For the future development of an integrated energy system (IES) with ultra-high penetration of renewable energy, a planning model for an electricity-hydrogen integrated energy system (EH-IES) is proposed with the considerations of hydrogen production and storage technologies. In this EH-IES, a reasonable power to heat and hydrogen (P2HH) model with startup/shutdown constraints and a novel model of seasonal hydrogen storage (SHS) are proposed for the first time. To cope with the challenges faced by EH-IES, we use a combination of stochastic and robust optimization approaches to address the generation-load uncertainties, making the planning results robust. The N-1 contingency of crucial devices is further considered to make the system reliable. Additionally, the effects of the annual ratios of different seasons on the optimal allocation and operation of SHS are investigated. The min-max-min model with binary variables is solved by a nested column-and-constraint generation algorithm. Finally, case studies verified the advantages and effectiveness of the proposed model and planning method.

To unlock the potential of flexible resources, a multi-time-scale economic scheduling strategy for the virtual power plant (VPP) to participate in the wholesale energy and reserve market considering large quantity of deferrable loads (DLs) aggregation and disaggregation is proposed in this paper. For the VPP multi-time-scale scheduling including day-ahead bidding and real-time operation, the following models are proposed, namely, DLs aggregation model based on clustering approach, economic scheduling model considering DLs aggregation, and DLs disaggregation model satisfying consumers' requirements, respectively. The proposed strategy can realize the efficient management of massive DLs to reduce the energy management complexity and increase the overall economics with high computation efficiency, which indicate its promising application in the VPP economic scheduling.

This paper proposes an optimal distributed control strategy for the coordination of multiple distributed generators in an islanded microgrid (MG). A finite-time secondary frequency control approach is developed to eliminate the frequency deviation and maintain accurate active power sharing in a finite-time manner. It is demonstrated that the traditional distributed control approach with asymptotical convergence is just a special case of the proposed finite-time control strategy under the specific control parameter settings. Then, a secondary voltage control approach is presented to regulate the average voltage magnitude of all distributed generators to the desired value and achieve accurate reactive power sharing. The implementation of the proposed distributed control strategy only requires information exchange among neighboring local controllers through a sparse communication network. Simulations with an islanded MG testbed built in MATLAB/Simulink are conducted to validate the effectiveness of the proposed distributed control strategy.

Numerous small-capacity distributed energy resources (DERs) pose technical challenges and increase the management complexity for power system operators. This article proposes an aggregate operation model to efficiently manage a large number of DERs with heterogeneous parameters. The aggregate operation model includes the approximate feasible region and the equivalent operational cost function. First, considering the coupling of power, energy, and regulation service, the operational flexibility of multiple categories of DERs is modeled by a general polytope. Second, by scaling and translating a basic homothetic polytope, a maximum inner aggregation approach is formulated to exploit the potential flexibility of DERs and guarantee solution feasibility. The uncertainty of DERs is modeled by the distributionally robust chance-constrained program (DRCCP), and the equivalent cost function of the DER aggregator is rigidly derived. Last, this study theoretically explains that the aggregate feasible region can be enlarged by introducing the DER clustering process, and a spectral clustering algorithm based on the multi-scale similarity metric method is developed to classify DERs into different aggregators. Numerical simulation results indicate the great potential of the proposed method to enhance system operational flexibility with high computational efficiency.

In view of the plurality of ac and dc microgrids connected to the power grid, this paper proposes a bi-level two-stage robust optimal scheduling model for ac/dc hybrid multi-microgrids (HMMs). In this model, the ac/dc HMM system is divided into two interest bodies, called the utility level and supply level, and two-stage robust (also called adaptive robust) optimal scheduling is carried out considering the uncertainties in each level. For the mutual interaction between the two bodies, power constraints and deviation penalties of the interaction lines are introduced in the model to realize bi-level coordinated scheduling and obtain a unified robust dispatch scheme of ac/dc HMMs. The column-and-constraint generation algorithm is used to convert the Min-Max-Min problem of each level into a two-stage mixed-integer linear programming problem, which can be solved quickly and effectively. Case studies verify the rationality and validity of the proposed model and the solving procedure.

Wind power consumption is often curtailed by the inflexible operation of combined heat and power (CHP) units due to the strong coupling relationship between power generation and heating supply. Besides, the time delay of district heating network and indoor temperature usually affects the operation plan of the district heating system (DHS) heavily. Hence, a practical CHP-DHS model and multiregional coordinated operation strategy based on model predictive control are developed for planning and operating this CHP system. The thermal characteristics of demand side such as the thermal inertia of buildings and thermal comfort are taken into consideration. Three types of heat source are considered: CHP units, electrical boilers, and heat storage tanks. The objective of the optimization is to minimize the overall generation costs of CHP units and conventional thermal power units. Part of real provincial power system and a municipal DHS in the Northeastern China are used in this case study. The results show that the proposed method has better performance in wind power integration and indoor temperature control.