Power Reserve Research Articles

Rural Green Tourism as a Factor in the Development of Rural Areas

Abstract. Introduction. Today, the tourism industry in Ukraine is only the fifth most important component of budget filling, but its share should increase significantly given such objective prerequisites as favorable geopolitical location of Ukraine in central Europe, the presence of significant tourist and recreational potential, favorable climate, rich flora and fauna, numerous world-class cultural and historical monuments. The general state and potential of rural green tourism in Ukraine are investigated in the work, the problems and prospects of its development are determined. Rural green tourism for Ukraine is a new concept, although it is developing quite actively. Research has shown that rural green tourism in combination with other industries will be able to solve a number of economic, social and environmental problems inherent in rural areas of Ukraine. It is determined that rural green tourism is one of the promising areas of national internal tourism in Ukraine. Purpose. The purpose of the article is to study the current state of rural green tourism in Mykolaiv region and to develop theoretical provisions and practical recommendations for its further development. Results. The essence and varieties of rural green tourism, processes of formation and factors of its development are investigated in the work. The views of scientists on the interpretation of the concept of “rural green tourism” are systematized. It is established that a common feature of rural tourism is the concept of the created atmosphere, which mainly determines the quality of the tourist product from the standpoint of the consumer. The study carried out a comprehensive assessment of the socio-economic conditions of the industry, characterized the natural resource potential of Mykolaiv region, which is quite attractive for tourists. The main recreational zones of Mykolaiv region, which will promote the formation and development of the location of rural green tourism, are analyzed. It is substantiated that for the formation of the tourist product of the region it is necessary to involve not only a powerful nature reserve fund, historical and architectural heritage, but also the agricultural sector, which produces organic products. The study identified factors that delay the development of rural green tourism. They include the lack of government policy and information support, proper rural infrastructure, limited choice of leisure, high share of agricultural production and manual labor in farms, absence of coordination center between rural communities, authorities and consumers about tourism development. It is determined that the successful development of rural green tourism requires a strategy that takes into account the specialization of each area and emphasizes the uniqueness of the tourist product. Conclusions. Prospects for the development of green tourism in rural areas are described. The internal potential and possibilities of its involvement for the development of green tourism are determined. It is established that green tourism can be an additional factor in filling the revenue side of the budget of rural settlements. The creation of a new tourist location is proposed and its economic efficiency is substantiated. The implementation of the proposed recommendations will promote mutually beneficial cooperation between the rural green tourism market of the region and local governments, environmental protection, as well as sustainable rural development.

Covid-19 crisis impact on the next generation of physicians: a survey of 800 medical students

BackgroundMany initiatives have emerged worldwide to handle the surge of hospitalizations during the SARS-CoV-2 pandemic. In France, the University of Paris North called on its medical students, whose status makes them integral members of the healthcare staff, to volunteer in their capacity of medical students and/or as nurses/nursing aids in understaffed intensive care units and other Covid-19 services. We attempted to evaluate their commitment, whether the pandemic affected their certainty for the medical profession and career choices, and how they scored their sadness and anxiety levels.MethodsThe University of Paris North took a weekly official census of the involvement of 1205 4th–6th year medical students during the first lockdown in France. Six weeks after the lockdown began (May 4th), an e-questionnaire was sent to 2145 2nd-6th year medical students. The survey lasted 4 weeks and documented volunteering by medical students, the association between the pandemic and certainty for their profession, their choice of medical specialty and factors that influenced sadness and anxiety scores.Results82% of 4th–6th year medical students volunteered to continue their internship or be reassigned to COVID-19 units. Of 802 2nd-6th year students who completed the e-questionnaire, 742 (93%) volunteered in Covid-19 units, of which half acted as nurses. This engagement reinforced the commitment of 92% of volunteers to become physicians. However, at the peak of the outbreak, 17% had doubts about their ability to be physicians, while 12% reconsidered their choice of future specialty. Finally, 38% of students reported a score of 7/10 or more on the sadness scale, and 43% a score of 7/10 or more for anxiety. Neither study year nor service influenced sadness or anxiety scores. However, gender influenced both, with women scoring significantly higher than men (p < 0.0001).ConclusionMedical students of the University of Paris North who made an early and unconditional commitment to help hospital staff handle the pandemic constituted a powerful healthcare reserve force during the crisis. Although the vast majority remained convinced that they want to become physicians, this experience came at a significant psychological cost, especially for women. Alleviating this cost would improve future crisis responses.

