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The intermittent access of renewable energy sources leads to a significant increase in fault short‐circuit currents in power grid. DC superconducting fault current limiters (SFCL) can limit short‐circuit currents in flexible DC transmission systems, which work in combination with direct current circuit breaker (DCCBs) to protect the grid system effectively. However, for the parameter design of DC superconducting fault current limiter (DCSFCL), it is difficult to balance the economics of the device and its adaptability to different fault situations. In this paper, a cross‐mapping design methodology for the DCSFCL is proposed and applied in the Nan'ao flexible DC transmission project, China. A cross‐mapping method is designed combining the critical parameters of DCSFCL and the system parameters. A three‐terminal simulation model of the flexible DC transmission system is constructed through MATLAB/Simulink and the design process of DCSFCL parameters is introduced. A cyclic calculation approach is proposed for the design of DCSFCL parameters through three fault conditions of the power system. Meanwhile, impact current short‐circuits test and artificial ground short‐circuit test were conducted on the prototype. Test results show that the designed DCSFCL meets the requirements of practical applications. [ABSTRACT FROM AUTHOR]

A large‐scale AC/DC hybrid power network has recently been constructed in China because of the fast development of high voltage direct current (HVDC) technology. The receiving AC system must have sufficient system strength to guarantee the safe operation of the DC side. The paradox is that raising the AC side system's strength will increase the short‐circuit current (SCC) level, endangering the safety of the system. In order to resolve the contradiction between the system strength of multi‐infeed DC receiving‐end power networks and SCC, this paper proposes an optimal transmission switching strategy. Firstly, the system strength is characterised by the multi‐infeed short‐circuit ratio (MISCR), followed by constructing a comprehensive constraint set that considers the MISCR and SCC simultaneously. Secondly, to optimize SCC with MISCR and N−1 safety constraints, a mixed integer linear programming model is developed. Finally, to enhance the computing performance for large power systems, a new connectivity constraint set and decision space reduction techniques are provided. The proposed method is tested for effectiveness using the IEEE 30‐bus and IEEE 118‐bus systems. [ABSTRACT FROM AUTHOR]

Equipment maintenance decision is a very critical technology in power grid asset management. The traditional maintenance decision focuses on the analysis of the operation performance of the equipment itself, but lacks the analysis and description of the fuzziness of power equipment outage parameters. Therefore, this paper establishes the reliability assessment model based on equipment health condition monitoring, which makes the maintenance decision transition from equipment level to system level, and the fuzzy mathematics theory is introduced to establish a model describing the fuzziness of equipment failure rate parameter to make system reliability assessment and equipment maintenance decision scheme. Firstly, this paper proposes a fuzzy failure rate model of power transformer based on condition monitoring. Then the fuzzy parameters are combined with the conventional probabilistic reliability assessment method to establish the fuzzy probability hybrid reliability assessment model of the transmission system, and the fuzzy maintenance reliability benefit index is defined and deduced. Finally, a maintenance strategy of transformer based on fuzzy probability hybrid reliability assessment and fuzzy set theory is proposed, and the case study is carried out on a regional power grid in East China. The results show that the proposed model provides an improved maintenance strategy of power equipment. [ABSTRACT FROM AUTHOR]

