Energy Station Research Articles

Risk Assessment for Energy Stations Based on Real-Time Equipment Failure Rates and Security Boundaries

In the context of China’s 2020 dual carbon goals of peak CO2 emissions by 2030 and carbon neutrality by 2060, the security of multi-energy systems is increasingly challenged as clean energy continues to be supplied to the system. This paper proposes a risk assessment and enhancement strategy for distributed energy stations (DESs) based on a security boundary. First, based on the coupling relationship between different energy sources and combining the mutual support relationships between different pieces of equipment, a security boundary for DESs was constructed. Second, based on the characteristics of different sources of equipment failure, the real-time failure probabilities of equipment and pipelines were calculated in order to obtain the security risks of DES operation states based on the security boundary. Finally, for equipment and pipelines at high risk, an economic security enhancement strategy is proposed, and the Pareto solution set is solved using a multi-objective algorithm. The analysis shows that the proposed method can effectively quantify the security risks of energy systems in real time, and the proposed enhancement strategy takes into account both economics and system security.

UAV‐assisted multi‐hop D2D relaying for communication in large disaster area

SummaryAn unmanned aerial vehicle (UAV)‐assisted communication is a promising technique for enabling ground users in a non‐functional area (NFA) or disaster area to communicate. All the base stations in the disaster area may be partially or fully damaged due to the natural calamity. Device‐to‐device (D2D) communication can be a viable solution for immediate connection between users in an NFA. We propose a UAV‐assisted multi‐hop D2D communication following a hybrid power‐time switching (PTS) in this paper. Moreover, a D2D user of a cluster can communicate with another D2D user in a different cluster through UAVs. However, D2D users can harvest energy from their respective ad hoc energy stations and forward the information to the nearby D2D user following a hybrid PTS‐based strategy. We propose a time frame for the same and show a node‐based energy harvesting strategy. The expressions of outage probability, throughput, end‐to‐end energy consumption, and energy efficiency are developed for the Rician and Nakagami‐m faded channel. The impact of several network parameters such as energy harvesting factor, energy harvesting efficiency, and fading parameter on the network performance is also indicated.

Impact of Active Frequency Support Control of Photovoltaic on PLL-Based Photovoltaic of Wind-Photovoltaic-Thermal Coupling System

The coupling systems formed by wind power, photovoltaics, and thermal generators possess broad application prospects. To build grid-friendly renewable energy stations, active frequency support control (AFSC) is adopted. There are potential risks on subsynchronous oscillation (SSO) dominated by the phase-locked loop (PLL) based photovoltaic considering AFSC of photovoltaic. The impact of AFSC on PLL dominant SSO mode (PLL-SSOM) of the photovoltaic is still not clear. To address that, this paper firstly observes the SSO characteristics of the wind-photovoltaic-thermal coupling system (WPTCS) with AFSC. Considering the second-order rotor motion equation of the thermal generator and ignoring the dynamics of DFIG, a simplified model of WPTCS with AFSC is established. Compared with the detailed model, the correctness of the simplification is verified. Based on that, the transfer function of additional AFSC is derived. The study reveals that the root cause of the impact of AFSC on PLL-SSOM is that AFSC will make the synchronous torque and damping torque corresponding to the PLL-SSOM transform each other. Finally, the frequency-domain and time-domain simulation results verify the correctness of the model simplification and theoretical analysis.

Global path planning for airport energy station inspection robots based on improved grey wolf optimization algorithm

Global path planning is one of the key technologies for airport energy station inspection robots to achieve autonomous navigation. Due to the complexity of airport energy station buildings with numerous mechanical and electrical equipment and narrow areas, planning an optimal global path remains a challenge. This paper aimed to study global path planning for airport energy station inspection robots using an improved version of the Grey Wolf Optimizer (IGWO) algorithm. Firstly, the initialization process of the Grey Wolf Optimizer algorithm selects several grey wolf individuals closer to the optimal solution as the initial population through the lens imaging reverse learning strategy. The algorithm introduces nonlinear convergence factors in the control parameters, and adds an adaptive adjustment strategy and an elite individual reselection strategy to the location update to improve the search capability and to avoid falling into local optima. Benchmark function and global path planning simulation experiments were carried out in MATLAB to test the proposed algorithm’s effectiveness. The results showed that compared to other swarm intelligent optimization algorithms, the proposed algorithm outperforms them in terms of higher convergence speed and optimization accuracy. Friedman’s test ranked this algorithm first overall. The algorithm outperforms others in terms of average path length, standard deviation of path length, and running time.