Methods of ensuring the operational stability of dc-dc power supply in arctic conditions

THEPURPOSE.To consider the features of development and exploitation of DC-DC power supplies for Arctic conditions, to show the key problems and existing methods of solving them, to identify prospective directions in the design of this type of devices.METODS.Theworkismainlyanover-viewwiththequestionsofconstruction,circuitdesign,controlprinciples,maintainingthermalequilibrium,choosingofelectricelementsandminiaturization.Thefirstpartofthearticleisdevotedtothereviewofscientificpublicationsandpatents,in the second part the idea of using a parallel architecture in frost-resistant power supplies is considered, giving an opportunity to adapt modular principle of device construction.RESULTS.Thearticleexaminestheissuesofadaptingthemodularapproachtothespecificsoffrost-resistantpowersupplies.Inthiswayyoucanbuilda self-healing, configurable, easy-to-repair power supply of wide application. With modular construction principle the entire electrical complex consists of parallel-connected cells, placed in one hermetic and heated case (a case with connectors on the surface, as well as the control and display units).CONCLUSION. Parallelconnectionofthecellsallowstoprovidea significant power reserve in the power supply, to perform a quick replacement of faulty modules without interrupting the power supply process, to increase/reduce the system power easily by changing the number of working cells. The system acquires special advantages, if the output voltage levels of the cells are adjustable. In this case, it is possible to build a universal configurable power supply of wide application,whichisa novelty on the market. If you group the cells on the output, you can use one power supply for several different consumers. The spare parts for the power supply are as simple as possible and consists of ready-made cells and connecting wires. The obtained results can be used in development of fault-tolerant secondary DC-DC power supplies for hard operating conditions.

Multiobjective Scheduling of Hybrid Renewable Energy System Using Equilibrium Optimization

Due to increasing concern over global warming, the penetration of renewable energy in power systems is increasing day by day. Gencos that traditionally focused only on maximizing their profit in the competitive market are now also focusing on operation with the minimum pollution level. The paper proposes a multiobjective model capable of finding a set of trade-off solutions for the joint optimization problem, considering the cost of reserve and curtailment of power from renewable sources. Managing a hybrid power system is a challenging task due to its stochastic nature mixed with the objective function and complex practical constraints associated with it. A novel metaheuristic Equilibrium Optimizer (EO) algorithm incepted in the year 2020 utilizes the concept of control volume and mass balance for finding equilibrium state is proposed here for computing the optimal schedule and impact of renewable energy integration on profit and emission for different optimization objectives. In this paper, EO has shown dominant performance over well-established metaheuristic algorithms such as particle swarm optimizer (PSO) and artificial bee colony (ABC). In addition, EO produces well-distributed Pareto-optimal solutions and the fuzzy min-ranking is used as a decision maker to acquire the best compromise solution.

Endogenous Approach of a Frequency-Constrained Unit Commitment in Islanded Microgrid Systems

Power reserves are usually scheduled in day-ahead unit commitment (UC) to minimize operating costs while maintaining system security. In applying basic UC (bUC) after a contingency, the system frequency may fall upon the activation of the load-shedding global control (under-frequency load-shedding or UFLS) limits. Small isolated microgrids are more sensitive to this issue due to their lack of inertia. Including dynamic considerations into the bUC problem can minimize UFLS activation and also avoid the need for the operator to later check the short-term feasibility of a bUC solution. These proposals are known as Frequency-Constrained UC (FCUC), although the implementation are very time-consuming. FCUC implementation will increase the system’s operational costs, which should be calculated to estimate remuneration to the safety service based on the additional reserve provision. The electrical system of Gran Canaria island has suffered several episodes of greater blackouts in recent years. Shortly, there will be 242 MW of wind generation installed (26% of the thermal power installed on Gran Canaria). The main objective of this work is to improve the island system reliability by means of an FCUC formulation applied by the system operator in practice, including renewable sources. The results show that the frequency values remained within the admissible boundaries, but the system’s operational costs increased by around 13%.

