Rural Power System Load Forecast Based on Principal Component Analysis

Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.

Dynamic Equivalent Method of Motor Loads for Power Systems Based on the Weighted

Dynamic equivalence can not only largely reduce the system size and the computation time but also stress the dominant features of the system [1]-[3]. This paper firstly recommends the basic concept of dynamic equivalent and the status of both domestic and abroad development in this area. The most existing equivalent methods usually only deal with static load models and neglect the dynamic characteristics of loads such as induction motors. In addition, the existing polymerization method which is based on the frequency domain algorithm of induction electric machines parameters takes a long time to equivalent for the large system, then the new method based on the weighted is proposed. Then, the basic steps for dynamic equivalence with the weighted method are introduced as follows. At first, the clustering criterion of motor loads based on time domain simulation is given. The motors with similar dynamic characteristics are classified into one group. Then, the simplication of the buses of motors in same group and network is carried out. Finally, parameters of the equivalent motor are calculated and the equivalent system is thus obtained based on the weighted. This aggregation method is applied to the simple distribution system of 4 generators. Simulation results show that the method can quickly obtain polymerization parameters of generator groups and the aggregation model retains the dynamic performance of the original model with good accuracy, the active and reactive power fitting error is smaller as well.

Wide-Area Delay-Dependent Adaptive Supervisory Control of Multi-machine Power System Based on Improve Free Weighting Matrix Approach

The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).

A novel control scheme for simultaneous elimination of imbalance, disturbance and voltage harmonic in power systems

In recent years, the increasing application of nonlinear and unbalanced electronic equipment and large single phase loads have made voltage imbalance a serious problem in power distribution systems. A novel approach has been proposed to eliminate voltage imbalance and disturbances. The main strategy of this scheme is based on series active filter. By improving control circuit toward existing schemes and proposing a new strategy to control the voltage amplitude, simultaneous elimination of voltage imbalance, faults, voltage harmonics and also compensation of voltage drop in transmission lines become possible. Eventually, the voltage on the load side is a perfectly balanced three phase voltage with specific proper amplitude. The proposed scheme has been simulated in a test network and the results show high capability of this scheme for the complete elimination of imbalance without phase shift.

Multimodel Ensemble Forecast of Global Horizontal Irradiance at PV Power Stations Based on Dynamic Variable Weight

In the present study,multimodel ensemble forecast experiments of the global horizontal irradiance(GHI)were conducted using the dynamic variable weight technique.The study was based on the forecasts of four numerical models,namely,the China Meteorological Administration Wind Energy and Solar Energy Prediction System,the Mesoscale Weather Numerical Prediction System of China Meteorological Administration,the China Meteorological Administration Regional Mesoscale Numerical Prediction System-Guangdong,and the Weather Research and Forecasting Model-Solar,and observational data from four photovoltaic(PV)power stations in Yangjiang City,Guangdong Province.The results show that compared with those of the monthly optimal numerical model forecasts,the dynamic variable weight-based ensemble forecasts exhibited 0.97%-15.96%smaller values of the mean absolute error and 3.31%-18.40%lower values of the root mean square error(RMSE).However,the increase in the correlation coefficient was not obvious.Specifically,the multimodel ensemble mainly improved the performance of GHI forecasts below 700 W m^(-2),particularly below 400 W m^(-2),with RMSE reductions as high as 7.56%-28.28%.In contrast,the RMSE increased at GHI levels above 700 W m^(-2).As for the key period of PV power station output(02:00-07:00),the accuracy of GHI forecasts could be improved by the multimodel ensemble:the multimodel ensemble could effectively decrease the daily maximum absolute error(AE max)of GHI forecasts.Moreover,with increasing forecasting difficulty under cloudy conditions,the multimodel ensemble,which yields data closer to the actual observations,could simulate GHI fluctuations more accurately.

Independent component analysis approach for fault diagnosis of condenser system in thermal power plant

A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is to utilize system as a black box.The system studied is condenser system of one of MAPNA's power plants.At first,principal component analysis(PCA) approach was applied to reduce the dimensionality of the real acquired data set and to identify the essential and useful ones.Then,the fault sources were diagnosed by ICA technique.The results show that ICA approach is valid and effective for faults detection and diagnosis even in noisy states,and it can distinguish main factors of abnormality among many diverse parts of a power plant's condenser system.This selectivity problem is left unsolved in many plants,because the main factors often become unnoticed by fault expansion through other parts of the plants.

A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial processes.However,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)analysis.Recently,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality monitoring.Although the MHNBM is effective,it still has some shortcomings that need to be improved.For the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating variables.In addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical data.When the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of MHNBM.Here a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above shortcomings.For the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the model.At the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data samples.Compared with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.

Hybrid Block Diagonalization Precoding for Multi-User Weighted Sum-Rate Maximization

This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.

