Intelligent Power Utilization Research Articles

Feature Selection and Energy Management in Wireless Sensor Networks using Deep Learning

In wireless sensor networks, when the available energy sources and battery capacity are extremely constrained, energy efficiency is a major issue to be adressed. One of the main goals in the design of wireless sensor networks (WSNs) is to maximize longevity of battery life. Designers can benefit from the use of intelligent power utilization models to accomplish this goal. These models seek to decrease the number of chosen sensors used to record environmental measures in order to minimize power utilization while retaining the acceptable level of measurement accuracy. In order to simulate wireless sensor networks, we looked at real world datasets. Our simulation findings demonstrate that the suggested strategy can be used to accomplish significant goals by using the right number of sensors using deep learning, extend the lifespan of the wireless sensor networks.

Research on Non-intrusive Load Decomposition Based on FHMM

Non-intrusive load monitoring and decomposition, as one of the important parts of intelligent power utilization system, can deeply analyze users’ internal load components and obtain user’s electricity consumption information from different scales, which is of great significance to users and power companies. In this paper, a non-intrusive load decomposition method based on factorial hidden Markov model using low frequency data is proposed. Kmeans-II algorithm is used to cluster the working state of a single load, the results of which are used to calculate the parameters of the HMM for individual load model. The total load model is represented by a factorial hidden Markov model, which transforms the load decomposition into an optimization problem with maximum probability. The improved Viterbi algorithm based on event detection is proposed to solve this optimization problem, so as to obtain the working state sequence and realize load decomposition. Finally, the correctness and practicability of the method are verified by an example.

Research on Development Ideas of Customer-side Energy Internet Business of Power Grid Enterprises Based on SWOT Analysis Method

In recent years, the concepts and practices of smart cities and “Internet plus” smart energy have mushroomed, greatly promoting the development and application of customer-side energy Internet business and stimulating users’ diversified and personalized demand for interactive services of intelligent power utilization. Intelligent power utilization, as the core of the interactive service system, serves as a bridge between power supply departments and customers. Its construction has a direct impact on the efficiency, economic operation and orderly electricity consumption of power grids. In the context of the increasingly intelligent power grid and complex load structure, this paper analyzed the development trend of energy Internet and adopted SWOT to reveal the strengths, weaknesses, opportunities and challenges of power grid enterprises in developing energy Internet, explore their development ideas on energy Internet businesses, and facilitate their development of energy Internet.

Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs) based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

Multi-Mode Intelligent Power Utilization System with Two-Way Shiftable Feature and Its Implementation

Multi-Mode Intelligent Power Utilization System with Two-Way Shiftable Feature and Its Implementation

An Intelligent Power Utilization Strategy in Smart Building Based on AIWPSO

Abstract This paper presents a strategy for intelligent power utilization in smart building based on particle swarm optimization with adaptive chaotic inertia weights (AIWPSO) to minimize electric cost and maximize user's comfort. Suppose that photovoltaic (PV) generation, batteries, micro turbines, controllable loads and uncontrollable loads exist in smart building. The proposed AIWPSO algorithm used in solving the intelligent power utilization model can further improve the performance compared with PSO algorithm in terms of convergence speed and accuracy as well as the global searching ability because of the chaotic characteristics and adaptive nature provided by the success rate which can provide the state information of the swarm and help them adjust the inertia value for better position. The effectiveness of AIWPSO is evaluated and compared with the standard PSO, and the simulation results demonstrate the effectiveness of the proposed intelligent power utilization strategy, which can reduce electric cost and increase user's comfort through optimally operate power equipments and appliances according to self demand.

Design of Interactive Intelligent Family Utilization System in Smart Grid

Intelligent power utilization is an important part in the construction of smart grid, its outstanding characteristic is interaction between power grid and demand side. Based on the demand of family intelligent power utilization, this paper analyzes the significance of bilateral interaction system construction, proposes the design scheme of interactive family intelligent power utilization system to satisfy the users various and individual demands, designs intelligent display client software. The system integrating power flow, information flow and business flow is established in order to support new power supply and demand relationship between grid and users and ensure the QoE (Quality of Experience) and optimize the configuration of assets of power grid.