Search Results (166)

In recent years, the global power industry has experienced rapid development, with significant advancements in the source, network, load sectors, and energy storage technologies. The secure, reliable, and economical operation of power systems is a critical challenge. Due to the stochastic nature of intermittent renewable energy generation and the coupled time-series characteristics of energy storage systems, it is essential to simulate uncertain variables accurately and develop optimization algorithms that can effectively tackle multi-objective problems in economic dispatch models for microgrids. This paper proposes a pelican algorithm enhanced by multi-strategy improvements for optimal generation scheduling. We establish eight scenarios with and without pumped storage across four typical seasons—spring, summer, autumn, and winter—and conduct simulation analyses on a real-world case. The objective is to minimize the total system cost. The improved pelican optimization algorithm (IPOA) is compared with other leading algorithms, demonstrating the validity of our model and the superiority of IPOA in reducing costs and managing complex constraints in optimization. Full article

Information and communication technology (ICT) components, especially actuators in automated irrigation systems, are essential for managing precise irrigation and optimal soil moisture, enhancing orchard growth and yield. However, actuator malfunctions can lead to inefficient irrigation, resulting in water imbalances that impact crop health and reduce productivity. The objective of this study was to develop a signal processing technique to detect potential malfunctions based on the power consumption level and operating status of actuators for an automated orchard irrigation system. A demonstration orchard with four apple trees was set up in a 3 m × 3 m soil test bench inside a greenhouse, divided into two sections to enable independent irrigation schedules and management. The irrigation system consisted of a single pump and two solenoid valves controlled by a Python-programmed microcontroller. The microcontroller managed the pump cycling ‘On’ and ‘Off’ states every 60 s and solenoid valves while storing and transmitting sensor data to a smartphone application for remote monitoring. Commercial current sensors measured actuator power consumption, enabling the identification of normal and abnormal operations by applying threshold values to distinguish activation and deactivation states. Analysis of power consumption, control commands, and operating states effectively detected actuator operations, confirming reliability in identifying pump and solenoid valve failures. For the second solenoid valve in channel 2, with 333 actual instances of normal operation and 60 actual instances of abnormal operation, the model accurately detected 316 normal and 58 abnormal instances. The proposed method achieved a mean average precision of 99.9% for detecting abnormal control operation of the pump and solenoid valve of channel 1 and a precision of 99.7% for the solenoid valve of channel 2. The proposed approach effectively detects actuator malfunctions, demonstrating the potential to enhance irrigation management and crop productivity. Future research will integrate advanced machine learning with signal processing to improve fault detection accuracy and evaluate the scalability and adaptability of the system for larger orchards and diverse agricultural applications. Full article

Pumped storage power stations not only serve as a special power load but also store excess electricity from the power system, significantly reducing the curtailment of wind and solar power. This dual function ensures the stable operation of the power grid and enhances its economic benefits. The scheduling optimization problem of a combined wind–solar–pumped storage system is addressed in this study, and an optimization scheduling model is proposed with the objective of maximizing total system revenue. The model is designed to comprehensively account for the generation revenues from wind power, photovoltaic power, thermal power, and pumped storage, as well as the penalty costs associated with pollutant emissions. To address the limitations of traditional algorithms, which are prone to being trapped in local optima and exhibit slow convergence, an improved bat algorithm was developed. The algorithm is enhanced through the use of chaotic mapping to expand the initial solution space, the incorporation of adaptive step-size updates to improve convergence efficiency, and the integration of the Cauchy function to strengthen global search capabilities, thereby effectively avoiding local optima. Simulation results have demonstrated that the improved algorithm achieves significant improvements over traditional bat algorithms and particle swarm optimization (PSO) in terms of optimization efficiency, with total revenue increases of 21.9% and 24.6%, respectively. The optimized scheduling plan is shown to fully utilize the flexible regulation capabilities of pumped storage, mitigating the adverse effects of wind and photovoltaic output fluctuations on grid operations and achieving a balanced trade-off between economic and environmental objectives. Full article