In the distribution network planning work, taking into account the constraints of funds and construction annual plan, there is always the prioritization problem of multiple MVDC distribution networks. Aiming at the problem, this paper proposes a method for the optimization analysis of MVDC distribution network planning objects. Firstly, a comprehensive evaluation index system of urban MVDC distribution network planning and optimization is established from three aspects of improving power supply reliability and the quality of voltage, MVDC distribution network scenario types and distribution network social benefits. Then, the qualitative indexes are quantified based on the cloud model, and the comprehensive evaluation values of each distribution network are calculated and sorted by the hierarchical additive weighting of Delphi entropy weight method. Taking the maximum comprehensive evaluation value of the scheme as objective function and the annual total investment as constraint, the construction priority of multiple MVDC distribution networks is determined. Finally, taking several distribution networks in Guangzhou, Guangdong Province, China as examples, the simulation results show that the optimal objects of distribution network based on the urban scenario demands are X4, X8 and X1, with the lowest total investment cost of 19,180 yuan, thus verifying the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The development of foreign electricity markets has been relatively complete, while China's electricity market started late and the design of the market mechanism needs to be improved, so the selection of a suitable market model and the design of the market mechanism in hydropower‐rich regions is conducive to the healthy development of the electricity market. While most of the first eight pilot regions in China have entered the long‐period continuous operation stage, and all the second batch of six power spot pilots have started the simulation trial run. However, the construction of power markets in hydropower‐rich regions of China, Sichuan, and Yunnan, still faces multiple problems to be solved, such as ensuring the reliability of medium‐ and long‐term power supply, improving the efficiency of hydropower resources utilization and consumption scale, and maintaining the stability of market prices. In this paper, the authors establish a multi‐scale joint clearing model for different market models considering both long‐term and short‐term operation strategies, and conduct simulations of different market models at different time scales to compare and analyze the optimization results and electricity price fluctuations of different market models. It can stabilize the market price and reasonably reflect the true value of hydropower, and also promote the consumption of clean energy and guarantee the reliability of power supply in the medium and long terms. Finally, suggestions are made for the selection of electricity market models, the security of energy supply and the design of sustainable development mechanisms for hydropower in hydropower‐rich regions such as Yunnan and Sichuan in China, with a view to providing useful references for the construction of China's electricity market. [ABSTRACT FROM AUTHOR]

Pollution usually accumulates on the surface of the insulator rapidly on high‐speed electric multiple units (EMUs) under operation condition, and the flashover can occur frequently, especially when the EMUs is running on a high‐altitude line. To solve the problem, this paper proposes the calculation method of insulator withstand voltage under the condition of non‐uniform fouling distribution of high‐speed airflow based on the characteristics of high altitude of Lanzhou‐Xin Line in China, and gives the design and test verification of insulator support insulator for 3500‐km altitude. The design and test verification of the supporting insulator of the rolling stock applicable to 3500 km altitude are presented. The result shows that the insulator should be reliable operation on 4430‐km high altitude area if the insulator structure height is 430 mm, the creep distance is 1250 mm. The anti‐pollution performance is fine in high‐speed wind if the radiuses of the large and small shed of the insulator are 196 and 145 mm, respectively, and the shed spacing is 45 mm. The 50‐Hz withstand voltage of the developed insulator is 131 kV and the light impulse voltage is 228 kV which is suitable for lines running on 3500 m. This research provides a theoretical basis and data to support the safety of high‐speed rolling stock in high‐altitude areas. [ABSTRACT FROM AUTHOR]

Abnormal heating of composite insulators on ultra‐high voltage (UHV) transmission lines is widespread under high humidity and heat in southern China. The infrared imaging technology can be used of quickly and effectively detect insulators with abnormal heating and determine their defect types. However, it may cause misjudgement when the infrared images are not clear. A super‐resolution reconstruction method of infrared images of composite insulators with abnormal heating based on improved super‐resolution generative adversarial networks (SRGAN) is proposed in this paper, and the dense residual network in SRGAN is perfected by introducing the residual channel attention (ResCA). This method overcomes the problems that the resolution of images reconstructed by traditional methods is not significantly improved, and images are too smooth, and the edge details are easily lost. Compared with the traditional methods, the five reference‐free image quality evaluation indexes of the image reconstructed by the improved SRGAN are increased by −0.73% to 63.84%. Further the effectiveness and superiority of the improved SRGAN are verified by comparing the changes in the distribution of grey values of infrared images before and after reconstruction. Finally, the improved SRGAN is used to perform super‐resolution reconstruction of the low‐resolution infrared image examples. [ABSTRACT FROM AUTHOR]

