Energy conversion efficiency constitutes a critical parameter in the operation of charging facilities and serves as a pivotal focus of research in the domain of remote metering for these facilities. However, currently, the primary method for evaluating the energy efficiency of charging modules remains the direct method. This approach is challenging to measure indirectly due to the complex circuit structure and the characteristics of the components involved. An indirect measurement method for assessing the efficiency of charging modules based on grey box theory is proposed in this paper. Firstly, an accurate calculation model is established through the analysis of component losses. Next, the parameters of the complex model are processed using a parameter fusion method, resulting in an indirect measurement model of efficiency that utilizes the voltage and current outputs of the charging module as variables. Finally, the Levenberg-Marquardt (L-M) algorithm is employed to solve for the model parameters. The experimental verification of typical 15 kW and 20 kW charging modules demonstrates that the error of this method is less than 1.3% under low load conditions, and less than 0.5% under high load conditions. The indirect measurement method proposed in this paper exhibits high measurement accuracy and can be directly applied to most standard charging modules. It possesses good universality and can effectively meet the indirect measurement requirements for the conversion efficiency of charging modules.

With the increasing penetration of wind power, flexible ramping resources are becoming increasingly critical in power systems. Hydrogen energy storage (HES), due to its system-level energy regulation capability, can be deeply integrated with wind farms to form a wind–hydrogen integrated energy system (WH-IES), enabling the system to provide flexible ramping products (FRPs). Based on this, this paper investigates an optimal bidding strategy for a WH-IES participating in both the energy and ramping markets. To accurately characterize the internal operations and market interactions of the system, a physical model incorporating the dynamic hydrogen production efficiency of proton exchange membrane electrolyzers (PEMELs) is developed. Meanwhile, the prosumer identity of the WH-IES in the ramping market is systematically modeled, explicitly capturing the ramping demand induced by wind power fluctuations and the ramping capability provided by the hydrogen storage system, as well as their impact on the market response of the WH-IES. On this basis, a bi-level bidding strategy is established to simulate the strategic interaction between the WH-IES and the electricity market, and the problem is reformulated as a mathematical program with equilibrium constraints using Karush–Kuhn–Tucker conditions and strong duality theory for efficient solution. Case studies on a modified IEEE 6-bus system demonstrate that the proposed strategy effectively captures market interactions, and considering both the dynamic efficiency of PEMELs and the dual identity in the ramping market significantly enhances system profitability and market stability, providing a theoretical reference for the market-oriented operation of large-scale WH-IES.

With the continuous improvement of the living standards and quality of urban residents, the electricity and energy consumption in residential substation areas have maintained a rapid growth rate. Carbon peaking in residential substation areas has become an urgent issue to be studied. In this paper, a direct carbon emission model of residential substation areas is established. Then a carbon emission reduction model is proposed with the help of three technologies such as building new photovoltaic systems, increasing the proportion of domestic electrification, and reducing power grid loss. A simulation studies the impact of various carbon reduction technologies on carbon emissions in residential substation areas under different scenarios. The results show that: 1. under the current condition of slowing population growth, when the growth rate of per capita energy consumption is comparable to the reduction rate of regional carbon emission factors, carbon peaking in residential substation areas can be achieved by applying certain carbon reduction technologies in 2030; 2. under the current carbon emission factors, replacing gas with electric energy for domestic use cannot achieve carbon emission reduction; 3. among various carbon reduction technologies in residential substation areas, the effect of constructing photovoltaic power supply areas is the most obvious. Therefore, this paper suggests that to achieve fast carbon peaking in residential substation areas, we should reduce the electricity-carbon factor of the regional power grid, and vigorously carry out photovoltaic power supply construction.

Wireless charging technology provides a convenient and safe method for electric vehicles. To meet the needs of commercial operations, it is essential to accurately measure the active power at the transmitter end of the wireless charging system. However, due to the high-frequency and high-voltage, measuring the voltage at the transmitting coil is challenging. In response to this issue, this paper focuses on the bilateral LCC compensation network and analyzes the harmonic components of the current and voltage at transmitting coil. It derives the voltage relationship between compensation capacitor and the transmitting coil and indirectly measure voltage at transmitting coil, finally proposing an active power calculation method for the transmitting coil. An experimental prototype of a wireless charging system utilizing bilateral LCC compensation is built. Simulations and experiments verify that the active power consumed by the transmitting coil is mainly the fundamental component, and the impact of the sampling frequencies and power levels on the measurement accuracy is discussed.

