# Joint Acquisition Time Design and Sensor Association for Wireless Sensor Networks in Microgrids
## 1 Introduction  
Electricity is mainly generated from fossil fuels such as coal, oil and natural gas. These sources are often referred to as traditional or non-renewable energy sources [1]. However, these traditional modes of power generation have caused severe environmental pollution and ecological damage. The sustainable modern energy sources have been used to solve these problems. Consequently, microgrids are created as a hybrid system that combines traditional and modern energy sources. The microgrid is an energy generation device consisting of solar, wind and fuel cells, which is distributed in communities. In recent years, microgrids have attracted more and more attention. Microgrids are an integrated energy system composed of interconnected loads and distributed energy. As a system, the microgrid can operate in parallel with the grid or on an island. If the power system fails to connect to the microgrid or is geographically isolated, the microgrid operates in island mode [2]. Therefore, how to control these distributed energy devices to ensure the safe and reliable operation of the power system is an urgent problem [3]. Typically, microgrids are located in the vicinity of consumers or remote areas, and their operational status needs to be monitored in real-time. Thus, sensor nodes can be deployed around the microgrid, and the information collected about the status of the microgrid will be transmitted to the energy management system for processing [4]. The implementation of wireless sensor network (WSN) in microgrids has become a hot research topic. WSN has some advantages, including low cost, dynamic networking, large-scale deployment, scalability, etc. WSN can effectively achieve the acquisition and transmission of the status data of each object in the microgrids, and realize the monitoring and diagnosis of related information of the microgrids. Furthermore, in terms of a smart city's energy, microgrid and blockchain technology are combined to build a consumer community network. Then, multiple wireless sensor nodes are used to manage the large amount of data generated in the network, improving the microgrid network's efficiency [5]. Additionally, sensors and actuators and wireless communication technology can transmit measurement data and command messages. The wireless sensor and actuator network are a promising scenario to realize the intelligent management of microgrids and smart grids [6]. Under the condition of limited energy, how to reduce the distortion of transmitted data and extend the lifetime of the WSN is a crucial concern. In [7], an asynchronous wake-up scheduling scheme for a WSN is proposed based on heterogeneous arbitration while finding the trade-off between delay and energy consumption. Innovative DC grid technology based on a WSN, combined with power-system-related solutions, provides a reliable monitoring and fault detection system for the power system. It is necessary to utilize sensors to monitor changes in transmission parameters (such as voltage, current and power) [8]. The WSN can replace part of the communication infrastructure of the microgrids and be deployed among the units of the microgrids to ensure the real-time data flow [9]. However, it is quite important to effectively control the topology of sensor nodes in microgrids, which contributes to a balance between energy consumption and data satisfaction of sensor nodes. Motivated by the above illustrations, we propose an energy-efficient algorithm by jointly optimizing acquisition time design and sensor node association. The energy consumption of sensor nodes is composed of acquisition energy consumption and transmission energy consumption. The longer the data acquisition time, the higher the monitoring accuracy and data satisfaction. However, this will also lead to data redundancy and excessive energy consumption so that a weighted balance is needed between the sensor's energy consumption and the satisfaction of the data. The main contributions of this paper can be summarized as follows:  
1.