The China Energy Administration has issued policies to encourage energy storage to participate in the electric auxiliary service market, which will provide ideas for electric vehicle charging stations (EVCSs) to collectively participate in peak‐regulation and frequency modulation (FM). Taking into account the benefits of EVs participating in peak‐regulation and FM, this paper studies expansion planning for EVCSs. First, the orderly scheduling strategy of EVs under vehicle‐to‐grid (V2G) technology is established in this paper. And a peak regulation method is proposed to maximize the economic benefits of charging and discharging during peak and valley periods. Second, based on the temporal and spatial prediction model of EV charging demand, the expansion planning model of EVCSs is constructed considering the benefits of peak‐regulation and FM. Aiming at minimizing the comprehensive annual social cost of charging stations, the expansion site selection and capacity scheme of EVCSs are obtained. Finally, taking the 24 nodes in Xiangzhou District of Zhuhai City as an example, the location and capacity of the final annual expansion plan are obtained. And the influence of main control parameters on the results of the whole model and method is analysed in detail, the feasibility and effectiveness of the whole model and method are verified. [ABSTRACT FROM AUTHOR]

Buildings near direct current transmission lines are sensitive to the electromagnetic environment, and the measurement of the electric field above them is important in engineering design and environmental assessment in China. The models of buildings and probes in the ion flow field were established to explore the accurate measurement method of the electric field above the building. Based on the upstream finite element method and the predictor–corrector method, the influence of whether the probe was grounded or not above the building was studied. On this basis, simulation experiments and real‐type experiments were carried out. The results show that when the electrical conductivity of the building was greater than 10−10 S/m, being grounded or not would not change the results. When the building conductivity was between 10−11 and 10−12 S/m, the electric field measurement results would be increased by 30% to 120% after grounding. In the real‐type experiments on the platform with a plywood roof, the relative error in the electric field when grounded or not was only 2.6%. This proved the reliability of the calculated results. In this paper, the measuring method of the DC space charge‐modified electric field above buildings was analyzed first, and the conclusion that ground wire can be cancelled above buildings with general materials was presented. The research results can provide a technical basis for the accurate measurement of the electric field above the buildings near DC transmission lines. [ABSTRACT FROM AUTHOR]

With the increasing proportion of wind power connected to grid, power system dispatching is facing more and more challenges from uncertainty. To cope with this uncertainty, robust optimization has been applied in unit commitment (UC) problem. In this paper, a multi-band uncertainty set considering the temporal correlation (MBUSCTC) of wind/load prediction error is proposed firstly, which has two characteristics: (1) The MBUSCTC rigorously and realistically reflect the distribution characteristics of uncertainties in uncertainty intervals, thereby effectively reducing the conservatism of the traditional singe-band uncertainty set; (2) the temporal correlation constraints of wind power/load prediction errors in MBUSCTC could limit the realization of uncertainties fluctuating frequently in uncertain intervals, thereby eliminating scenarios with lower probability in uncertainty sets. Then the proposed MBUSCTC is applied to UC problem, leading a robust UC model based on MBUSCTC, which is solved by Benders decomposition method and C&CG method. Finally, case studies based on the modified IEEE-118 bus system and an actual power system of China demonstrate that the proposed method can effectively reduce the conservativeness of the robust UC model and ensure the robustness of the unit commitment solution. [ABSTRACT FROM AUTHOR]

With the access of renewable distributed generations and the uncertainty of demand-side response, the operation states of the active distribution network (ADN) are uncertain. This study proposes a novel optimal strategy taking active management costs of the source--network--load as the goal and considering the site selection and the incentive price for the responsive load to optimise the ADN. To deal with uncertainties, a chance-constrained optimisation model is established and the Monte Carlo sampling method is used. Then, the uncertain model is settled by the improved backtracking search algorithm, which uses an adaptive mutation scale factor. Finally, the practicability of the proposed strategy and the performance of the algorithm are verified by the modified IEEE 33-bus distribution system and an actual distribution system in China. [ABSTRACT FROM AUTHOR]

