To solve the risks brought by the uncertainty of renewable energy output and load demand to the virtual power plant dispatch, a multi-objective information gap decision theory (IGDT) dispatching model for virtual power plants considering source-load uncertainty under vehicle-to-grid (V2G) is proposed. With the lowest system operating cost and carbon emission as the optimization objectives, the multi-objective robust optimization model for virtual power plants is constructed based on the uncertainties of wind output, photovoltaic output and load demand guided by the time of use price. The weights of uncertainties quantify the effects of uncertainty factors. The adaptive reference vector based constrained multi-objective evolutionary algorithm is used to solve it. The weight coefficients, evasion coefficients of uncertainties and the penetration rate of electric vehicles are analyzed for the optimal dispatching of the virtual power plant. The algorithm results show that the method can effectively achieve load-side peak shaving and valley filling and has superiority in terms of economy, environmental benefits, robustness and stability.

Cooperating with distributed energy storage, distributed generation is with the potential of supply load stably under both normal and failure periods of distribution network. Therefore, distributed generation has not only electricity value, but also capacity value. The capacity value can be characterized by credible capacity index. However, the uncertainty of the distributed generation output and the sequential characteristics of energy-storage operation must be considered during a united credible capacity evaluation. A united credible capacity evaluation method of distributed generation and energy storage based on active island operation is proposed. The proposed method carries out day-ahead economic dispatching under a normal state and island partition under a fault state, alternately, to realize accurate reliability calculation, which is the key link of credible capacity searching. The main work is as follows. First, a day-ahead economic dispatching model under normal state is established to obtain the sequential remaining electricity information of energy storage. Second, the models of maximum island partition and optimal island rectification are established based on electricity sufficiency and power balance information. By solving the maximum island partition and optimal island rectification models alternately, optimal island partition schemes under the fault state could be achieved. Then, the convergence criterion based on variance coefficients instead of artificial selection is designed in reliability calculation. Finally, the united credible capacity of distributed generation and energy storage is evaluated in the PG&E 69-bus system. It is found that credible capacity value increases by 23%, 53%, and 61%, respectively, under the energy storage allocation ratios of 20%, 30%, and 40%. It can be seen that the integration of energy storage makes a significant impact on distributed generation credible capacity value.