Advanced Materials Research Vols. 860-863

Abstract: With the deepening of smart grid construction, it is necessary to fully study the intelligent response behavior of residential users, enhance the power grid comprehensive service capabilities and meet the requirements of interactive marketing. According to the model analysis of residential customers comprehensive response behavior, we can get the steady-state situation of residents overall responsiveness, which is able to judge the residents responsiveness level. The homogeneity trend of residential electricitys responsiveness is very strong, as a consequence, we should establish adequate incentives to tap the potential responsiveness of the residential users.

Abstract: By using of the object-oriented technology and the knowledge representation of the production rule, this paper classifies the operation experience of grid according to the nature and builds a power grid operation experience knowledge base with active learning capability. Through application of Bayesian classifier model based on weight, it classifies the statistical data and identifies the semantic, to realize the exchange between the knowledge base and the users feedback. Using the powerful learning ability of knowledge base, it can make the operation experience knowledge base optimize its knowledge system structure while exchanging with users feedback, so that it can go on refining the operation experience base of the grid. This method can provide technical support and improve the quality of the stuff, as well as strengthen the security and stability of the grid.

Abstract: This paper briefly introduces a smart control system for power consuming network and its front-end sub-system. The front-end sub-system is developed on the Android platform, which consists of several Android applications. This paper briefly introduces the Android platform, describes the design and development of the Zigbee-based front-end sub-system of the smart control system for power consuming network, and finally gives several screen shots of the application interface.

Abstract: This paper presents an improved GSA-GA algorithm to achieve bad-data detection, identification and correction in power grid. The algorithm combines BP neural network, K-means clustering algorithm, gap statistical algorithm (GSA) and genetic algorithm together. BP neural network preprocesses the data, K-means algorithm clusters the preprocessed data and GSA algorithm determines the optimal clustering number and identifies the presence of bad data. After identifying the bad data, GA-BP algorithm is used to correct the identified data. This paper takes simulation tests to verify the proposed algorithms correctness and effectiveness based on actual grid data considering multiple types of existed bad data.

Abstract: This document focuses on the DC micro-grid photovoltaic energy storage device, the design of energy storage systems are optical storage hybrid power system which composes the photovoltaic array, battery pack, management systems, photovoltaic inverter, load and power grid. According to the characteristics of the battery and the development of the switching device control technology, the charging and discharging control strategy of battery is studied. In this paper, three-phase inverter is based on the space vector control mode that is called SVPWM, after introducing the basic principle and synthesis method of SVPWM, the on-grid and off-grid system working mode control strategy is studied. Finally the control theory develops the inverter used in the optical storage complementary power generation system, and the article builds test platform to test system, verifying the validity of the control strategy.

Abstract: As distributed energy increasing, grid-consumer interoperability (GCI) is becoming a core characteristic of smart grid. Basically consumers behavior is fuzzy and adaptive, which causes difficulty to simulating interoperability. To deal with the difficulty, a GCI simulation framework and corresponding response algorithm are proposed, and thus consumers adaptive behavior could be simulated by fuzzy inference. Simulation on IEEE-14 bus test system demonstrates the validity of the simulation framework and the response algorithm proposed.

Abstract: CAES system electromotor transient model was established from the view of equipment and the grid interface, based on Power System Analysis Software Package (PSASP). The model was divided into energy storing sub-system model part and generating sub-system model part, and the normal and abnormal dynamic characteristics after CAES connected to the grid were simulated bythis model. The validity of this model was theoretically verified by applying it into example systems and testing.,according to detecting the system responses caused by power system contingency and the sudden change of CAES characteristics. This model provides a basic platform for studying CAES system characteristics, and also provides necessary technical support to the security and stability of power system operation when integrating renewable energy into the grid.

Abstract: The combination of renewable energy and dynamic electricity pricing is an important feature of modern smart grid. Due to the dynamic electricity price and the intermittency nature of renewable energy, a local small-scaled smart grid (microgrid) needs to intelligently schedule various work loads to determine their start and end time in order to maximize the utilization of renewable energy and minimize the total electricity cost. Since the workload that can be shifted/scheduled is classified into interruptible load and non-interruptible load, in this paper we present two novel recursive scheduling strategies based on dynamic programming for both categories. The simulation experiment demonstrates that our strategies can effectively save energy expenditure and increase the proportion of renewable energy in overall energy consumption.

Abstract: The time synchronization network provides time benchmark tasks for various services in electric power system. With the development of the power grid, the applications require more and more accurate time synchronization precision. In this paper, a method of time synchronization based on adaptive filtering with a modified particle swarm optimization (MPSO-AF) was presented to satisfy the high precision and high security requirements of the time synchronization for smart grid. The modified PSO was introduced for tuning the weight coefficients of the adaptive filter to improve the filtering property. The proposed MPSO-AF hybrid algorithm can combine the advantageous properties of the modified PSO and the adaptive filtering algorithm to enhance the performance of the time synchronization. A comparison of simulation results shows the optimization efficacy of the algorithm.

Abstract: Mainly from the perspective of power grid enterprise, this paper analyzed the impact about operational factors based on balanced score card (BSC) analysis framework, sorted order of key external environmental factors by establishing interpretative structural model (ISM) , put forward to key indicators of operational warning system, and examine the result by principal component analysis. As a result, grid enterprise should pay more attention to 11 factors from 32 operational indexes.