Research On Optimization And Control Strategies Of Microgrid With Multiple Distributed Energy Resources

Microgrid is one of the new conceptual power systems for effective integration ofdistributed generations (DGs), loads and energy storage devices. It is benefical to connect therenewable energy sources with the main power grid by means of microgrid. This new grid,which take fully use of DGs, is an important way to achieve high efficient, environmentalfriendly and high quality power supply in future. As a useful supplement to the main powergrid, microgrid attracts wide attention all over the world once it was proposed. This paper hasstudied the optimization problems of microgrid with multiple distributed energy resourcesalong the ideas of planning, dispatch and control. Main research works and innovative pointsof this dissertation are as follows:1) Optimal allocation of controllable distributed generation (CDG) in a microgrid systemwith wind power generation is studied. A new method based on loss sensitivity factor andvoltage stability index is proposed to determine the candidate bus sets for CDG installation.An optimal configuration model of CDG considering the effects of load factors (load type,load level and uncertainty) and energy policy is built, aiming at reduction of the sum ofinvestment cost, fuel cost, maintenance cost, electricity purchasing cost and emission cost.Random variables are introduced to represent the wind turbine output and load power,accordingly, the operating constraints are expressed by means of probability. Probabilisticload flow method based on semi-invariant and Gram-Charlier series for microgrid is used tojudge whether the planning scheme satisfies the chance constraints, and artificial bee colonyalgorithm is applied to search the optimal allocation scheme, thus the simultaneousoptimization between type, site and size of CDG is achieved.2) From the perspective of demand side response, economic dispatch problem of microgrid with battery swap station (BSS) is studied. A new bi-level optimization model formicrogrid operation considering the benefit of BSS is bulit. Decision-making body of theupper-level model and lower-level model is microgrid dispatch center and BSS operator,respectively. The former is devoted to minimizing microgrid power generation costs, and thelatter is aimed at maximizing BSS profit. Interaction between the upper and loweroptimization model is implemented by using the personalized price supplied by microgrid.Invasive weed optimization algorithm and CPLEX commercial solver are employed to solvethe developed optimization problem, and output power of controllable microsources as wellas personalized price are obtained, then the win-win situation is achieved.3) From the perspective of energy supply, optimal dispatch for microgrid with multipledistributed energy resources is researched. A multi-objective dynamic dispatch model basedon chance constrained programming is established for microgrid, aiming to minimize the totalelectricity costs, total greenhouse gas emissions and maximum node voltage deviation in aday. This model not only consider the internal connection of optimization variables atadjacent time points but also consider the uncertain factors related to wind generation andload demand. The scheduling scheme is allowed if the constraints of both node voltage andbranch power flow are satisfited at a certain confidence level. A method based on probabilisticload flow and clone selection algorithm is proposed to solve the multi-objective modeldirectly. In the process of solving, a hybrid mutation strategy composed of fixed step andvariable step is adopted to improve the diversity of solution. Pareto optimal set satisfying theconstraints is obtained repeatedly through cloning, mutation, selection operations, and fuzzymembership is used to calculate the overall satisfaction degree for selecting the optimalsolution from Pareto optimal set.4) Operational control strategies of AC microgrid are researched. A AC microgridcomposed of wind turbine (WT), fuel cell (FC) and battery (BAT) is studied, and itsoperational control strategies considering the characteristics of WT, FC and BAT are designedfor islanded and grid-connected operations of microgrid. When microgrid operates in islandedmode, voltage source inverter control based on voltage amplitude and phase angle droopcontrol is adopted by parallel-connected BAT to share load power according to thepredetermined proportion, and to provide the voltage and frequency support for microgrid. When microgrid operates in grid-connected mode, the control method of BAT is switchedfrom voltage source inverter control to PQ control to output active and reactive poweraccording to the given value. PQ control is adpoted by FC under the two above-mentionedmodes, and the FC operating state is decided by the state of charge of BAT when microgrid ison isolated island operation mode. In the process of designing controllers for the microsourcegrid-side converters, using inner sliding mode current controller instead of PI currentcontroller to enhance the control performance.5) Operational control strategies of islanded DC microgrid are researched. A low-voltageunipolar-type DC microgrid composed of photovoltaic array (PVA), FC and supercapacitor(SC) is studied, and the centralized control strategy and distributed control strategyconsidering the characteristics of PVA, FC and SC is designed respectively for centralizedsupply power scheme and distributed power supply scheme. Perturb and observe method isapplied to track the maximum power of PVA. Slope limiter is used to limit the change rate ofFC output power, thus prevent FC from fuel starvation. In centralized control strategy, theinner sliding mode current controller is applied to SC for its rapid charging and discharging tostabilize DC bus voltage. In distributed control strategy, the different operation status ofmicrogrid can be automatically switched by using DC bus voltage signaling.The results of relevant examples show that the optimization models and operationalcontrol strategies for microgrid proposed in this dissertation are rational, and the proposedoptimization algorithms are effective to solve the aforementioned optimization models.