Several retrofillings have been performed by different utilities in China. However, there is still insufficient understanding of the retrofilling procedures for minimising residual mineral oil and on the effect of the temperature rise of transformers. Following new detailed procedures, an out‐of‐service S11‐M‐315/10 (10 kV 315 kVA) and a new S13‐M‐400/10 (10 kV 400 kVA) distribution transformers were selected to retrofill their mineral oil with FR3, a soybean‐based natural ester. A method was proposed to predict the residual mineral oil content, which uses the kinematic viscosity at 60°C. This method fills a gap in the testing of residual mineral oil content. The mass ratios of residual mineral oil were 1.24% for the S11‐M‐315/10 transformer and 2.05% for the S13‐M‐400/10 transformer, based on the procedures in this study. The fire point of the mixed oil after retrofilling was 352°C, which meets the K‐class less‐flammable requirements, indicating a proper control of residual mineral oil. After retrofilling, the time of reaching the limits of the 1.5 times rated load was 30% longer than that of the mineral oil transformer. Two retrofilled transformers have been operating in good conditions since November 2019 for the S11‐M‐315/10 transformer and December 2020 for the S13‐M‐400/10 transformer. [ABSTRACT FROM AUTHOR]

Short‐term load forecasting is essential to power systems management. However, most existing forecasting methods fail to fully consider how to rationally integrate the intrinsic time‐related dimensions of electric load data and the decomposition methods into machine learning models so that their prediction accuracy and robustness still have much room for improvement. To solve this problem, this paper proposes a decomposition‐based multi‐time dimension long short‐term memory (DB‐MTD‐LSTM) model for short‐term electric load forecasting (STELF). In DB‐MTD‐LSTM, empirical mode decomposition with adaptive noise (CEEMDAN) is first introduced to smooth non‐linear non‐stationary electric load data and constrain the modal aliasing or noise of decomposed electric load data in the traditional decomposed method. A joint relevant time dimensions method (JRTDM) is then developed using autocorrelation analysis to rationally extract the temporal characteristics of decomposed data in multiple time dimensions. An improved LSTM called MTD‐LSTM is developed by combining JRTDM with LSTM, which can effectively apply multi‐dimensional time characteristics of the decomposed load to improve the predictive accuracy and robustness. Several datasets from Australia and China are performed to check the predictive performance of DB‐MTD‐LSTM. Experimental results verify that DB‐MTD‐LSTM has better predictive accuracy and satisfactory robustness compared with state‐of‐the‐art and conventional predictive models. [ABSTRACT FROM AUTHOR]

Power distribution networks are in a transformation active distribution networks with distributed energy resources. However, the widely adopted distribution test networks were established many years ago, which are untimely and cannot reflect the characteristics of high penetration renewable energy. Therefore, in this study, a distribution network with high penetration renewable energy is established based on the real data of a renewable-energy-rich radial rural distribution network in China. The proposed radial distribution network includes three types of loads and two types of renewable energy distributed generations. The evaluation indexes are designed to assess the proposed system and compare with the existing distribution networks. In addition, the topical high/low voltage problem of distribution network caused by high penetration of renewables is discussed. Furthermore, based on the measured time series characteristics of load and renewable resources, the effectiveness of the proposed system is validated by power flow analysis and dynamic characteristic criterion. [ABSTRACT FROM AUTHOR]

Circuit breakers (CBs) are of vital importance for the stability of power systems, and a new two-stage hierarchical state estimation method is proposed for 500 kV sulphur hexafluoride CBs based on Bayesian probability and perceptron neural networks. On the basis of the samples collected from Yunnan Power Grid in China, a new indicator system is constructed by association rules. Bayesian probability is applied to measure the correlation between the individual indicators and comprehensive indicators at the same status level, to weigh the individual indicators. Also, an adaptive perceptron is improved to train the weights of comprehensive indicators in different operational conditions, to eliminate the influence of the imbalance problem of relative deterioration. Then, the operating state of equipment can be inferred according to the calculated comprehensive scores. Finally, taking the actual operating equipment as an example, the effectiveness of this proposed method is proved by sample tests and comparison with other existing linear methods. [ABSTRACT FROM AUTHOR]