Dependence of the increase in the power reserve of an electric vehicle on the season when using a non-flat battery of photovoltaic converters

Due to the fight against CO2 emissions and other harmful substances, the world’s leading vendors of motor vehicles (MV) come back to development of electric vehicles (EV) as the most environmentally friendly transport. But EV has inadequate power reserve from one accumulators charge. One of the ways to increase it is to use additional environmentally friendly electrical energy sources, e.g., photovoltaic converter (PVC) batteries due to the increase in their efficiency. In order to improve aerodynamic, design and consumer properties, the world’s leading EV manufacturers pass from flat PVC battery to non-flat. Non-flat PVC batteries compared with flat have insufficient energy efficiency, which can be increased in several ways, including PVC battery segmentation. In scientific publications, there are no methods for calculating non-flat PVC batteries, which indicates the actuality of the research being conducted. Mathematical modeling of the EV power reserve depending on the season allows us to justify the actuality of segmenting the non-flat PVC batteries installed on the EV. Materials for the mathematical modeling of nonlinear interaction are obtained experimentally, the method of conducting experimental research is scientifically justified. As a result of the mathematical modeling, the dependences of EV power reserve on the season at different standard test cycles were obtained. The obtained dependences of the EV power reserve on the season allow us to assume the feasibility of segmenting the PVC batteries installed on the EV to increase the energy output and EV power reserve from one accumulators charge.

Grid-Forming Control for Solar PV Systems With Power Reserves

This paper presents a grid-forming control (GFC) scheme for two-stage photovoltaic (PV) systems that maintains power reserves by operating below the maximum power point (MPP). The PV plant in GFC mode behaves like a voltage source that supports the grid during disturbances in full or limited grid-forming mode as per the reserve availability. This is a model-free method that avoids the estimation of MPP power in real-time commonly done in the literature, which makes it simpler and more reliable. The proposed control also features an enhanced current limitation scheme that guarantees containment of the current overshoots during faults, which is not trivial in voltage-sourced GFC inverters. A thorough investigation is done, exploring various generation mixtures of synchronous machines (SM), GFC and grid-following (GFL) inverters, and all common disturbances, e.g., load change, faults and irradiance transients. The results show very favorable dynamic performance by the GFC inverters, far superior to GFL inverters and directly comparable to SMs. It is found that replacing SMs with GFC inverters may improve the frequency profile and terminal voltage during disturbances, despite losing out in the mechanical inertia and the strict inverter overcurrent limits.

Coordinated Frequency Regulation Using Solar Forecasting Based Virtual Inertia Control for Islanded Microgrids

Power system inertia helps the grid to maintain frequency stability. However, as photovoltaic (PV) generation continuously displaces synchronous generators (SGs) and reduces system inertia, it may result in system failure. Virtual inertia control (VIC) technology has drawn increasing attention because it enables PVs to increase system inertia by mimicking the characteristics of SGs. Energy sources are needed to implement the VIC strategy. Energy storage systems (ESS) can be used to provide such energy. However, the high-cost is still hindering its large-scale adoption. Although constant reserve power in PV has recently been proposed as an alternative for ESS, it can cause unnecessary power losses during the PV system working at a stable state. This paper proposes a forecasting-based VIC (FB-VIC) and coordinated reserve strategy. FB-VIC enables the PVs to serve as an alternative inertia supplier without using ESS. PV generation is pre-reserved based on the solar forecasting results, either at PV plant about to be shaded for local curtailment or other unshaded PV plants providing virtual inertia. The coordinated reserve strategy decides how much to reserve at the selected PV plant. It makes the system more robust to forecasting errors. The simulation results reveal that the proposed method can improve system inertia and suppress the frequency variation in a shorter time.

산업용 수용가의 최대 전력 수요저감에 관한 부하 이동 알고리즘 제안

Power demand of industrial consumers accounts for more than 55% of the total national demand quota, and power demand management measures are strongly required to mitigate the increase in power consumption in the industrial sector. In particular, problems such as insufficient power reserve ratio and large-scale blackouts occur in the power system due to high power consumption during peak periods such as the summer and winter seasons. In view of this, efficient load management and reduction of peak demand power are of importance. In this paper, we obtain predicted load data of industrial consumers via its historical load profile, based on this, we propose a load shifting algorithm to reduce the maximum power demand and basic cost. This is done by applying a load movement algorithm on the day-ahead predicted load data considering the facilities

Inertia and primary frequency modulation strategy for a doubly fed induction generator based on supercapacitor energy storage control