Considering the ambitious climate goals defined by the European Union, the significant share of energy demand represented by buildings, the slow process of their renovation due to challenges such as a need for majority consent from residents and limited available space in dense urban areas, this study aims to foster retrofitting of energy supply systems of multi-storey apartment buildings, improving their sustainability. This entails making the transition to sustainable energy systems more socially acceptable and practical in urban contexts by proposition and demonstration of the potential of a power and heat supply system retrofit that minimises disruptions felt by residents. It integrates rooftop renewable power sources, heat storage with an electric heater, heat pumps, and existing connections to public utility networks. Furthermore, simulation results of both single- and multi-objective optimisation (performed by the genetic algorithm) for equipment selection, as well as conventional and smart control (implemented as a gradient-based optimisation) for daily scheduling, are compared, defining the main scientific contribution of the study. It is found possible to achieve a net present value of up to almost twice the annual energy expenses of the unrenovated building or self-sufficiency rate of up to 41.6% while using conventional control. These benefits can reach 2.6 times or 49.8% if the smart control is applied, demonstrating both the profitability and improved self-sufficiency achievable with the proposed approach in Latvian conditions. Full article

Definitive chemoradiotherapy (CRT) is a cornerstone of treatment for locoregionally advanced head and neck cancer (HNC). Research is ongoing on how to improve the tumor response to treatment and limit normal tissue toxicity. A major limitation in that regard is the growing occurrence of intrinsic or acquired treatment resistance in advanced cases. In this review, we will discuss how overexpression of efflux pumps, perturbation of apoptosis-related factors, increased expression of antioxidants, glucose metabolism, metallotheionein expression, increased DNA repair, cancer stem cells, epithelial-mesenchymal transition, non-coding RNA and the tumour microenvironment contribute towards resistance of HNC to chemotherapy and/or radiotherapy. These mechanisms have been investigated for years and been exploited for therapeutic gain in resistant patients, paving the way to the development of new promising drugs. Since in vitro studies on resistance requires a suitable model, we will also summarize published techniques and treatment schedules that have been shown to generate acquired resistance to chemo- and/or radiotherapy that most closely mimics the clinical scenario. Full article

With the extensive integration of renewable energy into the power grid, pumped storage power plants have become an essential component in the development of modern power systems due to their rapid response capabilities, advanced technology, and other beneficial features. However, high construction costs and irrational capital expenditure and construction schedules have constrained the robust and sustainable growth of pumped storage plants. Therefore, this paper proposes a pumped storage plant construction timing optimization method considering capital expenditure capacity feedback. Initially, an analysis is conducted on the factors that influence the capital expenditure costs of pumped storage power plants throughout their lifecycle. Next, the value of investing in pumped storage plants is assessed across three different aspects: economics, environment, and reliability. Finally, according to the principle of dynamic planning combined with the actual needs and capital expenditure potential of pumped storage plants, the sum of the capital expenditure effectiveness values in each stage is used as the indicator function of each stage to construct the pumped storage plants project capital expenditure timing optimization model, and a simulation analysis is carried out with Province Z as an example to verify the validity and applicability of the proposed model. The findings indicate that the suggested model is effective in balancing the implementation time of individual projects to achieve the maximum cumulative capital expenditure performance over the entire planning period. Full article

Recent advancements in sensor technologies have significantly improved the monitoring and control of various energy parameters, enabling more precise and adaptive management strategies for smart microgrids. This work presents a novel model of an energy management system (EMS) for grid-connected polygeneration microgrids that allows optimizing the management of electrical storage systems, electric vehicles, and other deferrable loads such as heat pumps. The main novelty of this model is that it incorporates both climate comfort variables and the consideration of the degradation of the energy storage capacity in the control strategy, as well as a penalty for the dumping of surpluses. The model has been applied to a smart, sustainable building as a case study. The results show that the proposed model is highly adaptable to diverse weather conditions, minimizing renewable energy losses while satisfying the energy demand and providing comfort to the building’s users. The study shows (i) that EVs’ dynamic charging schedules play a crucial role, (ii) that it is possible to minimize a battery’s degradation by optimizing its cycling, averaging one cycle per day, and (iii) the critical impact of seasonal weather patterns on microgrid energy management and the strategic role of EVs and storage systems in maintaining energy balance and efficiency. Full article

