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Considering the increasing coupling between transmission and distribution networks, an affine arithmetic-based interval power flow algorithm of integrated transmission and distribution (I-T&D) networks is proposed. First, a novel two-step approximation method for sine and cosine functions is proposed to reduce the number of noise variables in the affine form of the injected power, as the basis of the proposed algorithm. Then, this algorithm is divided into four stages, which are implemented alternatively between a transmission system operator (TSO) and multiple distribution system operators (DSOs) by exchanging parameters at TSO-DSO boundaries. Three-phase unbalanced I-T&D networks and boundary tap changer action are also discussed. In addition, an asynchronous power flow method is proposed to mitigate the influences of communication networks on the proposed interval power flow algorithm. Numerical experiments demonstrate the effectiveness of the proposed two-step approximation method, as well as the conservative property, fairly good approximation effect, high efficiency, and low data exchange amount of the proposed algorithm in various circumstances, including single-phase and three-phase networks, varying degrees of unbalance, various smart inverter controls, etc.

To satisfy the robust and real-time requirements of power flow calculation for large-scale power systems, a globally convergent method is proposed with trust-region techniques, which shows satisfying robustness and convergence. Then, this method is combined with Newton's method to achieve a two-stage algorithm, benefiting from their different advantages. In the first stage, the proposed globally convergent method is used for searching power flow solution. When the values of state variables in a certain iteration are close enough to the real operational point, the algorithm enters the second stage to use Newton's method to achieve the solution. This two-stage algorithm can achieve an accurate solution for solvable cases, and can also achieve a least-square solution, which is an approximate solution for unsolvable cases. Numerical experiments show that the proposed globally convergent method and two-stage algorithm have better robustness and efficiency than the existing methods in previous research. They have universality for well- and ill-conditioned systems as well as the cases under ill-conditioned operational modes, heavy loads and inappropriate initial values. They can also handle different limit violations, such as reactive power limit in PV buses and voltage limit with tap changers action, which could significantly benefit real practice.

Distribution networks with high penetration of distributed generation yield complicated and uncertain power flow, which makes most existing faulted line identification methods not adaptable for industrial applications. Driven by this motivation, a novel single-phase-to-ground (SPTG) faulted line identification method is proposed based on hybrid state estimator (HSE). The first step of the method is to present an HSE for power distribution networks using power flow measurements mixed phasor measurement units. Then, an SPTG fault on a power line is treated as an event that suddenly increases one virtual bus in the monitored network, so as to form the extended bus admittance matrix and augmented HSE based on the specific network topology. In this way, the faulted line identification could be obtained by computing parallel estimated results transversally. Robustness and effectiveness of the proposed HSE and the HSE-based SPTG faulted line identification method are validated by means of a cyber-physical system (a cosimulation platform), where two typical three-phase power distribution networks are considered to simulate with its hybrid measurement system.

The state information of district heating network (DHN) is significant to the secure operation and control of the integrated energy system. This paper focuses on the dynamic energy flow calculation method of the hot-water heating network under variable flow rate conditions, i.e. under the quantity regulation mode. First of all, known inputs, desired outputs and mathematical formulation of the energy flow calculation model are clarified. For the partial differential equation describing the temperature dynamics in each pipe, we apply the finite difference method to convert it into a group of algebraic equations for standardized solution. After that, a cross iteration method is proposed to solve the high-dimensional nonlinear model, where the global mass flow rate distribution and the temperatures of return water at each load are alternately updated until both converge to their acceptable precision levels. One nice feature of our method is that the temperatures of return water at each load do not need to be known inputs. Instead, the dynamic response of them can be fully captured, which is crucial for identifying the thermal conditions at each load. Test results of a DHN in the Barry Island demonstrate the validity and effectiveness of our method.

A continuous power flow (CPF) calculation method for the islanded microgrids with droop control is proposed in this paper. The starting point of CPF is solved by the modified factored load flow algorithm. The algorithm ensures the robustness of the starting point calculation with a two-step solution. The tangent prediction method and the Newton-Raphson method are used to determine the prediction and correction steps. Further, this paper proposes an adaptive step size control method based on frequency variation, which avoids the comparison among different nodal voltage magnitudes. In addition, node type switching is considered for handling the limit violations of PV nodes and droop nodes. The case analysis shows that the proposed CPF method has high efficiency and strong robustness.

In this paper, neural network, semi-supervised training, integrated learning, and other techniques are applied to the prediction and analysis of static voltage stability margin of island microgrid power systems and an online prediction method based on the Tri-Training-Lasso-BP network is proposed. The network consists of Tri-Training, the least absolute shrinkage and select operator (Lasso) algorithm and the backpropagation (BP) neural network. The analysis results on an 115-node example show that the proposed method can reduce the requirement of the data volume of the training set, take advantage of the massive data collected during the daily operation of the power system, improve the prediction accuracy of the network and reduce manual intervention. Finally, this paper uses statistical methods to make a comprehensive and objective description of the performance of the method.

