

A General Approach to Design Dual Ratiometric Fluorescent and Photoacoustic Probes for Quantitatively Visualizing Tumor Hypoxia Levels In Vivo.

Herein, we describe an energy balance strategy between fluorescence and photoacoustic effects by sulfur substitution to transform existing hemicyanine dyes (Cy) into optimized NIRF/PA dual ratiometric scaffolds. Based on this optimized scaffold, we reported the first dual-ratio response of nitroreductase probe AS-Cy-NO2 , which allows quantitative visualization of tumor hypoxia in vivo. AS-Cy-NO2 , composed of a new NIRF/PA scaffold thioxanthene-hemicyanine (AS-Cy-1) and a 4-nitrobenzene moiety, showed a 10-fold ratiometric NIRF enhancement (I773 /I733 ) and 2.4-fold ratiometric PA enhancement (PA730 /PA670 ) upon activation by a biomarker (nitroreductase, NTR) associated with tumor hypoxia. Moreover, the dual ratiometric NIRF/PA imaging accurately quantified the hypoxia extent with high sensitivity and high imaging depth in xenograft breast cancer models. More importantly, the 3D maximal intensity projection (MIP) PA images of the probe can precisely differentiate the highly heterogeneous oxygen distribution in solid tumor. Thus, this study provides a promising NIRF/PA scaffold that may be generalized for the dual ratiometric imaging of other disease-relevant biomarkers.

A General Approach to Design Dual Ratiometric Fluorescent and Photoacoustic Probes for Quantitatively Visualizing Tumor Hypoxia Levels In Vivo

AbstractHerein, we describe an energy balance strategy between fluorescence and photoacoustic effects by sulfur substitution to transform existing hemicyanine dyes (Cy) into optimized NIRF/PA dual ratiometric scaffolds. Based on this optimized scaffold, we reported the first dual‐ratio response of nitroreductase probe AS‐Cy‐NO2, which allows quantitative visualization of tumor hypoxia in vivo. AS‐Cy‐NO2, composed of a new NIRF/PA scaffold thioxanthene‐hemicyanine (AS‐Cy‐1) and a 4‐nitrobenzene moiety, showed a 10‐fold ratiometric NIRF enhancement (I773/I733) and 2.4‐fold ratiometric PA enhancement (PA730/PA670) upon activation by a biomarker (nitroreductase, NTR) associated with tumor hypoxia. Moreover, the dual ratiometric NIRF/PA imaging accurately quantified the hypoxia extent with high sensitivity and high imaging depth in xenograft breast cancer models. More importantly, the 3D maximal intensity projection (MIP) PA images of the probe can precisely differentiate the highly heterogeneous oxygen distribution in solid tumor. Thus, this study provides a promising NIRF/PA scaffold that may be generalized for the dual ratiometric imaging of other disease‐relevant biomarkers.

Optimization control of a 330 MW drum boiler unit based on DMC algorithm and DEB strategy

This paper firstly established a nonlinear dynamic model of a 330 MW drum boiler unit, which has a clear physical meaning and is conducive to the design of coordinated control system (CCS). On this basis, the boiler energy storage coefficient is calculated, and its relationship with that in direct energy balance (DEB) strategy is analyzed. Secondly, this paper proposes a CCS based on dynamic matrix control (DMC) algorithm and DEB strategy, in which: (1) energy demand and status signals of DEB are taken as the setting point and process value of DMC controller, so as to overcome the internal disturbance of the boiler; (2) a compensation signal is constructed as the feedforward input of DMC controller, so as to overcome the external disturbance of the turbine and realize the timely utilization and supplement of boiler energy. Simulation shows: (1) there is a certain deviation in main steam pressure when the energy demand and status signals are taken as the setting point and process value, but this is an illusion of insufficient energy, and in fact the energy status can already meet the demand; (2) compared with the main steam valve, the constructed compensation signal takes into account more operating parameters of the unit, which greatly improves the accuracy of the compensation. Practical application shows: the grid dispatch order can be well tracked by the unit, the maximum deviation of main steam pressure is ±0.6 MPa in constant pressure mode, and that is ±1.2 MPa in sliding pressure mode, thereby improving the control performance of the unit under high, medium, low, and overall load conditions.

