Deploying high penetration of variable renewables represents a critical pathway for deep decarbonizing the power sector. The conflict between their temporal variability and limited system flexibility has been largely ignored currently at planning stage. Here we present a novel capacity expansion model optimizing investment decisions and full-year, hourly power balances simultaneously, with considerations of storage technologies and policy constraints, such as carbon tax and renewable portfolio standards (RPS). Based on a computational efficient modeling formulation, all flexibility constrains (ramping, reserve, minimum output, minimal online/offline time) for the 8760-hour duration are incorporated. The proposed model is applied to the northwestern grid of China to examine the optimal composition and distribution of power investments with a wide range of renewable targets. Results indicate that the cost can increase moderately towards 45% of RPS, when properly designing the generation portfolio: prioritizing wind investments, distributing renewable investments more evenly and deploying more flexible mid-size coal and gas units. Reaching higher penetrations of renewables is expensive and the reductions of storage costs are critically important for an affordable low-carbon future. RPS or carbon taxes to reach a same target of emission reduction in China will result in similar overall costs but different generation mixes.

The increasing penetration of renewable generation increases the need for flexibility to accommodate for growing uncertainties. The level of flexibility is measured by the available power that can be provided by flexible resources, such as dispatachable generators, in a certain time period under the constraint of transmission capacity. In addition to conventional flexible resources, energy storage is also expected as a supplementary flexible resource for variability accommodation. To aid the cost-effective planning of energy storage in power grids with intensive renewable generation, this study proposed an approach to determine the minimal requirement of power capacity and the appropriate location for the energy storage. In the proposed approach, the variation of renewable generation is limited within uncertainty sets, then a linear model is proposed for dispatchable generators and candidate energy storage to accommodate the variation in renewable generation under the power balance and transmission network constraints. The target of the proposed approach is to minimize the total power capacity of candidate energy storage facilities when the availability of existing flexible resources is maximized. After that, the robust linear optimization method is employed to convert and solve the proposed model with uncertainties. Case studies are carried out in a modified Garver 6-bus system and the Liaoning provincial power system in China. Simulation results well demonstrate the proposed optimization can provide the optimal location of energy storage with small power capacities. The minimal power capacity of allocated energy storage obtained from the proposed approach only accounts for 1/30 of the capacity of the particular transmission line that is required for network expansion. Besides being adopted for energy storage planning, the proposed approach can also be a potential tool for identifying the sufficiency of flexibility when a priority is given to renewable generation.

The ever-growing scale of offshore wind power integration has led coastal provincial power grids to face the common issue of insufficient AC grid structure capacity. An effective solution involves constructing an offshore–onshore mono–bipolar hybrid high voltage DC (HVDC) system by integrating an offshore wind monopolar HVDC with an onshore embedded bipolar HVDC. Firstly, the limitations of existing AC structures in coastal grids when undertaking offshore wind power integration are analyzed through N-1 security verification, and the applicability of conventional power evacuation approaches is assessed from both theoretical and practical engineering standpoints. Subsequently, an offshore–onshore mono–bipolar hybrid HVDC system is proposed. Meanwhile, based on operational requirements and the analysis of the structural features, a coordinated control strategy for the hybrid HVDC system under both symmetric and asymmetric operation modes is designed. Finally, a simulation model is built on the PSCAD/EMTDC platform to verify the feasibility of the hybrid HVDC system control strategy in the coastal power grid and the effectiveness of the system to improve the wind power consumption capacity of the coastal power grid.

The rising integration of renewable energy sources has resulted in a diminished capacity for voltage support within the system, which is characterized by low inertia and a reduced short circuit ratio (SCR). In order to improve grid strength and enhance the capacity for renewable energy integration, an initial analysis was conducted on the grid support capabilities of grid-forming (GFM) stations, followed by an investigation into how grid strength influences the dominant operational modes of GFM converters. Subsequently, leveraging the definition of the multi-infeed short circuit ratio, a calculation method for the SCR, applicable to new energy base stations featuring GFM substations, is developed. Additionally, a strategic approach to optimal location selection and sizing of these substations aimed at enhancing the SCR within new energy grids is proposed, with the model being solved through genetic algorithms. Finally, the effectiveness of the proposed method is verified based on the IEEE39-node system and a real new energy station. The results show that the system strength is greatly improved after the optimized configuration of the GFM equipment, and the maximum tolerable space of 90% new energy stations reaches 95% of the theoretical maximum tolerable space of each new energy station.