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With the growth in demand for energy and the boom in energy internet (EI) technologies, comes the multi-energy complementary system. In this paper, we first model the components of the micro-energy-grid for a greenhouse, and then analyzed two types of protected agriculture load: time-shifting load and non-time-shifting load. Next, multi-scenario technology is directed against the uncertainty of photovoltaic (PV). Latin Hypercube Sampling (LHS) and the backward reduction algorithm are the two main methods we use to generate the representative scenarios and their probabilities, which are the basis for PV prediction in day-ahead scheduling. Third, besides the time of day (TOD) tariff, we present a model using real-time pricing of consumers’ electricity load, which is proposed to compare consumers’ demand response (DR). Finally, we establish a new optimization model of micro-energy-grid for greenhouses. By calculating the dispatch of electricity, heat, energy storage and time-shifting load under different conditions, the local consumption of PV and the comprehensive operational cost of micro-energy-grid can be analyzed. The results show that a storage device, time-shifting load and real-time pricing can bring more possibilities to the micro-energy-grid. By optimizing the time schedule of time-shifting load, the cost of the greenhouse is reduced.

Research on Optimal Dispatching Strategy for Micro-Energy-Grid of Protected Agriculture