LDPC-Coded OFDM Transmission Based on Adaptive Power Weights in Cognitive Radio Systems

In this paper, we propose a new scheme to improve the performance of an LDPC-coded OFDM based cognitive radio (CR) link by applying adaptive power weights. To minimize estimation errors of detected signals in all the CR subcarriers, power weights are allocated to the CR subcarriers at the secondary transmitter. Some constraints for the power weights are considered, such as keeping the interference power introduced by the CR to primary users below a given interference threshold and also keeping sum of transmission powers in all CR subcarriers within a total transmission power. The LDPC decoder applies these power weights in the Log Likelihood Ratios (LLRs) used in message passing scheme at the secondary receiver to achieve more reliable communications. So, the received signal in each CR subcarrier will be decoded with the knowledge of transmission power weights, which come from the cognitive feedback channel without additional cost. Simulation results demonstrate that our proposed scheme achieves a lower bit error rate and a higher transmission rate compared with those of the same scheme without applying power weights.

Analysis of value of flexibility in Japan’s power system with increased VRE

The growth of renewable energy has accelerated globally toward a low-carbon economy since the Paris Agreement entered into force in 2016.As a result of the increase of variable renewable energy(VRE),namely solar PV and wind,power systems require more flexibility from conventional power plants with less power generation to regulate increased variability.There are sources of flexibility other than conventional power plants,including enhanced power networks,storage capacity and demand response.To maximize economic utilization of VRE power generation,it is necessary to use the flexibility potential from all these sources.In Japan,the share of VRE has increased since the introduction of a feed-in tariff(FIT)and,in parallel,power market reform is underway.Japan has a unique power system of nine grids connected like a fish bone,making the uptake of an increasing share of VRE challenging.This paper assesses the value of flexibility by source in Japan’s power system in 2030.An analysis of different VRE scenarios is undertaken based on a newly developed production cost model.The result of the simulation shows the quantitative impact of each source of flexibility to the generation cost and VRE curtailment and demonstrates the mechanism by which flexibility works to impact VRE curtailment.

Joint Subcarrier and Power Allocation for Multi-UAV Systems

This paper investigates subcarrier and power allocation in a multi-UAV OFDM system.The study considers a practical scenario,where certain subcarriers are unavailable for dynamic subcarrier allocation,on account of pre-allocation for burst transmissions.We first propose a novel iterative algorithm to jointly optimize subcarrier and power allocation,so as to maximize the sum rate of the uplink transmission in the multiUAV OFDM system.The key idea behind our solution is converting the nontrivial allocation problem into a weighted mean square error(MSE) problem.By this means,the allocation problem can be solved by the alternating optimization method.Besides,aiming at a lower-complexity solution,we propose a heuristic allocation scheme,where subcarrier allocation and transmit power allocation are separately optimized.In the heuristic scheme,closedform solution can be obtained for power allocation.Simulation results demonstrate that in the presence of stretched subcarrier resource,the proposed iterative joint optimization algorithm can significantly outperform the heuristic scheme,offering a higher sum rate.

Differentiation degree combination weighting method for investment decision-making risk assessment in power grid construction projects

Power grid construction projects are distinguished by their wide variety,high investment,long payback period,and close relation to national development and human welfare.To improve the investment accuracy in such projects and effectively prevent investment risks,this paper proposes an investment optimization decision-making method for multiple power grid construction projects under a certain investment scale.Firstly,an in-depth analysis of the characteristics and development requirements of China’s power grid projects was performed.Thereafter,the time sequence and holographic method was adopted to conduct multi-dimensional,multi-perspective risk assessment of different parts of power grid projects,and a holographic risk assessment index system was developed.Moreover,an investment decision model considering the comprehensive risk based on combination weighting was developed according to the output and input of power grid construction projects.A new combination weighting optimization method that takes into account the investment willingness of enterprises was designed to improve the current weighting evaluation methods.Finally,the validity and applicability of the proposed evaluation method were verified by case examples.

Boundedness of Hausdorff operators on the power weighted Hardy spaces

In this paper, we consider the two-dimensional Hausdorff operators on the power weighted Hardy space H;（R;） （ -1 ≤α≤0）, defined by H;f（x）=∫R;Φ（u）f(A（u）x)du,where Φ∈L;oc;（R;）,A（u） = (α;（u）);is a 2×2 matrix, and each α;is a measurablefunction.We obtain that HΦ,A is bounded from H;（R;） （ -1≤α≤0） to itself, if∫R2|Φ（u）‖det A;（u）|‖A（u）‖;ln(1+‖A;（u）‖;/|det A;（u）|)du<∞.This result improves some known theorems, and in some sense it is sharp.

Extreme scenario extraction of a grid with large scale wind power integration by combined entropy-weighted clustering method

Large-scale integration of wind power into a power system introduces uncertainties to its operation and planning,making the power system operation scenario highly diversified and variable.In conventional power system planning,some key operation modes and most critical scenarios are typically analyzed to identify the weak and high-risk points in grid operation.While these scenarios may not follow traditional empirical patterns due to the introduction of large-scale wind power.In this paper,we propose a weighted clustering method to quickly identify a system’s extreme operation scenarios by considering the temporal variations and correlations between wind power and load to evaluate the stability and security for system planning.Specifically,based on an annual time-series data of wind power and load,a combined weighted clustering method is used to pick the typical scenarios of power grid operation,and the edge operation points far from the clustering center are extracted as the extreme scenarios.The contribution of fluctuations and capacities of different wind farms and loads to extreme scenarios are considered in the clustering process,to further improve the efficiency and rationality of the extreme-scenario extraction.A set of case studies was used to verify the performance of the method,providing an intuitive understanding of the extreme scenario variety under wind power integration.