ABSTRACT Doubly fed wind turbines cannot respond to changes in grid frequency under maximum power point tracking control. The traditional deloading frequency control suffers from problems, such as low power generation efficiency, small speed adjustment range, and frequent starting of pitch angle control. An inertia and primary frequency modulation (FM) strategy for a doubly fed wind turbine based on supercapacitor energy storage control is proposed in this study. Virtual inertia and primary frequency adjustments are realized by supercapacitor control. Changing or increasing the additional control of the wind turbine is unnecessary. The proposed strategy can improve the disturbance resistance and self-stabilization of a single wind turbine. The capacity of the energy storage unit is optimally configured in accordance with the cost and charging/discharging efficiency of the actual supercapacitor module. Comparing and evaluating the economics of the primary FM scheme of an active power reserve provide a powerful economic advantage. Simulations and experiments show that inertial support, primary frequency adjustment capability, and power generation benefits are significantly improved compared with those in the conventional primary frequency control. This study provides new ideas for the modified inertia and primary FM function of a doubly fed wind turbine.

Effects of graded hypoxia during exhaustive intermittent cycling on subsequent exercise performance and neuromuscular responses.

This study examined the effect of graded hypoxia during exhaustive intermittent cycling on subsequent exercise performance and neuromuscular fatigue characteristics in normoxia. Fifteen well-trained cyclists performed an exhaustive intermittent cycling exercise (EICE 1; 15s at 30% of anaerobic power reserve interspersed with 45s of passive recovery) at sea level (SL; FiO2 ~ 0.21), moderate (MH; FiO2 ~ 0.16) and severe hypoxia (SH; FiO2 ~ 0.12). This was followed, after 30min of passive recovery in normoxia, by an identical exercise bout in normoxia (EICE 2). Neuromuscular function of the knee extensors was assessed at baseline, after EICE 1 (post-EICE 1), and EICE 2 (post-EICE 2). The number of efforts completed decreased with increasing hypoxic severity during EICE 1 (SL: 39 ± 30, MH: 22 ± 13, SH: 13 ± 6; p ≤ 0.02), whereas there was no difference between conditions during EICE 2 (SL: 16 ± 9, MH: 20 ± 14, SH: 24 ± 17; p ≥ 0.09). Maximal torque (p = 0.007), peripheral (p = 0.02) and cortical voluntary activation (p < 0.001), and twitch torque (p < 0.001) decreased from baseline to post-EICE 1. Overall, there were no significant difference in any neuromuscular parameters from post-EICE 1 to post-EICE 2 (p ≥ 0.08). Increasing hypoxia severity during exhaustive intermittent cycling hampered exercise capacity, but did not influence performance and associated neuromuscular responses during a subsequent bout of exercise in normoxia performed after 30min of rest.

Coordinated energy management strategy in scheme of flexible grid-connected hubs participating in energy and reserve markets

This paper uses the coordinated energy management strategy for different sources and storages in the framework of flexible grid-connected energy hubs that participate in the day-ahead (DA) energy and reserve markets. In the base problem, this method maximizes the difference between the expected revenue of hubs gained by selling energy and reserve power in the proposed markets and the expected cost of lost flexibility (COLF). Also, it is subject to linearized optimal power flow (LOPF) equations in the electricity, gas and district heating systems, as well as hub constraints including different sources, storages and reserve models. This problem contains uncertainties of load, market price, reserve requirement, renewable power and hub mobile storages parameters. Therefore, the hybrid stochastic/robust optimization (HSRO) is suitable to model these uncertain parameters and obtain robust capability for the hub to improve the system flexibility. Accordingly, the bounded uncertainty-based robust optimization (BURO) is used in this paper to model the uncertainty of hub mobile storages to achieve the hub robust potential in improving the system flexibility, and other uncertain parameters are modeled according to scenario-based stochastic programming (SBSP). Finally, the proposed strategy is implemented on a standard test system. The obtained numerical results confirm the capability of the suggested scheme in improving the economic status of sources and storages using the coordinated energy management strategy in the form of an energy hub, as well as enhancing economic conditions, operation, and flexibility of energy networks thanks to hubs for having access to optimal scheduling.