Optimal design method and benefits research for a regional integrated energy system

Regional integrated energy systems (RIES) have garnered increased attention because they highly utilize renewable energy, comprehensive efficiency, and flexible operation. However, the current research on RIESs is mainly based on burning natural gas and supplemented by renewable energy, which will consumes much primary energy and generates corresponding carbon emissions. Therefore, a RIES contained various renewable energy sources and station energy sharing was constructed in this paper. Both the collaborative optimization model, which considered the operating parameters and system configuration, and the hierarchical optimization model, which optimizes the equipment configuration at the upper layer and the operational parameters at the underlayer, were constructed, respectively. Taking a multi-function low-carbon park as an example, the isolated integrated energy system (IIES) and RIES performances were explored. Finally, the operation cost, carbon emission, and interactive power in the separated production system, IIES and RIES were analyzed and discussed from a long-short time scale perspective. The results showed that the carbon emission, interactive power, and energy supply cost of the RIES's unit area are 7.62 kg/m2, 10.07 kWh/m2, and 40.55 CNY/m2, respectively. Long time scale perspective (Years or months), RIESs could significantly reduce carbon emissions and interactive power. However, on a short time scale viewpoint (Hours), the system's instantaneous energy conservation and carbon reduction effect was general; meanwhile, the maximum grid-connected power in IIES and RIES was 2617.7 and 2712.0 kW, respectively.

New multi-energy sources coupling a low-temperature sustainable central heating system with a multifunctional relay energy station

Due to short cost-effective heat transportation distance, the existing geothermal heating technologies cannot be used to develop the deep hydrothermal type geothermal fields situated far away from urban area. To solve the problem, a new multi-energy source coupling a low-temperature sustainable central heating system with a multifunctional relay energy station is put forward. As for the proposed central heating system, a compression heat pump integrated with a heat exchanger in the heating substation and a gas-fired water/lithium bromide single-effect absorption heat pump in the multifunctional relay energy station are used to lower return temperature of the primary network step by step. The proposed central heating system is analyzed by using thermodynamics and economics, and matching relationships between design temperature of return water and main line length of the primary network are discussed. The studied results indicate that, as for the proposed central heating system, the cost-effective main line length of the primary network can approach 33.8 km, and the optimal design return temperature of the primary network is 23 ℃. Besides, annual coefficient of performance and annual exergy efficiency of the proposed central heating system are about 3.01 and 42.7%, respectively.

Modeling and Analysis of Aluminum Cable Joints in Steady State for New Energy Stations

Compared with copper cables, aluminum cables have certain advantages in engineering costs and transportation costs, but have installation difficulties in the application process. However, limited by the manufacturing process, installation technology, and operating conditions, the intermediate joint of the aluminum cable is prone to failures such as insulation deterioration caused by abnormal temperature. The temperature of the core of the conductor in a steady state in the cable joint is the most direct and effective physical quantity, which can reflect the operating state. So modeling and analysis of the aluminum cable joint, as well as the study of its internal temperature change mechanism and influencing factors, are to improve the process and installation level of the aluminum cable joint and to develop the basis of the corresponding temperature monitoring system. In this paper, the thermal conduction mechanism of aluminum cable joints in a steady state is analyzed by using the thermal circuit theory. Then, the thermal circuit model of aluminum cable joints in a steady state based on the equivalent thermal circuit model and its parameter calculation method are proposed. By building an experimental platform, the validation experiment finally proved the accuracy of the method proposed in this paper.

