Due to the lack of support from the main grid, the intermittency of renewable energy sources (RESs) and the fluctuation of load will derive uncertainties to the operation of islanded microgrids (IMGs). It is crucial to allocate appropriate reserve capacity for the economic and reliable operation of IMGs. With the high penetration of RESs, it faces both economic and environmental challenges if we only use spinning reserve for reserve support. To solve these problems, a multi-type reserve scheme for IMGs is proposed according to different operation characteristics of generation, load, and storage. The operation risk due to reserve shortage is modeled by the conditional value-at-risk (CVaR) method. The correlation of input variables is considered for the forecasting error modeling of RES and load, and Latin hypercube sampling (LHS) is adopted to generate the random scenarios of the forecasting error, so as to avoid the dimension disaster caused by conventional large-scale scenario sampling approaches. Furthermore, an optimal day-ahead scheduling model of joint energy and reserve considering riskbased reserve decision is established to coordinate the security and economy of the operation of IMGs. Finally, the comparison of numerical results of different schemes demonstrate the rationality and effectiveness of the proposed scheme and model. Index Terms--Day-ahead scheduling, risk-based reserve decision, conditional value-at-risk (CVaR), renewable energy source (RES), islanded microgrids.
This paper focuses on voltage fluctuation and the mismatch between generation and load demand caused by photovoltaic access to distribution network, using energy storage to solve negative effects brought by photovoltaic.According to the characteristics of point of common coupling (peC) photovoltaic and energy storage accessed to, extended QV bus-type is put forward in order to describe the feature of pee more reasonably. The solution of power flow calculation with QV bus-type is also shown in this paper. Furthermore, a joint day-ahead scheduling of photovoltaic-storage is put forward in core view of voltage control at pee. The two scenarios where whether the power output of energy storage system is beyond the limit are considered. When the power output beyond its limit, the bus-type is transformed. As a consequence, node voltage curve and joint power curves of photovoltaic-storage are thus gained. The result is comprehensively compared with the case where photovoltaic and energy storage operate with constant power. It shows that the strategy this paper proposed has a significant effect on suppressing voltage fluctuation, improving power flow, peak load shifting and so on.
In the islanding micro-grid operation mode, due to the lack of support from the large power grid, the voltage of the bus and each node in the network is completely supported by the cooperation of the micro-grid inverters in the grid. Therefore, the control performance of the micro-grid inverter determines the quality of the power supply voltage. This paper proposes an improved AC and DC islanding micro-grid fixed frequency current control method with variable topology. First, the neural network algorithm improved by particle swarm optimization is used as the basis to optimize the coordinated compensation control of the micro-grid to obtain the fitness value of the objective function under the positive and negative sequence potentials. Then, a control strategy for the improved AC/DC hybrid micro-grid is proposed, and the decoupling and coordinated control strategy for the output compensation of the dual filters in the islanding mode is designed. Finally, simulations and experiments verify the improved AC/DC hybrid microgrid with variable topology and achieve the goal of constant-frequency current control.
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