With the gradual maturity of wireless charging technology for electric vehicles, wireless charging piles have gradually been installed for trial operation. Different from the conductive charging piles, there is still a lot of controversy in the energy measurement of electric vehicle wireless charging systems. Based on the characteristics of the separation of the primary and secondary sides of the electric vehicle wireless charging system, this paper analyzes the characteristics of the electric vehicle wireless charging system and the impact on measurement. This paper discusses the two billing modes of the transmitter and receiver. And based on these two billing modes, this paper selects four different measurement points for feasibility analysis, gives the advantages and disadvantages of different measurement point selection. This paper discusses and summarizes the impact on the actual operation of electric vehicles. The research results show that the measurement of electrical energy at the transmitting coil is a more suitable measurement scheme for the commercial operation of the charging stations, but at the same time, different measurement methods can be used in different applications to meet to the current needs.

Traditional thermal power units are continuously replaced by renewable energies, of which fluctuations and intermittence impose pressure on the frequency stability of the power system. Electrolytic aluminum load (EAL) accounts for large amount of the local electric loads in some areas. The participation of EAL in local frequency control has huge application prospects. However, the controller design of EAL is difficult due to the measurement noise of the system frequency and the nonlinear dynamics of the EAL’s electric power consumption. Focusing on this problem, this paper proposes a control strategy for EAL to participate in the frequency control. For the controller design of the EAL system, the system frequency response model is established and the EAL transfer function model is developed based on the equivalent circuit of EAL. For the problem of load-side frequency measurement error, the frequency estimation method based on Kalman-filtering is designed. To improve the performance of EAL in the frequency control, a fuzzy EAL controller is designed. The testing examples show that the designed Kalman-filter has good performance in de-noising the measured frequency, and the designed fuzzy controller has better performance in stabilizing system frequency than traditional methods.

为提高综合能源系统的能源利用效率,提出一种考虑能效的多目标优化模型与求解方法.首先,分析影响综合能源系统的能源流动环节效率的因素.然后,以运行成本最低为目标建立经济性目标函数,以能源利用效率最优为目标建立能效目标函数,采用加权系数法将多目标优化转化为单目标优化.最后,采用模型预测控制进行优化调度,设立仅考虑单一目标与考虑多目标优化多种场景.算例表明,所建立的模型能够引导综合能源系统对能源进行合理利用,通过经济性目标与能效目标的优化调度提升综合能源系统的能源利用效率.

According to the change of the characteristics of the power grid, the dispatching space of the traditional load adjustment resources is getting smaller, and it is necessary to effectively expand the adjustment resources of the power grid to realize the coordinated mode of source-load interaction. Based on the current structure of the smart grid dispatching control system, this paper proposes a technical framework for the participation of adjustable load resource in power grid regulation, and builds a three-level business system of Regulation agency-Aggregator-Load resource, which can effectively realize the real-time interaction of data of monitoring, control and marketing between regulation agency and aggregators and promote the power of the load resource cluster continuously adjusted to participate in the scheduling optimization of the entire power grid through the function of automatic generation control.

随着电力竞争市场的发展与完善,电网利益主体逐步走向多元化,用户主动参与电网互动的背景下,开展用户用电行为研究具有重要意义.提出了一种基于家用电器特性的居民用电行为优化模型,首先,开展了居民家用电器的用电特性分析,对用户用电设备的使用效用和可调度潜力进行了研究,实现了典型家庭响应能力的评估;然后建立了计及用户舒适度的居民家用电器综合管理优化模型,该模型以使用时间期待、使用效果期待和电费变动期待为优化目标,以家用电器的使用和调控存在时间为约束条件;最后,基于家庭典型案例进行了算例测试,结果验证了模型的经济性与有效性.

At present, the potential analysis of adjustable load resources is mostly based on refined model to describe its demand and regulation ability, and less consider the load data drive and the correlation within the data. Accurate and effective classification of different types of adjustable load resources by historical load data, and then considering the characteristics of adjustable load, accurate prediction can effectively improve the accuracy of load potential calculation. An adjustable load power prediction method ( CK-MGRU-AT ) based on improved Canopy and K-Medoids two-level clustering, multi-channel gate recurrent unit ( MGRU ) and attention mechanism ( AT ) are proposed in this paper. Firstly, the improved Canopy algorithm is used to obtain the cluster center samples of various types of adjustable resources. Then the load data with similar characteristics are aggregated into a cluster by K-Medoids algorithm, which makes GRU more conducive to extracting the time characteristics of load data. Finally, the MGRU-AT model is used to extract the time characteristics of each cluster, and it is finally mapped to the power prediction outputs of different types of adjustable loads through the full connection layer. In order to verify the advantages of the proposed model ( CK-MGRU-AT ) in the stability of prediction accuracy, this paper uses the historical load data of industrial and commercial users in a typical region for experimental analysis. The results show that the proposed model reduces the average absolute error at least 0.0003, the mean square error 0.0149, and increases the R 2 index at least 0.0027.