Generalizations of mixed weighted power mean inequality

Tarnavas established mixed weighted power mean inequality in 1999. A separation of weighted power mean inequslity was derived in this paper. As its applications, some separations of other inequalities were given.

STUDY ON FUNCTION OF COMPONENTS OF DY NAMIC SYSTEM OF TOURISM DEVELOPMENT IN DEVELOPED REGION---A Case Study of Foshan in Guangdong Province

In the forming of the Dynamic System of Tourism Development (DSTD)in developed regions from the view of supply side,the Delphi Method and the Analytical Hierarchy Process(AHP)are used to count the weight of each component of the DSTD.It has been fou nd that the attraction subsystem is t he most important one of the three subsystems at the first hierarchical level of DSTD,which means that tourist attractions are always the principal factors for regional tourism development,even in develo ped regions.But it is also noteworth y that the significance of the attraction subsystem is not dominant in the DSTD.At the sec ond hierarchical level,the physica l attraction subsystem rank No.1,while the weight of the non-physical attraction subsystem is just a little larger t han the weight of the hardware subsystem and that of software subsystem.And the weights of the three components in the medium subsystem are similar.The top 3factors at the third hierarchical level are scenic spot,location and regional econ omic impact.The result verifies the conclusions of qualitative analysis,which depends on the market research and the study of historical date,that the most imp ortant compo-nent of the DSTD in Foshan is the impact of the developed economy.Knowing t he weight of each component of the DST D can be helpful to make out the most use ful force,furthermore to determine the future orientation for regional tourismdevelop-ment.

Endpoint Estimates for Hardy Operator's Conjugate Operator with Power Weight on n-Dimensional Space

In this paper, we establish two integral inequalities for Hardy operator＇s conjugate operator at the endpoint on n-dimensional space. The operator Hn is bounded from Lxα1 （Gn） to Lxβq （Gn） with the bound explicitly worked out and the similar result holds for Hn＊.

Novel Oxygen Storage Components Promoted Palladium Catalysts for Emission Control in Natural Gas Powered Engines

A three-way catalyst comprised novel oxygen storage components for emission control in natural gas powered engines was prepared. The addition of novel oxygen storage components to the Pd/γ-Al2O3 catalysts resulted in improved activities of the fresh and aged catalyst by lowering the light-off temperature for methane in natural gas engines exhaust.

Genetic analysis for brix weight per stool and its component traits in sugarcane (Saccharum officinarum)

Brix weight per stool (BW) of sugarcane is a complex trait, which is the final product of a combination of many components. Diallel cross experiments were conducted during a period of two years for BW and its five component traits, in- cluding stalk diameter (SD), stalk length (SL), stalk number (SN), stalk weight (SW), and brix scale (BS) of sugarcane. Phenotypic data of all the six traits were analyzed by mixed linear model and their phenotype variances were portioned into additive (A), dominance (D), additive×environment interaction (AE) and dominance×environment interaction (DE) effects, and the correlations of A, D, AE and DE effects between BW and its components were estimated. Conditional analysis was employed to investigate the contribution of the components traits to the variances of A, D, AE and DE effects of BW. It was observed that the heritabilities of BW were significantly attributed to A, D and DE by 23.9%, 30.9% and 28.5%, respectively. The variance of A effect for BW was significantly affected by SL, SN and BS by 25.3%, 93.7% and 17.4%, respectively. The variances of D and DE effects for BW were also significantly influenced by all the five components by 5.1%～85.5%. These determinants might be helpful in sugarcane breeding and provide valuable information for multiple-trait improvement of BW.

Design of a Regenerative Auxiliary Power System for Service Vehicles

This paper presents a RAPS,namely the regenerative auxiliary power system,for the vehicle with special accessory power systems.Taking city buses and delivery trucks as examples,service vehicles keep engines idling to power their auxiliary devices(e.g.,refrigeration systems and hydraulic pumps).The potential fuel savings brought on by the electrification of these auxiliary systems are first quantitatively analyzed over a typical drive cycle for a delivery truck.The RAPS is then designed,and its components are sized in accordance with the objectives of compactness and cost-effectiveness.By introducing the proposed RAPS into a conventional delivery truck with an internal combustion engine,the powertrain can be treated as a hybrid because of adding an extra battery.As a result,to pursue a high overall efficiency,a holistic controller is presented for determining how and when to recharge the battery while minimizing the auxiliary system’s power consumption.More importantly,the proposed RAPS saves about 7%fuel when compared with consumption by conventional service vehicles.