With the recent China electricity market reformation, an increasing portion of electricity is traded in wholesale electricity markets. However, collusion among generation companies reduces competition and raises market clearing prices. Based on the newly released electricity policies in China, a two-stage market clearing method is employed to mitigate collusion. In order to evaluate the effectiveness of this method, the system dynamics method is adopted. With consideration of the two aspects of collusion, i.e. capacity withholding and bidding at a high price, the causal feedback and quantitative relationship between the generator bidding process and the market clearing process are established. The sensitivities of the market parameters are analysed in a case study with real data collected from the Eastern China electricity market. The results can be used as a reference for policy makers. [ABSTRACT FROM AUTHOR]

Unit restarting after a blackout is the basis of the overall restoration process for a power system. A reasonable restarting sequence of units may speed up the restoration process and reduce economic loss. In view of the situation that there are usually several black-start sources in a large-scale power system, a global optimisation method for unit restarting considering black-start zone partitioning is proposed in this study. On the basis of the multiple time-step modelling framework, the optimisation problem is formulated as a mixed integer linear programming model, with the objective functions to maximise the total-weighted MWh output and minimise the links between the subsystems under various operational constraints. The hierarchical method based on generalised Benders decomposition is applied to decompose the optimisation problem into one master problem and two sub-problems: (i) determination of the unit restarting sequence considering only the grouping of units and (ii) rationality check of unit grouping and check of operational constraints based on power flow calculation. The master problem and sub-problems are alternately and iteratively solved until the optimal solution is obtained. The results of New England 10-unit 39-bus system and a practical power system in southwest China verify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

In modern power systems, the impact of random power sources and loads on power systems is increasing, resulting in threatened system frequency security. However, traditional methods are often not comprehensive in modelling randomness, and there is no analytical method to assess the frequency response of power systems under uncertain power fluctuations. Here, the power fluctuation in a power system is regarded as an interval random quantity. An analytical prediction method of the power system frequency deviation under uncertain power fluctuation is proposed. Through further deduction, the allowable range of power fluctuation under the premise of secure frequency deviation can also be defined, which provides a reference for frequency security and accident prevention in power systems. Numerical simulations with the model of the East China Power Grid demonstrate that the proposed analytical method can delimit the response interval of system frequency deviation well, and the backstepping calculation can also delimit the allowable range of power fluctuation to ensure the secure operation of the system. [ABSTRACT FROM AUTHOR]

The fluctuation of photovoltaics (PVs) output may cause the voltage out‐of‐limit, while the PV inverters and hybrid distribution transformers (HDTs) bring flexible controllability to distribution networks (DNs). However, there are differences in response speeds between power electronic equipment and traditional discrete regulating equipment. Therefore, a network partitioning and hierarchical voltage regulation method using holomorphic embedding method (HEM) ‐based sensitivity is proposed. Firstly, the HEM‐based voltage sensitivity is derived, and the network partitioning method is proposed using the HEM‐based sensitivity matrix. Then, the hierarchical voltage regulation framework is constructed. The objects of the upper layer are the minimum network loss and voltage deviation, which centrally optimizes the operation status of discrete regulation equipment. The lower layer exploits the fast control ability of PV inverters and HDTs, so as to autonomously regulate the voltage of each partition. Finally, a practical 10 kV DN in China is used for case studies. The results demonstrate that the HEM‐based voltage sensitivity calculation method has advantages in computational efficiency and accuracy compared with the conventional method. Moreover, the proposed voltage regulation method can suppress the voltage fluctuation. [ABSTRACT FROM AUTHOR]