Energy-efficient task offloading and trajectory planning in UAV-enabled mobile edge computing networks

In order to meet the double-sided challenges brought by the shortage of computation resources and energy of users, we investigate in this paper the optimization of energy efficiency (EE) in an unmanned aerial vehicle (UAV)-assisted wireless network, where UAV is functioned as a flying energy station and edge server to provide charging and computing services for ground users. We aim to maximize the average EE of the mobile edge computing network by the joint design of user transmit power, user computing frequency, UAV transmit power, bandwidth allocation, and UAV trajectory planning under strict energy and power constraints. In order to solve such challenging problem, we first elaborately construct a Markov decision process to model task offloading and resource allocation by learning from past experiences. Then, an average EE maximization method relying on deep reinforcement learning (DRL) is designed to efficiently adjust task offloading policy, where the policy of agent can be gradually improved by interacting with the environment and collecting the experience for learning. Finally, the EE-maximization proximal policy optimization (EE-PPO) algorithm is proposed to train the DRL agent and thereby solve this optimization problem. Numerical results are given to indicate that the proposed EE-PPO method has the properties of both fast convergence and well performance.

Distributed Shared Energy Storage Double-Layer Optimal Configuration for Source-Grid Co-Optimization

Shared energy storage is an energy storage business application model that integrates traditional energy storage technology with the sharing economy model. Under the moderate scale of investment in energy storage, every effort should be made to maximize the benefits of each main body. In this regard, this paper proposes a distributed shared energy storage double-layer optimal allocation method oriented to source-grid cooperative optimization. First, considering the regulation needs of the power side and the grid side, a distributed shared energy storage operation model is proposed. Second, a distributed shared energy storage double-layer planning model is constructed, with the lowest cost of the distributed shared energy storage system as the upper-layer objective, and the lowest daily integrated operation cost of the distribution grid-distributed new energy stations as the lower-layer objective. Third, a double-layer iterative particle swarm algorithm combined with tide calculation is used to solve the distributed shared energy storage configuration and distribution grid-distributed new energy stations’ economic operation problem. Finally, a comparative analysis of four scenarios verifies that configuring distributed shared energy storage can increase the new energy consumption rate to 100% and reduce the net load peak-valley difference by 61%. Meanwhile, distributed shared energy storage operators have realized positive returns.

Photovoltaic-battery powered bike share stations are not necessarily energy self-sufficient

Many cities use solar photovoltaic (PV) panels to power off-grid bike share stations to provide sustainable transportation. When a station's energy demand for operating the station’s kiosk and docks exceeds the PV panel's supply, the battery can be depleted, requiring manual battery replacement to avoid service disruption. However, existing research on siting, modeling, or assessing the environmental impacts of bike share stations has not accounted for spatially variable solar PV potential and energy usage. This study addresses this gap to analyze the performances of PV-battery systems for bike share stations and evaluates strategies to improve their energy independence, sustainability, and system reliability. Using Chicago’s Divvy bike share system as a case study, we simulated the battery charging, discharging, and replacements, and measured their performances with three metrics: energy self-sufficiency level, energy payback time (EPBT), and station downtime. We found that PV energy alone is insufficient to meet all energy needs of bike share stations, with the average energy self-sufficiency levels being 56%. Additionally, relying solely on battery replacement during rebalancing operations was insufficient to maintain stations' operational status. On average, bike share operators need to manually replace a station’s batteries 72 times a year. Furthermore, the current PV panels for most stations are sized too small. Increasing panel sizes could reduce most stations' downtime and increase their self-sufficiency without significantly affecting EPBT. The study highlights the need for bike share system modeling and operation planning to account for battery replacement needs and demonstrates the importance to evaluate smaller yet large-scale street-level PV applications. The modeling framework presented in this study can also be extended to examine other smaller PV-battery systems similar to bike stations.