Hierarchical Voltage/VAR security boundaries and margin assessments in Multi-HVDC infeed systems

Operational security issues such as a lack of voltage/VAR support and cascading failures triggered by an initial fault present crucial challenges and issues in systems with multiple high-voltage direct current (HVDC) infeeds with both line-commutated converter (LCC) and voltage-source converter (VSC) links. Due to the complexity of the switching strategy for the filter banks in the converter stations, the modeling of the voltage control process inside converter stations is also complex; however, this complexity is not considered in the existing methods, leading to low calculation accuracy. Therefore, this paper proposes an approach based on hierarchical voltage/VAR security boundaries (HVVSBs) and margin assessments for multi-HVDC infeed systems to ensure high calculation accuracy and speed. The voltage/VAR control characteristics of LCC/VSC stations are appropriately formulated by means of a stepwise search method and boundary information, and an HVVSB-based method of dynamic reactive power reserve evaluation is proposed that is suitable for extreme scenarios. Finally, the proposed method is tested in a modified IEEE-118 system to verify its accuracy and effectiveness.

Smart Energy Bricks: Ti3C2@Polymer Electrochemical Energy Storage inside Bricks by 3D Printing

AbstractThree‐dimensional (3D) printing technology has a pronounced impact on building construction and energy storage devices. Here, the concept of integrating 3D‐printed electrochemical devices into insulation voids in construction bricks is demonstrated in order to create electrochemical energy storage as an integral part of home building. The low‐cost 3D‐printed supercapacitor (SC) electrodes are created using graphene/polylactic acid (PLA) filament in any desired shape such as 3D cylindrical‐ (3Dcy), disk‐ (3Ddc), and 3D rectangular‐ (3Drc) shaped electrodes. To obtain excellent capacitive performance, a Ti3C2@polypyrrole (PPy) hybrid is uniformly electroplated on the surface of 3D‐printed electrodes. These Ti3C2@PPy‐coated 3D‐printed electrodes exhibit outstanding electrical conductivity, capacitive performance, cycle life, and power density. The bricks themselves act as an excellent scaffold for electrochemical energy devices as they are electrically insulating, fire‐resistant, and contain substantial unused thermal insulation voids. A 3Drc Ti3C2@PPy SC is integrated into a real brick to showcase a smart house energy storage system that allows to reserve power in the bricks and use it as a power backup source in the event of a power outage in the elevator. This concept provides a platform for future truly smart buildings built from added value “smart brick” energy storage systems.

Optimal Sizing of Energy Storage System for Operation of Wind Farms Considering Grid-Code Constraints

Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also results in an imposition of penalties on the wind farm operators. Therefore, an operation strategy is developed in this study for optimizing the operation of wind farms using an energy storage system. This facilitates wind farms in fulfilling all the grid-code constraints imposed by the transmission system operators. Specifically, the limited power constraint and the reserve power constraint are considered in this study. In addition, an optimization algorithm is developed for optimal sizing of the energy storage system, which reduces the total operation and investment costs of wind farms. All parameters affecting the size of the energy storage systems are also analyzed in detail. This analysis allows the wind farm operators to find out the optimal size of the energy storage systems considering grid-code constraints and the local information of wind farms.

An optimal probabilistic spinning reserve quantification scheme considering frequency dynamic response in smart power environment

These frequency responses in tandem with spinning reserve are a prominent problem in the future smart grid environment due to the increase of non-dispatchable energy sources. However, this new environment allows incorporating new technologies, that is, distributed energy resource (DER), energy storage systems (ESSs), and shiftable loads, to prevent emergency situations and blackouts. This paper proposes a novel, energy reserve operational scheduling method for future smart grid frequency enhancement considering wind generation, ESSs, thermal generating units, shiftable loads, and power system frequency response characteristics. The proposed method divides the reserve into two different parts, that is, active power reserve, which is responsible for smoothing the frequency fluctuations due to load variations and the second part is essential to control the frequency after large disturbances. The spinning reserve required for safe operation of the power system is determined based on a reliability criterion, that is, total expected energy not supplied (TEENS). The proposed method aims to maintain the frequency response in a stable mode by incorporating active power reserve from both generation and demand-sides. IEEE 30-bus and RTS-96 systems are utilized to verify the proposed reserve scheduling methods using GAMS programming environment. The obtained results verify the superiority and usefulness of the proposed method over others.

