# Research on Renewable Energy Planning Considering the Flexible Region of the Microgrid
## 1 Introduction  
With the development of human society, energy consumption has increased year by year. The consumption of fossil energy directly leads to an energy crisis and environmental protection problems. The application of renewable energy in a microgrid can effectively alleviate fossil energy consumption and reduce the environmental pressure. A microgrid is an effective strategy to cope with these two challenges [1]. Meanwhile, due to the intermittence and volatility of renewable energy, energy storage [2, 3] and demand side response, resources are needed in the microgrid to reduce the adverse effect on renewable energy in the distribution network. Therefore, how to allocate renewable energy in the microgrid has become an urgent problem to be solved. In the existing research, the configuration of distributed energy in the microgrid has different objectives, such as economic, reliability, security and stability objectives. The authors of [4] established a life cycle adaptive optimal configuration scheme of a microgrid based on the economic objective and analyzed the sensitivity of key factors that determined the influence degree on the optimization results. The microgrid can operate in two ways: grid-connected operation and isolated network operation. The existing researchers also studied the optimal allocation of distributed energy in the microgrid under the two different operation modes. Under the grid-connected operation mode, the authors of [5] proposed two business models for the capacity configuration of a grid-connected microgrid, referring to the existing distributed photovoltaic operation mode, and optimized the wind/solar/storage configuration in the microgrid with the objectives of economy, reliability and renewable energy utilization. For the distributed energy configuration in the microgrid under the isolated networkoperation mode, the authors of [6] established an optimization model of the microgrid economy, considering various elements, and studied the optimal of the capacity configuration of the distributed power supply in the microgrid on the independent island. Meanwhile, due to the access of distributed energy, the operation efficiency of the microgrid can be improved by the optimal configuration of the distributed energy and the management of the demand side. The authors of [7] studied the bi-level optimization configuration method of an AC-DC microgrid considering the operation optimization of the microgrid, the distributed power generation and the demand side response to improve the economy and stability of the microgrid, and analyzed the influence of the intermittence and uncertainty of renewable energy generation on the optimal allocation of the microgrid. The distribution network planning in the market is more difficult than that in the monopoly mode [8]. Demand side response is an effective means of load regulation under the market mechanism. Demand side response refers to the user's response according to the current electricity price or incentive mechanism, so as to change the original power consumption mode and meet the demand of the power grid. It is verified that the demand side response can effectively reduce the power grid cost and save energy consumption in [9]. The existing configuration method of distributed generation in the microgrid is based on the definition of a microgrid by the U.S. Department of Energy. According to the definition, there are four characteristics for a microgrid: it has a clear electrical boundary, it is a single controllable whole, it can connect with the large grid or operate isolated and it contains distributed power and load. A clear electrical boundary can ensure that each microgrid is controlled as a whole to keep the power balance of the load and the distributed generation. In the existing research, most of the research on microgrids is based on the fixed boundary, so that the configuration of distributed generation in the microgrid can guarantee the power balance between the power and load of each microgrid in the distribution network.