An energy balancing strategy for modular multilevel converter based grid‐connected photovoltaic systems

Modular multilevel converters (MMC)s are promising candidates for large-scale grid-connected photovoltaic (PV) systems. Due to their modular structure, MMCs provide a direct connection of the PV arrays to the converter submodules. They also offer scalability, independent maximum power point tracking, and enhanced power quality with internal power flow capabilities. However, the intermittent nature of PV arrays introduces a power unbalance inside the converter, which affects its operation. This paper addresses the issue and proposes an energy balancing strategy for the grid-connected MMC-based PV system. It uses the internally generated leg currents to control the power flow inside the converter and inject a three-phase balanced current to the grid with low total harmonic distortion. Compared to the existing strategies, the proposed strategy can overcome any condition of the power unbalance with minimal submodule voltage fluctuations. A 162-kW, 9-kV PV grid-connected system is modelled and simulated in MATLAB Simulink environment. The corresponding results are presented to demonstrate the effectiveness of the proposed control strategy for grid-connected PV systems.

Improving the CCS performance of coal-fired drum boiler units base on PEB and DEB strategies

This paper proposes a coordinated control system (CCS) for a coal-fired drum boiler unit based on precise energy balance (PEB) and direct energy balance (DEB) strategies. Firstly, considering the boiler energy storage is extremely complex, this paper proposes a drum boiler model with clear physical meaning. Based on the model, the boiler energy storage is further tested and analyzed. Secondly, considering several key parameters, a PEB strategy for feedforward control is proposed. Combined with the DEB strategy and load command (LDC) reconstruction, the CCS of the unit is designed. Simulation results show that the PEB strategy can achieve precise feedforward control, the LDC reconstruction can greatly improve the evaluation indicators of the unit load, and the CCS can adapt well to changes in coal quality and boiler energy storage. Application results show that the unit load can track its set point well under small and large ranges of load swing. The ramp rate is up to 13.2MW/min, the load accuracy is less than 1.2MW/min, the response time is less than 22s, and the comprehensive indicator is up to 4.35. Therefore, the CCS can be highly adapted to the dispatching demand of power grid. In addition, the boiler combustion is stable, the max deviations of steam pressure and temperature are 0.7MPa and 6.4°C, respectively.

Comprehensive Comparison of Modular Multilevel Converter Internal Energy Balancing Methods

Stacking of floating structures, known as submodules or cells, provides the modular multilevel converter with theoretically unlimited voltage scalability. However, such a convenience comes at a price of increased control complexity, especially in the domain of internal energy control. In other words, energies of the submodule clusters must be controlled to their setpoint values; otherwise, stable and high-performance operation of the converter cannot be ensured. So far, several approaches toward balancing of the modular multilevel converter internal energy, in both vertical and horizontal directions, have been proposed. Nevertheless, differences among them have never been analytically supported. In this article, three seemingly different energy balancing strategies are thoroughly explained, providing a framework for the theoretical comparison of different dynamic responses provided by them. All the results are verified on the large-scale hardware-in-the-loop platform, serving as a digital twin of a grid-connected 3.3-kVac/5-kVdc 1.25-MW converter being driven by the industrial ABB PEC800 controller.

Serious analytical inconsistencies challenge the validity of the energy balance theory

Energy metabolism theory affirms that body weight stability is achieved as over time the average energy intake equals the average energy expenditure, a state known as energy balance. Here it is demonstrated, however, that weight stability coexists with a persistent energy imbalance. Such unexpected result emerges as a consequence of the answers to three fundamental problems: 1. Is it possible to model body weight fluctuations without the energy balance theory? And if so, what are the benefits over the energy balance strategy? 2. During energy balance, how the oxidized macronutrient distribution that underlies the average energy expenditure is related to the macronutrient distribution of the average energy intake? 3. Is energy balance possible under a low-fat diet that simultaneously satisfies the following conditions? (a) The fat fraction of the absorbed energy intake is always less than the oxidized fat fraction of the energy expenditure. (b) The carbohydrate fraction of the absorbed energy intake is always greater or equal to the oxidized carbohydrate fraction of the energy expenditure. The first of these issues is addressed with the axiomatic method while the rest are managed through analythical arguments. On the whole, this analysis identifies inconsistencies in the principle of energy balance. The axiomatic approach results also in a simple mass balance model that fits experimental data and explains body composition alterations. This model gives rise to a convincing argument that appears to elucidate the advantage of low-carbohydrate diets over isocaloric low-fat diets. It is concluded, according to the aforementioned model, that weight fluctuations are ultimately dependent on the difference between daily food mass intake and daily mass loss (e.g., excretion of macronutrient oxidation products) and not on energy imbalance. In effect, it is shown that assuming otherwise may caused unintended weight gain.