Integrated Energy Station Optimal Dispatching Using a Novel Many-Objective Optimization Algorithm Based on Multiple Update Strategies

Regarding the need to decrease carbon emissions, the electric vehicle (EV) industry is growing rapidly in China; the charging needs of EVs require the number of EV charging stations to grow significantly. Therefore, many refueling stations have been modified to integrated energy stations, which contain photovoltaic systems. The key issue in current times is to figure out how to operate these integrated energy stations in an efficient way. Therefore, an effective scheduling model is needed to operate an integrated energy station. Photovoltaic (PV) and energy storage systems are integrated into EV charging stations to transform them into integrated energy stations (PE-IES). Considering the demand for EV charging during different time periods, the PV output, the loss rate of energy storage systems, the load status of regional grids, and the dynamic electricity prices, a multi-objective optimization scheduling model was established for operating integrated energy stations that are connected to a regional grid. The model aims to simultaneously maximize the daily profits of the PE-IES, minimize the daily loss rate of the energy storage system, and minimize the peak-to-valley difference of the load in the regional grid. To validate the effectiveness of the model, simulation experiments under three different scenarios for the PE-IES were conducted in this research. Each object weight was determined using the entropy weight method, and the optimal solution was selected from the Pareto solution set using an order-preference technique according to the similarity to an ideal solution (TOPSIS). The results demonstrate that, compared to traditional charging stations, the daily revenue of the PE-IES stations increases by 26.61%, and the peak-to-valley difference of the power load in the regional grid decreases by 30.54%, respectively. The effectiveness of PE-IES is therefore demonstrated. Furthermore, to solve the complex optimization problem for PE-IES, a novel multi-objective optimization algorithm based on multiple update strategies (MOMUS) was proposed in this paper. To evaluate the performance of the MOMUS, a detailed comparison with seven other algorithms was demonstrated. These results indicate that our algorithm exhibits an outstanding performance in solving this optimization problem, and that it is capable of generating high-quality optimal solutions.

P-791 Supplementation of mitochondria from endometrial mesenchymal stem cells (EnMSCs) improves oocyte quality in aged mice

Abstract Study question To improve the quality of aging oocytes by supplementing the mitochondria from endometrial mesenchymal stem cells (EnMSCs) via microinjection. Summary answer Supplementation with EnMSC-derived mitochondria can improve the quality of oocytes and promote embryo development in aging mice. What is known already Maternal aging is one of the major causes of reduced ovarian reserve and low oocyte quality in elderly women. Decreased oocyte quality is the main cause of age-related infertility. Mitochondria are multifunctional energy stations that determine the oocyte quality. The mitochondria in aging oocytes display functional impairments with mtDNA damage, which leads to reduced competence and developmental potential of oocytes. To improve oocyte quality, mitochondrial supplementation is carried out as a potential therapeutic approach. However, the selection of suitable cells as the source of mitochondria remains controversial. Study design, size, duration Study design: Eight-month-old ICR mice were purchased and then were further raised to ten months of age for use in the experiments. EnMSCs were stably cultivated and oocytes were extracted from ten-month-old ICR mice. Study size: About 300 GV oocytes and 134 MII oocytes were counted . 80 fertilized oocytes were transplanted into the fallopian tubes of surrogate mothers. Study duraton: About one half a year. Participants/materials, setting, methods Participants:ten-month-old ICR mice. Setting and methods: We cultivated EnMSCs from aged mice and extracted mitochondria from EnMSCs. And then GV oocytes were supplemented with mitochondria via microinjection. To further assess the effects of mitochondrial supplementation on embryo development, MII oocytes from aging mice were fertilized by ICSI combining EnMSCs mitochondria microinjection.To test whether mitochondrial supplementation could improve in vivo embryo development in aging mice, embryo transplantation was performed after mitochondrial microinjection combined with ICSI. Main results and the role of chance In this study, we found that the mitochondria derived from EnMSCs could significantly improve the quality of aging oocytes.Supplementation with EnMSC mitochondria significantly increased the blastocyst ratio of MII oocytes from aging mice after intracytoplasmic sperm injection (ICSI). We also found that the birth rate of mitochondria-injected aging oocytes was significantly increased after embryo transplantation. Limitations, reasons for caution Microinjection into oocytes was invasive and some oocytes died after microinjection. The ability of this method to improve oocyte quality was limited because the MII rate of oocytes after mitochondria supplementation was 35.65±1.75% while the rate of oocytes from 6–8 weeks of mice in a previous study was nearly 80%. Wider implications of the findings For clinical treatment, the EnMSCs can be obtained from the patient's own menstrual blood as the sources of mitochondrial supplementation. A noninvasive procedure for cell extraction ensures safety, and the findings of this work might provide a valuable strategy for patients with declining oocyte quality due to aging. Trial registration number Not applicable