Icing disaster is one of the most serious threats to power grid security in China. This article provides a brief glance of current China's monitoring and prevention methods of icing disaster (MPI) development status. Despite a late start, China's research and development on MPI have made outstanding achievements, including formation mechanism causing ice disaster, key technologies and characteristics, and anti/de‐icing approaches development and application. It is apparent that Chinese scientists and engineers confronted the worldwide problem of anti/de‐icing, and put forward a comprehensive solution, which plays a more critical role in icing disaster prevention and reduction of power grid during the past 15 years. The article states that the anti/de‐icing devices have been applied successively to severe icing issues. These achievements are leading the world in the development and application of MPI. However, it is only at the extreme ice and snow conditions that can test and verify whether prevention methods are comprehensive and perfect or not. And the authors discovered the application limitations in the existing achievements. The article also discusses the overall development trends of MPI in the areas of key technological and technical breakthroughs and application scenarios etc. These discussions serve as references for MPI's future technological advancement and its ever‐expanding applications. [ABSTRACT FROM AUTHOR]

Large‐scale day‐ahead wind power forecasting (WPF) for wind farm clusters (WFCs) can enable dispatching agencies to formulate scientifically sound power generation plans and enhance the robustness of power grids. Most available WPF methods for WFCs only involve mathematical models and rarely consider spatial correlation factors. This necessitates further improvements to forecasting systems. In this study, to increase the day‐ahead WPF accuracy for WFCs, fractal transform theory is introduced to optimize the process of WPF for WFCs through spatial upscaling and establish a day‐ahead WPF model for WFCs based on an improved spatial upscaling method. First, a WFC is partitioned into subclusters. Then, using fractal transform theory, an affine relation is established between the local output of each subcluster and the overall output of the WFC. Finally, a day‐ahead power forecast is produced for the WFC through spatial upscaling of the forecast for the subcluster with the highest grey relational grade with the output of the WFC. The applicability of the proposed forecasting model is examined using historical measured data for a large WFC in north‐eastern China. The case study results show that the proposed forecasting model outperforms the summation method and the statistical upscaling method in terms of forecasting accuracy. [ABSTRACT FROM AUTHOR]

Secondary direct-current loss within a substation is a severe event. In China, each line protection device is generally powered by one set of secondary direct current (DC) power system within a substation of 110 kV voltage level. In this case, the line protection devices will be immediately taken out of service when the secondary DC is lost, and the lines protected by them will lose their corresponding protections. Once a fault occurs on the line, only the remote back-up protection can be relied on to isolate the fault, which expands the fault influence and increases its clearance time. To handle the above problem, a novel wide-area protection algorithm based on compensation voltage moduli comparison is proposed, which is independent of multi-terminal data synchronism. Then, a comprehensive protection strategy composed of the proposed protection algorithm and the original local distances protection is proposed. The results from a power systems computer aided design/electromagnetic transients including DC (PSCAD/EMTDC)-based simulation verify that the proposed protection algorithm has higher sensitivity. The comprehensive protection strategy could cope with most line faults effectively, even if only partial data are available, the selectivity and speed of which are better than that of distance protections. [ABSTRACT FROM AUTHOR]

Natural disasters, such as typhoons and earthquakes, pose great challenges to power system resilience and power supply reliability. It is widely acknowledged that critical transmission lines play a significant role in enhancing the resilience and reliability of power systems under severe natural disasters. In order to improve the disaster resilience of power systems with renewables, a critical line identification approach is proposed in this work based on the complex network theory. Firstly, the concept of core skeleton network (CSN) of power systems with renewables is introduced and a two-step strategy is presented to optimise the CSNs of the concerned power system considering the variable outputs of renewables. Then, a statistical salience method incorporating edge salience and the state-of-the-art null model in complex network theory is proposed to identify critical lines of each CSN and the concerned power system with renewables. Finally, the effectiveness of the proposed critical lines identification approach is verified by simulations on the modified IEEE 118-bus system with renewables, Guangdong Provincial Power System (GPPS) and Zhejiang Provincial Power System (ZPPS) in China. Simulation results show that by using the proposed approach, the critical transmission lines can be effectively identified, not requiring a predefined number of critical lines. [ABSTRACT FROM AUTHOR]