How to perform accurate calculation of heat balance and quantitative analysis of energy efficiency for building clusters is an urgent problem to be solved to reduce building energy consumption and improve energy utilization efficiency. This article proposes a method for the heat balance calculation and energy efficiency analysis of building clusters based on enthalpy and humidity diagrams and applies it to the energy management of building clusters containing primary return air systems and heating pipe networks. Firstly, the basic structure and energy management principle of building clusters with a primary return air system and a heating pipe network were given, and the heat balance calculation and energy efficiency analysis method based on i-d diagram was proposed to realize the accurate calculation of heat load and the quantification of energy utilization. Secondly, the energy management model of the building cluster with a primary return air system and a heating pipe network was established to efficiently manage the indoor temperature and the heating schedule of ASHP, HN and HI. Finally, the proposed method was validated by calculation examples, and the results showed that the proposed method is beneficial for improving the energy economy and energy efficiency of building clusters.

Recent years have seen the increasing flexibility in the changes of the demand-side user load, which makes it difficult to evaluate the demand-side response. Moreover, the accountability of the evaluation of the response plan depends on the accuracy of load peak-valley difference forecast. Therefore, considering the complexity of the load peak-valley difference, we establish a mid- and long-term peak-valley prediction model based on random forest and secondary correction to evaluate the response effect. First, the binary feature combination is used to identify the optimal feature set. Secondly, the random forest model is applied to the first mid-and long-term long-term prediction of the monthly and quarterly peak-valley differences. Finally, taking into account the impact of the influencing factors of different years on the seasonal peak-valley difference, we use the support vector regression machine to obtain the fitting features of the correction factors and the load peak-valley difference, which facilitates the secondary correction of the prediction. The validity of the model proposed is verified by the residential user load data of a city in Jiangsu Province.

随着能源市场的改革,社区综合能源系统各主体的分布式自治特征愈发明显,对传统集中式模式的计算和通信能力提出了挑战.考虑柔性负荷通过智能楼宇接入综合能源社区,形成分布式源荷互动模式,提出了基于目标级联分析理论的分布式优化调度模型.首先,将综合能源服务商和智能楼宇作为不同利益主体,以运行成本最低为目标,建立各自的优化自治模型.其次,引入目标级联分析方法,通过将购电功率等效为虚拟发电机与虚拟负荷实现不同主体间运行的解耦.最后,通过算例验证了所提方法的有效性,为综合能源社区运行提供了更为经济的运行方案.

The development service of adjustable load resource operation analysis module is a support platform deployed to adapt to the participation of adjustable load resources in regulation business. It is a part of smart grid dispatching control system (referred to as “D5000 system”) egion through it. It is mainly positioned as the load resource information gathering and processing center. The adjustable load resource operation analysis module carries out information undertaking, analysis and processing with the traditional automation system, realizes the on-demand interaction of monitoring, control and market data among various systems, and supports the adjustable load resources to participate in the regulation business without affecting the traditional business structure of the existing production control. It includes basic platform, data acquisition, processing verification, model data storage, auxiliary analysis and decision-making, instruction forwarding, control effect verification and visual display. The adjustable load resource operation analysis module service shall meet the cross platform interconnection and high time effective data exchange with the operation systems of different aggregators, so as to realize the comprehensive collection, monitoring, comprehensive analysis and display of adjustable load resources by dispatching. Establish a complete data model based on the characteristics of load resource objects, access the real-time measurement of load monomer and aggregation, AGC on / off signal, adjustable upper and lower limits and other control data, undertake the transfer and distribution of AGC instructions and planned values, and release market data such as declaration, clearing, settlement information and announcement. Meet the “comprehensive collection, reliable interaction and on-demand provision” of information between traditional dispatching automation system, aggregator operation platform, regulation cloud, auxiliary service market and other systems, and finally realize the panoramic perception, analysis and control of adjustable load operation situation on the dispatching side.