In recent years, Virtual Synchronizer Generator (VSG), which simulates the inertia and damping of the synchronous generator, has been gradually applied in microgrid. This paper studies the microgrid inverter using the VSG control strategy. Due to the existence of virtual inertia and damping coefficient in the VSG, the frequency and output active power of the microgrid inverter will oscillate when the active power scheduling command is abrupt, and the inverter will break down in severe cases due to over-current protection. Aiming at this problem, based on the root trajectory analysis of active power closed-loop transfer function, the influence of damping coefficient on VSG stability and dynamic performance is studied, combined with the physical meaning of the power angle curve and damping coefficient of VSG, the fuzzy algorithm is proposed to configure virtual damping coefficient. The VSG adaptive control algorithm of the coefficient is given, and the membership function and fuzzy rule table are given. Finally, the correctness and effectiveness of the control strategy are verified by constructing the simulink simulation model.

Spinning reserve in the electric power system is vital in dealing with the sudden drop of electricity supply caused by failure, which used to be provided by traditional power generations. With the development of information and communication technologies (ICTs), demand response (DR) is deployed gradually for providing spinning reserve by shedding flexible loads. Air conditioners (ACs) are one of the most high-quality flexible loads due to its high proportion of capacity in electricity consumption. However, power rebound spike (PRS) of AC loads tend to emerge at the end of DR. Therefore, traditional spinning reserve providers (TSRPs) have to ramp to cooperate with ACs immediately. In this paper, a DR management approach is proposed for controlling DR duration time and capacity by sequent temperature configuration. Meanwhile, the connection between PRS and DR duration time is studied. Reliability indices have also been applied to evaluate different cooperation strategies between ACs and TSRPs. Simulations based on Monte Carlo methods are performed quantitatively.

Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation (DA) system for safe operation and control. The design of optimal feeder terminal units (FTU) placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation (SE), typically include the following two main shortcomings: 1) only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2) few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function (PDF). The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy (CMA-ES). Case studies demonstrate the feasibility and effectiveness of the proposed methodology.

In the development of on-line monitoring technique for transformer aging status, detecting concentration of methanol dissolved in transformer oil by the method of surface enhanced Raman spectroscopy (SERS) is a novel and promising technique. By use of Raman spectroscopy technique, we can improve various shortcomings of traditional detection technology. In this paper, the concentration of methanol dissolved in 2 mL/L methanol-oil solution was effectively detected by surface enhanced Raman spectroscopy. In the first, Raman spectra of single methanol molecule and its SERS were simulated to analyze the Raman peaks of methanol. A SERS substrate was prepared with selective enhancement. Based on prepared SERS substrate, concentration of methanol dissolved in transformer oil with content of 2 mL/L have been effectively detected. This helped us to further study the lower concentration of methanol in oil and make quantitative analysis.

In some of the China’s urban grid, the transmission congestion problems are usually mitigated by reconfiguring the topological structure of the high voltage distribution network (HVDN). Whereas the growing amount of the electric vehicles (EV) and the large scale photovoltaic (PV) generations that integrate to the grid result in the frequent reconfiguration of the HVDN. However, the development of the energy storage technology provides an efficient method to handle this problem. But the high cost of the energy storage devices and the limited installation room for large scale energy storage systems (ESS) are still a tricky problem. Thus the size and the location of the ESS should be elaborately selected. In order to fully exploit the advantages of the ESS, this paper proposed a two-layer ESS planning model which considered the coordination scheme of the charge and discharge strategy of the ESS and the HVDN reconfiguration. The optimal size and location of the ESS is determined in the upper layer model. The lower level model is used to calculate the operation cost which can be considered as the adaptability of the decision produced by the upper layer model. The two layer optimization model is solved by the NSGA-II algorithm. A testing system extracted from an urban grid in China is used to verify the validity of the proposed method. Numerical results shows that with the assistant of the ESS control scheme, the reconfiguration times of the HVDN is significantly reduced while the reconfigurability of the HVDN is also conducive to save the investment on ESS.

With the rapid growth of energy consumption, how to utilize energy in an efficient and cheap way becomes an intensive problem. This paper proposes an optimal operation strategy to reduce system fuel costs and increase system stability by independently considering cooling loads and adjusting CHP heat to power ratio seasonally. In this paper, a mathematical model of CHP operation is introduced to reveal the relationship between the supplementary volume of diesel oil and CHP heat to power ratio. Meanwhile, by analyzing the influence of seasonal factor on energy consumption, CHP heat to power ratio is optimized seasonally. Then, by independently considering the impacts of the cooling loads on system operation, the particle swarm optimization (PSO) algorithm is used to optimize the operation strategy of each device. Finally, this paper validates the positive effects of storage devices on improving system economy and stability under the premise of the time-of-use gas price. Results show that system fuel costs can be reduced by 5.2% if the seasonal factor is considered. Additionally, by optimizing the operation strategy, the peak valley gap of electrical loads in summer reduces by 40.7%. Moreover, the proposed strategy successfully utilizes storage capacity to shift loads and respond to gas price.