Performance analysis of adaptive smart controllers for islanded microgrid

Abstract This paper presents implementation of control method for dual control of Voltage and Current control and Power sharing coupled with Demand Response for the islanded microgrid. These three controller viz Voltage and current controller, Power sharing controller and smart load controller while acting in unison can able to maintain long layoff from the connection requirement of the main grid. The paper uses state space inverter based generator model with close loop Voltage and Current control and Power sharing controller will enhance microgrid stability and transient response where smart load controller which uses state space model for voltage,current and Phase Locked Loop units to estimate reserve power available from smart load for better voltage and frequency regulation. Voltage current Controller and Power Sharing Controller will also assist the microgrid for smooth disconnection of microgrid from main grid while smart load controller will use its point of load voltage control for smooth islanding of microgrid. This control technique henceforth called tripartite control technique, compared with classical controller connected to microgrid in maintaining frequency, voltage with power sharing of the inverter driven by renewable generator. This paper investigate the operation performance issues of test Microgrid using Tripartite Control Technique. Simulation results indicate close approximation with experimental results

Profit evaluation inclusive of reserve pricing for renewable-integrated GENCOs

Abstract Under the deregulated market scenario, the electric power industry is rapidly getting transformed due to integration of increasing renewable generation. Profit maximization has always been of highest priority for all the stakeholders. The generation planning problem is an important problem in the operation and planning of power systems which is required to be solved to accomplish the maximum profit. The individual GENeration COmpanies (GENCOs) are envisioning their most profitable Unit Commitment (UC) in the light of the available forecasts of availability of solar and wind power, energy prices and reserve prices during a given scheduling period. This paper presents a UC strategy for GENCOs’ profit with a generation portfolio comprising thermal generation, wind generation, and solar PV generation in different combinations. Priority List Method (PLM) and Modified Particle Swarm Optimization (PSO) with Time-Varying Acceleration Coefficients (PSO-TVAC) solution technique is deployed on the MATLAB platform. The aim is to maximize the profit while satisfying the load demand together with maintaining sufficient reserve at each hour. Sensitivity analysis of profit has also been carried out to showcase the impact of different pricing techniques, different parameters chosen and the different bidding prices for the power dispatched as well as for the reserve power maintained. The observations that emerged through the presented solution model may help develop an insight to the GENCOs to gain maximum profits.

Novel Aqueous Zinc–Halogenate Flow Batteries as an Offspring of Zinc–Air Fuel Cells for Use in Oxygen‐Deficient Environment

Autonomous and portable electronic devices require cheap energy storage units of ever‐increasing power and energy densities. Zinc/halogenate flow battery is proposed as a new type of reserve or emergency power supply unit. The battery uses a mechanically rechargeable zinc anode in contact with neutral aqueous salt electrolyte, cation‐exchange membrane, and a carbonaceous flow through cathode, at which aqueous acidified halogenate is reduced to halide in a six‐electron process. A new multielectron oxidizer, aqueous iodate, that can be used in other electrochemical power sources, is introduced. It is shown that iodate can be readily reduced in acidic media at cheap carbonaceous electrodes. Electrochemical experiments with stationary and rotating disk glassy carbon electrodes reveal that in acidic aqueous electrolytes reduction of iodate can be as fast as earlier studied reduction of bromate. Theoretical energy densities per reactants of Zn/bromate and Zn/iodate batteries are 1.2 and 1.45 kWh L−1, respectively. Area‐specific power of the single cells of these batteries reaches 0.57 W cm−2 at 50 °C.

Feature-Selection and Mutual-Clustering Approaches to Improve DoS Detection and Maintain WSNs' Lifetime.

Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algorithm, to improve anomaly detection efficiency over a WSN’s lifetime. Furthermore, the use of feature selection techniques with machine learning algorithms in examining WSN node traffic and the effect of these techniques on the lifetime of WSNs was evaluated. The evaluation results showed that the Water Cycle (WC) feature selection displayed the best average performance accuracy of 2%, 5%, 3%, and 3% greater than Particle Swarm Optimization (PSO), Simulated Annealing (SA), Harmony Search (HS), and Genetic Algorithm (GA), respectively. Moreover, the WC with Decision Tree (DT) classifier showed 100% accuracy with only one feature. In addition, the CH_Rotations algorithm improved network lifetime by 30% compared to the standard LEACH protocol. Network lifetime using the WC + DT technique was reduced by 5% compared to other WC + DT-free scenarios.