电力需求具有诸多响应主体,已有电力需求响应主体之间存在不协同、相互割裂的弊端,使得难以形成完善的互利共生合作框架体系,为解决此问题,在阐述共生理论的基础上,纳入政府机构、用户、电网企业、发电企业4个主体,构建政府主导、企业推动、用户倒逼的多主体共生体系框架,并对其运行机理进行了具体分析,根据多主体共生系统结构及其运行机理,分别从利益关系、交易频率、共生媒介与空间布局4方面提出了偏利共生、互利共生;偶然共生、间歇共生、连续共生和一体化共生;信誉型共生、契约型共生、政策型共生;卫星式共生、区域集聚式共生、模块化网络共生12种电力需求响应互利共生模式,分别对12种模式进行详细阐述.最后进行了总结,拟为政府职能部门制定电力需求响应的政策提供理论决策参考依据.

The energy efficiency analysis is a prerequisite for the construction of the integrated energy system (IES). In this study, a novel energy efficiency analysis method is proposed considering different energy subsystems in the IES. First, the energy efficiency index of the subsystems and conversion devices is formed for elaborating their influence on the IES. The IES is composed of four energy subsystems, i.e., power/gas/heat/cooling subsystems, and six energy conversion devices. Next, the energy efficiency contribution models of energy subsystems and conversion devices are proposed based on their energy efficiency index, respectively. Then, in order to calculate the energy flow in the IES, an equivalent topological model of the IES weighted directed graph is proposed to calculate the energy efficiency contribution. Finally, an actual park is employed to illustrate the validity of the proposed analysis method.

Event detection is an important foundation of non-intrusive load monitoring algorithm. In this paper, the common household appliance load events are classified, and a new triple-threshold event detection algorithm is proposed aimed at solving the problems of false detection and missing detection in the practical application. Firstly, a low power threshold is used to realize high-sensitive detection of the load events, and secondly the detected events are spliced according to the time threshold to get the complete events. Thirdly, the high threshold is used to discriminate the complete event set to filter out the disturbance caused by load fluctuation. Finally, the results are modified with a correction logic. The test results carried with static data show that, the algorithm proposed in this paper is more accurate for positioning the time of putting into and cutting off load, which is conducive to improve the accuracy of transient interval interception of load events, and has advantages in detecting slow rising load events. In addition, the algorithm proposed in this paper has a small amount of calculation, which can meet the requirements of application in the hardware of smart meter.

电力需求响应在保障能源安全供应与电力需求平衡、提高电力系统资源利用效率方面,发挥着积极作用,科学测度评价电力需求响应效益对于较好改善电力资源优化配置具有重要意义.为科学客观测度评价电力需求响应效益,从电力用户、电网企业、发电企业、政府机构4个参与主体入手,通过构建系统模型揭示各参与主体对电力需求响应的运演机理;选取相关指标体系,通过问卷调查获取数据,并运用层次分析测度评价各主体参与电力需求响应效益.研究表明:政府机构效益最高,电力用户效益第二,发电企业效益第三,电网企业效益最低.据此展开了相关讨论,为电力部门提高电能利用效率等提供理论支撑与实践指导.

Rapid and accurate eddy-current calculation is necessary to analyze eddy-current couplings (ECCs). This paper presents a general 3D analytical method for calculating the magnetic field distributions, eddy currents, and torques of ECCs with different Halbach magnet arrays. By using Fourier decomposition, the magnetization components of Halbach magnet arrays are determined. Then, with a group of H-formulations in the conductor region and Laplacian equations with magnetic scalar potential in the others, analytical magnetic field distributions are predicted and verified by 3D finite element models. Based on Ohm’s law for moving conductors, eddy-current distributions and torques are obtained at different speeds. Finally, the Halbach magnet arrays with different segments are optimized to enhance the fundamental amplitude and reduce the harmonic contents of air-gap flux densities. The proposed method shows its correctness and validation in analyzing and optimizing ECCs with Halbach magnet arrays.

This paper proposes a method to assess the active population in households based on the fine-grained electricity consumption data from Non-Intrusive Load Monitoring (NILM) devices. Firstly, a feasibility study on assessing household active population using fine-gained data was carried out. Various indices were then designed to evaluate active population. At last, an evaluation method was proposed in accordance with the proposed indices. The proposed method was applied to the measurement result of population quantity of each resident user. Through the method proposed in this paper, the data of household active population can be obtained, which can provide data support for the customer-oriented service of power grid and development of energy strategy for authorities.