Transmission congestion is considered as a serious security problem that limit the efficiency of the transmission systems. Due to the lack of controlling measures in some part of the transmission network, much load shedding amount and controlling cost would be required to alleviate the congestion. As more and more renewable energy resources integrate into the grid, the transmission lines are prone to be overload. Whereas in high voltage distribution network (HVDN), each substation usually has one or two reserve lines that connect to another power supply point thus greatly enrich the operation flexibility of HVDN. By changing the topological structure of HVDN, the load in transmission network can be greatly redistributed. In order to improve the transmission efficiency and reduce the total controlling cost, a generator rescheduling scheme considering line switching of HVDN was proposed in this paper. The model consists of a generator rescheduling model and a second order cone programming (SOCP) based HVDN line switching model. An urban test system in China was utilized to verify the effectiveness of the proposed method. Numerical results show that utilizing the HVDN line switching to transfer the load dramatically reduce the load shedding amount and controlling cost.

Efficient numerical simulation of thermo-hydraulic coupled conditions is critical for analysis and control of DH network. However, for most of meshed DH network, the flow directions of its pipelines may change, which will lead to difficulties in effective numerical calculation of the thermo-hydraulic conditions. This paper established an efficient thermo-hydraulic coupled calculation method, which utilizes the topology sorting algorithm to obtain the calculation sequence of all pipelines during numerical thermal transient calculation, according to the flow directions and flow rates of all pipelines. The flow directions and flow rates are solved by hydraulic condition calculation at each time step. The proposed method is applied to a real meshed DH network for thermal dynamic simulation. Independence analysis of hydraulic computation frequency is conducted, and convergences of the simulated temperature variations are observed when hydraulic computation frequency gets larger. Thermal dynamics of the meshed DH network are analyzed with 10-min hydraulic computation interval. Results show that the temperature decay and time delay can be up to 2.7 °C and 210 min for the simulated network. Thermal dynamic characteristics of supply temperature waves are various considering the distance from heat source, fluctuations of outdoor temperature and the variations of substation flow rate.

The growing penetration level of photovoltaic (PV) and electric vehicles (EV) increase the operational risk of the urban power system. Besides, the unbalanced load distribution at time-spatial scale also impacts the hosting capacity of the PVs and causes severe transmission congestion. Thus this paper proposed a bi-level optimization model to manage the transmission congestion and enhance the PV hosting capacity considering the reconfigurable capability of the high voltage distribution network (HVDN). In the upper level, the optimal topological structure of HVDN is calculated aiming at minimizing the total operational cost. In the lower level, the maximum hosting capacity of PVs is achieved by a second-order cone programming model. The proposed method was verified by an urban power system in China. Numerical results demonstrated that reconfiguring the HVDN topological structure provide huge benefits of enhancing PV penetration level and facilitating the integration of the EV.

Ultra-high frequency (UHF) detection, due to the advantages such as noiseless measurement, high sensitivity, wide detection range and 3-D localization capability, has been widely applied in power equipment. The propagation characteristics of electromagnetic (EM) waves should be investigated, because it serves as the substantial guides to improve the sensitivity of UHF detection and the efficiency of online monitoring by UHF detection. In this paper, a 110/35/10 kV three-phase oil-filled transformer with complete internal structure was reconstructed to investigate the propagation characteristics of EM waves. The amplitude, frequency band energy and time-frequency property were analyzed. The results show that the amplitude of EM waves decreases nonlinearly and the attenuation rate slows down with the increasing distance between antennas and PD source. During the propagation of EM waves, the higher frequency bands suffer the greater attenuation leading to the less energy ratio and the energy mainly concentrates on the 300 MHz-600 MHz. The time-frequency analysis also proves that higher frequency bands suffer the greater attenuation. These results are considered to be useful for the decisions of the detection sensitivity, sensor positions and the band width of sensors.

Ice flashover threatens the security and reliability of power transmission. However, the ice flashover mechanism of insulators remains poorly understood. This study analyses water droplet freezing and ion distribution in ice layer under alternating electric field. It also investigates ion migration during icing process of insulator string under alternating electric field and its effects on insulator flashover. Results showed that the average freezing time of water droplets was related to electric field strength. The extent of ion migration during freezing decreased with increasing electric field strength. The maximal melting water conductivity of the ice layer and icicle of the insulator formed under energized condition was higher than the corresponding freezing water conductivity but lower than that under non-energized condition. Furthermore, the hanging location of each insulator significantly affected the melting water conductivity of the ice layer. The surface conductivity of the ice layer increased because of the conductive ion migration in freezing water during freezing, which was an important factor that decreased the flashover voltage of the ice-covered insulator. The existence of alternating electric field would impact the extent of ion migration. This study may serve as a reference for updating prediction flashover model of ice-covered insulators during the melting period.