Contingency screening is vital for maintaining the transmission system reliability. Bilevel programming is a powerful tool for the accurate identification of critical events. To accelerate the contingency screening with bilevel programming, this study proposes a root-event-based dynamic space pruning algorithm. A root event is an event in which all the failed components have contributions to the event impact. Considering the fact that numerous N − k events describe the same critical scenario, the proposed space pruning principles partition the N − k event space into the subspace of root events and the complement subspace. To accelerate the screening of subspace of root events, bilevel programming is constructed to identify new critical events having high risk and causing more severe load shedding than the root event. Besides, relaxed bilevel programming is proposed to accelerate the screening of the complement subspace. The relaxed scheme replaces the constraints of power flow by constraints of transmission capacity, and enables the identification of most of the critical events in the complement subspace with a low computational cost. Case studies on the IEEE RTS and a provincial grid in China indicate that the proposed algorithm significantly accelerates the screening process without missing critical events. [ABSTRACT FROM AUTHOR]

With the development of renewable energy market, Renewable Portfolio Standard (RPS) has become the targeted renewable energy incentive mechanism in China and it is under a government's long-term plan that RPS overtakes feed-in tariff gradually in recent years. Given this background, the decision-making model of electricity retailers to accomplish the obligation under RPS is constructed as a bi-layer portfolio selection model. In the inner-layer, both capital allocation of the retailers to purchase various kinds of renewable energy capacity as well as RECs are optimised. In the outer-layer, the capital investment portfolio of each risky and risk-free strategy is determined based on the Behavioural Portfolio Theory, with different mental accounts (MAs) with different aspiration points and threshold levels built to describe the investor philosophy of retailers during the decision-making process. The simulation results of a provincial electricity market in China demonstrate that the presented model can effectively assist electricity retailers in making their capital investment strategies under RPS with relevant market factors. In addition, the proposed model provides insights for policy makers to set key parameters involving the design of RPS by analysing behaviours of retailers, including required quota ratio and value of fines. [ABSTRACT FROM AUTHOR]

With the increasing usage of cross-linked polyethylene (XLPE) power cables, it is more and more important to grasp and manage their insulation status. Nowadays, the distribution cables in urban area are of huge numbers, so it is impossible to carry out the preventive test for every cable. Therefore, it is very helpful to determine cables' testing urgency in a scientific way. Meanwhile, the main cable diagnosis methods in China are insulation resistance and withstanding voltage test, but they are difficult to quantitatively determine cable insulation status. Aiming at solving above challenges, according to the cable fault records in recent years, fuzzy evaluation analysis combining with mutual information is utilised to determine the insulation testing urgency (ITU) based on cable information including service year, laying way, load type, and length. At the same time, frequency domain spectroscopy (FDS) is introduced to diagnose the on-site cable insulation status quantitatively. Its characteristic parameters, including instantaneous electric susceptibility, DC conductivity, and hopping conductivity, are extracted by improved Havriliak-Negami (H-N) model and studied to analyse the changing trend before and after cable deterioration. The results show that the lower ITU is, the higher testing urgency is. ITU also has negative correlation with FDS characteristic parameters. [ABSTRACT FROM AUTHOR]

In China, the increasing amount of electricity imported from high voltage direct current (HVDC) transmission systems in some provinces has led to the retirement of local units. Lack of local generating capacity is adverse to the stability of system frequency and the adequacy of ancillary services. This study proposes a practical method to determine the minimum requirement of generating capacity (which is called the reliable generating capacity, RGC) in the sink side of a power grid. The relation between the minimum system frequency and the generating capacity is theoretically analysed. Based on simulation results, a function that determines RGC under a certain frequency drop constraint can be specified by data fitting. Meanwhile, the requirement of ancillary services (such as peak regulation, automatic generation control, and reserves) on typical days also imposes a floor constraint on the generating capacity. So the relation between generating capacities and ancillary services is also explored. Finally, the overall RGC value is the maximum of the above two aspects. A case study in East China Power Grid proves the effectiveness of the proposed method. The result can be used as a reference for power system planning and operation. [ABSTRACT FROM AUTHOR]