Research On Dispatch Model And Method Of Microgrid

As an effective organization form of distributed generators, microgrid can notonly take full advantage of the distributed generation technology on resourceconservation and environmental protection, but also effectively solve the technicaland management problems when interconnected to the grid. However, it still needs asystematic and effective method for microgrid’s energy management and optimization.In this paper, the dispatch optimization model and method for microgrid are studied toaddress this issue.(1) Taking both the variability of system composition and the complexity ofenergy flow into consideration, the quasi-steady-state models are constructed for themultiple types of distributed generators, distributed energy storages and distributedheaters embedded in microgrid. To lay the foundation for microgrid dispatchoptimization model, the typical devices in microgrid are classified and elaborated withtheir component models in quasi-steady state. On the basis of analyzing the typicalmicrogrid composition and structure, a general ‘bus-based structure’ is proposed formicrogrid description. By adopting the bus-based structure, the composition, structureand energy flow of the microgrid system are presented clearly, resolving thecontradiction between the facility independence and system complexity. Meanwhile,the gap between system description and modeling is bridged, which is beneficial tothe realization of streamlined and automatic procedure of general modeling.(2) To address the complex optimal dispatch issue of integrated microgrid systemcontaining combined cooling, heat and power (CCHP) system, a bus-structure basedgeneral dispatch optimization model and method is proposed based on the quasi-steady-state models of microgrid devices and the energy flow description method withbus-based structure. Taking the typical microgrid economic dispatch problem asexample, through the analysis and disposal of the three basic components of targetfunction, optimization variables and constraints, the process of the microgrid dispatchoptimization modeling is elaborated in detail. In accordance with the characteristics ofmicrogrid economic dispatch model, mathematical programming method andintelligent algorithms are selected to solve the model in the influence analysis ofdispatch strategies, device models and electricity price mechanism. (3) Furthermore, the bus-structure based dispatch optimization model is extendedto combine with multi-objective optimization, stochastic optimization and combineddispatch and design optimization, which enriches the system of dispatch optimizationmodels. By means of constructing the multi-objective dispatch optimization model,the stochastic dispatch optimization model and the two-layer optimization model fordispatch and design, the influence of several factors on microgrid dispatch schedulingare studied, including microgrid environmental cost, uncertain factors and systemconfiguration, and the generality and robustness of the bus-structure based dispatchoptimization model is verified. Focusing on the three dispatch optimization modeltypes above, through the combinations of the Pareto-optimal and initial-point guidetechniques, Monte Carlo simulation and generic algorithm, and multi-objectiveevolution algorithm and mathematical programming method, the model-solvingcapability and optimization effects are effectively improved.