Presentation and interaction of Internet of Things data based on augmented reality

In recent years, AR (Augmented Reality) technology has gradually entered people’s horizons and has become a research hotspot in the field of image processing. At the same time, the mobility and interactivity of AR have also been valued. This paper studies the interaction technology in the AR scene, and proposes a scheme to detect the user’s gaze at the cone perspective. The Leapmotion body sensor was used for gesture extension, and the hardware connection and data transmission scheme of Leapmotion and Holo Lens was designed. Based on the three input modes of sight, gesture and voice, the interaction logic between the user and the system in the AR scene is designed. The network of the Internet of Things is dominated by wireless sensor networks (Wireless Sensor Networks). This paper studies the problem of congestion in wireless sensor network sensing data transmission. WSNs nodes need to transmit the sensed data or preprocessed sensed data to sink nodes. When the data packets (or packets) received by a sensor node exceed its upper limit for forwarding or processing data packets, the excess data packets need to be buffered. When the memory of cached packets is full, excess packets are discarded, causing buffer overflows and causing node-level congestion. This paper proposes an energy balance strategy based on feedback control. The feedback control algorithm is used to adjust the node’s transmit power to realize the redistribution of node load in the network, solve the problem of node energy imbalance in wireless sensor networks, and further extend the sensor network.

City-scale morphological influence on diurnal urban air temperature

Urbanization patterns affect urban thermal environments. Studies have characterized the asymmetry of daily urban air temperature based on the increase in mean temperature, decrease in amplitude, and significant phase delay in the highly compact high-rise city of Hong Kong. In this study, a simple physical-based energy balance strategy was developed to investigate urban morphological impacts on city thermal climate. This energy balance model was first evaluated by using a meso-scale model, i.e. a weather research and forecasting model coupled to the BEP-BEM urban canopy model, and then applied to investigate urban daily air temperature profiles in a high-rise compact city. The modelling results show that urban thermal storage has no direct impact on the mean urban air temperature, but does affect amplitude and phase. The results reveal that different city morphologies lead to different urban air temperature profiles. Two important parameters for engineers and urban planners are introduced: a relative convective heat transfer number λ, and a time constant, τ, which respectively describe the relationships between convective heat transfer and urban thermal storage and ventilation rate in urban areas. These two parameters modulate the mean, amplitude term, and phase term of the daily urban air temperature cycles. The results have significant implications for design of city morphologies and urban planning of climate-resilient cities. The new results from this study and the proposed simple model should facilitate the rapid development and testing of potential urban heat island mitigation strategies.

Adaptive Energy Balanced Routing Strategy for Wireless Rechargeable Sensor Networks

The network lifetime of wireless rechargeable sensor network (WRSN) is commonly extended through routing strategy or wireless charging technology. In this paper, we propose an optimization algorithm from the aspects of both charging and routing process. To balance the network energy in charging part, node’s charging efficiency is balanced by dynamically planning charging point positions and the charging time is allocated according to the energy consumption rate of nodes. Moreover, the routing method is adapted to the node’s charging efficiency. The adaptive routing strategy assigns more forwarding tasks to nodes that can get more energy during the charging phase, and makes the data packets transmit farther away, thus reducing the average hops and energy consumption of the network. Finally, the simulation results reveal that the proposed algorithm has certain advantages in prolonging the network lifetime, reducing the average hop counts and balancing the energy of each node.