Pricing method of shared energy storage bias insurance service based on large number theorem

Under the goal of “double carbon”, energy storage is gradually recognized by the society as a means to adjust the output deviation of new energy sources. However, the development of energy storage industry is limited due to the high cost and unclear revenue model of energy storage batteries. Based on this, this paper proposes a business model in which shared energy storage operators provide bias insurance services for new energy sources. Firstly, based on the perspective of commercial insurance, the business model of the shared energy storage operator providing deviation insurance service is designed; secondly, based on the law of large numbers and the actuarial theory of insurance; and finally, the validity of the model is verified through calculation examples, and the feasibility of the proposed business model is also proved. The research results show that compared with the installed capacity of shared energy storage deviation insurance mode reduces 81.57 % compared with new energy storage, and the insurance cost of unit installed capacity of new energy station saves 71.07 % compared with the cost of self-built energy storage cost and deviation assessment cost, which greatly improves the energy storage utilization efficiency and the economic benefits of energy storage operators. The insurance, a financial product explored in this paper, enriches the profit model of energy storage, provides a feasible path for energy storage investors to lock in profits in advance, helps to stimulate the enthusiasm of energy storage investment, and promote the development of China's new energy and energy storage industry.

Distributed bi-level optimal power flow calculation for SVSM interval of integrated transmission and distribution networks considering the uncertain renewables

To accurately and efficiently calculate the static voltage stability margin (SVSM) interval of integrated transmission and distribution networks (ITDNs) considering the uncertain fluctuation of renewables, a distributed bi-level optimal power flow (OPF) calculation method based on the alternating direction method of multipliers for the SVSM interval of ITDNs is proposed in this paper. Due to the different structure characteristics of transmission network (TN) and distribution network (DN), a hybrid node-branch OPF method for calculating the SVSM of ITDNs is proposed, which has better convergence than the traditional node OPF method. Different reactive power-voltage control modes of renewable energy stations (RESs) are also considered in the calculation. Considering the uncertain fluctuation of RESs, two distributed bi-level OPF models for calculating the upper and lower bounds of the SVSM interval of ITDNs are established. Based on the alternating direction method of multipliers, the SVSM interval bounds of ITDNs can be obtained by solving the sub-optimization models and transmitting the boundary coupling variables and the load growth parameter between the TN and multiple DNs iteratively until the given convergence criterion is satisfied. Test results on two ITDNs, the modified IEEE 39–33 & 69 bus system and an actual 2285-bus ITDNs, demonstrate the high computation accuracy and efficiency of the proposed distributed bi-level OPF method compared with other calculation methods.

Optimization of the multi-level steam production and supply in industrial parks

Steam is an important medium for energy transmission in industrial parks. For providing steam to multiple users, it is key to determine the optimal number of steam levels in the design of steam system. With the increasing number of steam levels, the energy demand and supply can be better matched but the investment of steam pipeline network increases. In this paper, this trade-off is solved by a two-stage method. In the first step, a mixed-integer nonlinear programming (MINLP) model is established to minimize the total cost of the steam system of the industrial park, while a simple pipeline network optimization model is involved. The optimal scheme of steam production including the number of steam levels can be obtained automatically. In the second step, GeoSteiner algorithm is used for solving Rectilinear Steiner Minimum Tree (RSMT) model to further optimize the pipeline network separately. In a case study, the optimal number of steam levels is 3. The total annual cost (TAC) of the optimal steam system is 11.4%, 5.28%, and 1.43% lower than the schemes with the lowest pipeline network cost (1 level of steam), the best matching between heat supply and heat demand (6 levels of steam), and the largest electricity generation capacity (4 levels of steam), respectively. The sensitivity analysis indicates that the overall heat load required by consumers and the distance between the energy station and consumers can make a difference to the optimal number of steam levels.