Managing water supply systems is essential for developing countries to face climate variability in dryland settings. This is exacerbated by high energy costs for pumping, water losses due to aging infrastructures, and increasing demand driven by population growth. Therefore, optimizing the available resources using a water–energy nexus approach can increase the reliability of the water distribution network by saving energy for distributing the same water. This study proposes a methodology that optimizes the Water Distribution Network (WDN) and its management that can be replicated elsewhere, as it is developed in a data-scarce area. Indeed, this approach shows the gathering of WDN information and a model to save energy by optimizing pump schedules, which guarantee water distribution at minimal operational costs. The approach integrates a genetic algorithm to create pumping patterns and the EPANET hydraulic simulator to test their reliability. The methodology is applied for a water utility in the dryland urban setting of Lodwar, Turkana County, Kenya. The results indicate a potential reduction in energy costs by 50% to 57% without compromising the supply reliability. The findings highlight the potential of WEN-based solutions in enhancing the efficiency and sustainability of data-scarce water utilities in dryland ecosystems. Full article

With the continuous increase in the penetration rate of renewable energy, the randomness and flexibility demand in the power system continues to increase. The main grid side of the power system vigorously develops pumped hydro storage (PHS) resources. However, the current PHS station scheduling method of a fixed time period and fixed power has lost a certain flexibility supply. In this paper, an optimal dispatching model of multi-pumped hydro storage stations is proposed to supply flexibility for different regions of the state grid in east China. Firstly, the credible predictable power (CPP) of renewable energy is calculated and the definition of flexibility demand of a power system is given. The calculation model for flexibility demand is established. Secondly, considering the regional allocation constraint in the state grid in east China, a non-centralized model of multi-PHS within the dispatch scope is established. In the model, the constraints of storage capacity of different hydropower conversion coefficients of each PHS station is considered. The flexibility supply model of PHS stations to each region of the state grid in east China is established to realize reasonable flexibility allocation. Then, by combining the PHS station models and the flexibility demand calculation model, the optimal dispatching model for the flexibility supply of multi-PHS stations is established. Finally, based on the network dispatching example, the effectiveness and superiority of the proposed strategy are verified by a case study. Full article

In recent years, advanced controllers, including Model Predictive Control (MPC), have emerged as promising solutions to improve the efficiency of building energy systems. This paper explores the capabilities of MPC in handling multiple control objectives and constraints. A first MPC controller focuses on the task of ensuring thermal comfort in a residential house served by a heat pump while minimizing the operating costs when subject to different pricing schedules. A second MPC controller working on the same system tests the ability of MPC to deal with demand response events by enforcing a time-varying maximum power usage limitation signal from the electric grid. Furthermore, multiple combinations of the control parameters are tested in order to assess their influence on the controller performance. The controllers are tested on the BOPTEST framework, which offers standardized test cases in high-fidelity emulation models, and pre-defined baseline control strategies to allow fair comparisons also across different studies. Results show that MPC is able to handle multi-objective optimal control problems, reducing thermal comfort violations by between 66.9% and 82% and operational costs between 15.8% up to 20.1%, depending on the specific scenario analyzed. Moreover, MPC proves its capability to exploit the building thermal mass to shift heating power consumption, allowing the latter to adapt its time profile to time-varying constraints. The proposed methodology is based on technologically feasible steps that are intended to be easily transferred to large scale, in-field applications. Full article

A two-layer scheduling method of energy storage that considers the uncertainty of both source and load is proposed to coordinate thermal power with composite energy storage to participate in the peak regulation of power systems. Firstly, considering the characteristics of thermal power deep peak regulation, a cost model of thermal power deep peak regulation is constructed and fuzzy parameters are used to manage the uncertainty of wind, photovoltaics, and load. Secondly, based on the peaking characteristics and operating costs of composite energy storage, a two-layer optimal scheduling model of energy storage is constructed. The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. Finally, we verify the effectiveness of the proposed strategy based on an IEEE 39-node system. Full article

To explore the advantages in the flexibility of ternary pumped storage units (T-PSUs) compared with fixed-speed pumped storage units (FS-PSUs) and variable-speed pumped storage units (VS-PSUs) in the day-ahead optimal scheduling of power systems, this paper firstly establishes the mathematical model of T-PSUs which is suitable for the target application, and establishes a new hybrid pumped storage model combining both FS-PSUs and T-PSUs for the purpose of improving existing FS-PSUs. Secondly, a day-ahead optimal scheduling model used for a wind-thermal-pumped storage bundled transmission system with the goal of obtaining the lowest operating cost is established. Additionally, various indicators are proposed to comprehensively evaluate the flexibility of different pumped storage unit types on day-ahead optimal scheduling. Finally, a sensitivity analysis is conducted from three aspects: covering the wind power capacity, load rate, and pumped storage capacity. The results indicate that T-PSUs are superior to FS-PSUs and VS-PSUs in maintaining the smooth, economic, and robust operation of thermal power units, as well as in promoting wind power consumption. This provides a significant reference for evaluating the technical and economic benefits of the different types of pumped storage units in applications of future power grids. Full article