A novel evaluation method of the hosting capacity of multiple renewable energy stations accessed into a power system

Along with the rapid development of renewable energy (RE), a critical issue regarding the adequate accommodation of RE should be given careful attention. This paper proposes a novel evaluation method of the hosting capacity of multiple renewable energy stations (MRES) accessed into the power system. Firstly, the node-system short-circuit ratio is specially defined, and the impacts of accommodating the MRES on the node voltage strength are considered. Then, the evaluation model is established by comprehensively considering the MRES hosting capacity and the node-system short-circuit ratio, and the system power and node voltage constraints are implemented. Furthermore, the improved particle swarm optimization (IPSO) algorithm is adopted to address the designed model-solving problem. Using MATLAB, the effectiveness of the proposed evaluation method is validated in the IEEE-39 node system with MRES. The computation result of the objective function proves the suggested IPSO algorithm outperforms the traditional PSO in finding the optimal solution for the MRES hosting capacity in the system. The theoretical and numerical analysis methods are consistent, and the findings show that the proposed approach can obtain the maximum allowable capacity of the MRES while ensuring the safe and stable operation of the system.

Research on Optimization Method of Integrated Energy System Network Planning

The development of an integrated energy system (IES) is conducive to promoting the transformation of the energy system and helping to achieve the ‘double carbon’ goal in China. The IES integrates cooling, heating, electricity, gas, and other energy resources, which is significantly more difficult than single energy network planning. This paper systematically sorts out the process of IES network planning and proposes an improved methodology. Firstly, the bottom-up dynamic multiple-load forecasting method of 8760 h a year is proposed as the basis of system configuration and capacity selection. Subsequently, a planning method for energy station location and route optimization using the Dijkstra algorithm is constructed by applying the P-median optimization model. Finally, when optimizing the capacity allocation of the IES, the complementary characteristics of natural gas, electricity and heat, as well as the corresponding energy demand characteristic, have been fully considered, so that the optimization objectives can be reasonably determined. Through the actual calculation, it is found that the optimization method proposed in this paper can reduce the construction cost of the network by 41%. The work combines the process of energy network planning and capacity configuration of IES, which provides a simple, easy and economical solution for IES planning in new areas.

Planning and design of regional integrated energy station considering load growth mode

Planning and design of regional integrated energy station considering load growth mode

An energy storage allocation method for renewable energy stations based on standardized supply curve

The goal of carbon emission peak and carbon neutrality requires China to vigorously develop renewable energy. However, renewable energy has obvious randomness and volatility. Therefore, it is necessary to configure energy storage systems for renewable energy stations to ensure the safe and stable operation of power systems. Given the problem of energy storage system configuration in renewable energy stations, it is necessary to consider the system load characteristics and design appropriate principles to formulate planned output curves for renewable energy stations, so that the joint output curve of renewable energy and energy storage system can match the system load curve as much as possible, which will reduce the system peak shaving pressure and promote the utilization of renewable energy. This paper first considers the impact of renewable energy stations with the different installed scales on the power system and designs the standardized supply curves differentially, and defines the supply curve deviation index to characterize the difference between the renewable energy–energy storage system joint output curve and the standardized supply curve. Then, to minimize energy storage system investment costs and supply deviation costs, an optimization model for energy storage system configuration in renewable energy stations is established, and output deviation control constraints are set to ensure that the operation of energy storage systems conforms to actual conditions. Finally, case studies analyze the energy storage system configuration results and the typical scenario operation results of a single renewable energy station and a renewable energy power generation base, which verify the rationality and effectiveness of the method proposed in this paper.

Upper limb functional testing: Normative data in overhead and non-overhead athletes

Materials are very crucial and important factor in different industrial processes. Austenitic treated steel utilized overall in different significant businesses like synthetic, petrochemical, thermal energy station and vehicle dependent principally upon their corrosion opposition yet additionally for their formability, their solidarity, and their properties at outrageous temperatures. In any case, the expense of such steel is a significant worry to the ventures as the expense of austenitic treated steel is expanding step by step, because of the deficiency of its constituent Ni (Nickel). Thus, to keep away from this issue, the businesses could utilize a blend weld of two Steel having lower level of Ni. which would require right decision of filler material, welding method for an imperfection free sound weld. This paper endeavors an introductory survey of the most common way of joining significant contrasts among austenitic and ferritic Tempered Steel, its microstructure and corrosion opposition properties and mechanical properties in different Cycles and blends.