Background. Oxidative stress and inflammation are typically implied in atherosclerosis pathogenesis and progression, especially in coronary artery disease (CAD). Our objective was to investigate the oxidative stress and inflammation burden directly associated with atherosclerotic plaque in patients with stable coronary disease undergoing coronary artery bypass graft (CABG) surgery. Specifically, markers of oxidative stress and inflammation were compared in blood samples obtained from the atherosclerotic left anterior descending artery (LAD) and blood samples obtained from the healthy left internal thoracic artery (LITA), used as a bypass graft, within the same patient. Methods. Twenty patients scheduled for off-pump CABG were enrolled. Blood samples were collected from the LITA below anastomosis and the LAD below the stenosis. Samples were analysed for oxidative stress (sNOXdp, H₂O₂, NO) and inflammation markers (TNFα, IL-6, IL-1β, IL-10). Results. The analysis showed a significant increase in oxidative stress burden in the LAD as compared to LITA, as indicated by higher sNOX2-dp and H₂O₂ levels and lower NO levels (p < 0.01). Also, pro-inflammatory cytokines were increased in the LAD as compared to the LITA, as indicated by higher TNFα and IL-6 amounts (p < 0.01). On the other hand, no significant differences could be seen regarding IL-1β and IL-10 levels between the two groups. Conclusions. The oxidative stress and inflammatory burden are specifically enhanced in the LAD artery of stable coronary patients compared to systemic blood from the LITA of stable coronary patients. Full article

The integration of renewable energy sources (RESs) is rapidly increasing within energy systems worldwide. However, this shift introduces intermittency and uncertainty on the supply side. To hedge against RES intermittency, demand-side flexibility introduces a practical solution. Therefore, further studies are required to unleash demand-side flexibility in power systems. This flexibility is relevant across various sectors of power systems, including residential, industrial, commercial, and agricultural sectors. This paper reviews the key aspects of demand-side flexibility within the residential sector. To achieve this objective, a general introduction to demand flexibility across the four sectors is provided. As a contribution of this paper, and in comparison with previous studies, household appliances are classified based on their flexibility and controllability. The flexibility potential of key residential demands, including heat pumps, district heating, electric vehicles, and battery systems, is then reviewed. Another contribution of this paper is the exploration of demand-side flexibility scheduling under uncertainty, examining three approaches: stochastic programming, robust optimization, and information-gap decision theory. Additionally, the integration of demand flexibility into short-term electricity markets with high-RES penetration is discussed. Finally, the key objective functions and simulation software used in the study of demand-side flexibility are reviewed. Full article

Background: The aim of this study is to evaluate atrial involvement by comparing pre- and post-chemotherapy left atrial mechanical and electromechanical parameters in patients treated with cardiotoxic chemotherapeutic agents. Methods: We designed our study as a prospective cohort study. Sixty-eight female patients between the ages of 18 and 50, scheduled for treatment with cardiotoxic chemotherapeutic agents, were included in our study. Atrial mechanical functions and electromechanical parameters were examined and compared with basic echocardiographic parameters before and after chemotherapy. Results: The mean age of the patients was 41.6 ± 7.9 years. After chemotherapy, lateral PA, septal PA, and tricuspid PA durations showed a significant increase (p < 0.001), but there were no statistically significant changes in the left intra-atrial electromechanical delay, the right intra-atrial electromechanical delay, or the interatrial electromechanical delay values. Following treatment, LAVmax, LAVmin, and LApreA significantly increased (p < 0.001). Additionally, the left atrial passive and active emptying volumes increased (p < 0.001), while the reservoir and pump (active emptying) functions decreased (with p-values of 0.03 and 0.01, respectively). The passive emptying function, however, showed no significant change (p = 0.65). Decreases in LVEF were observed, while LVEDD, LVESD, IVS, PW, and LA diameters increased (p-value of 0.02 for IVS and <0.001 for the others). Conclusions: Significant impairment of atrial mechanical functions and electromechanical parameters was observed after treatment with cardiotoxic chemotherapeutic agents. This suggests an elevated likelihood of atrial arrhythmia linked to the use of cardiotoxic chemotherapeutic agents. Full article