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.

This paper presents a model predictive control (MPC)-based coordinated voltage control scheme for distribution networks with high penetration of distributed generation (DG) and energy storage. In this scheme, the DG units, energy storage devices, and on-load tap changer are optimally coordinated to maintain all bus voltages in the network within a permissible range. To better coordinate the economical operation and voltage regulation, two control modes are designed according to the operating conditions. In the preventive mode, the DG units operate in the maximum power point tracking mode. State-of-charge of energy storage system (ESS) units and power outputs of DG and ESS units are optimized while maintaining the voltages within the feasible range. In the corrective mode, active power curtailment of DG units is also used as a necessary method to correct the severe voltage deviations. The voltage sensitivity coefficients with respect to the power injections and tap changes are updated in real time using an analytical sensitivity calculation method to improve the computation efficiency. A test system consisting of two 20-kV feeders fed from the same substation based on a real distribution network was used to validate the proposed coordinated voltage control scheme under both normal and large-disturbance conditions.

This paper considers options for a future Indian power economy in which renewables, wind and solar, could meet 80% of anticipated 2040 power demand supplanting the country’s current reliance on coal. Using a cost optimization model, here we show that renewables could provide a source of power cheaper or at least competitive with what could be supplied using fossil-based alternatives. The ancillary advantage would be a significant reduction in India’s future power sector related emissions of CO₂. Using a model in which prices for wind turbines and solar PV systems are assumed to continue their current decreasing trend, we conclude that an investment in renewables at a level consistent with meeting 80% of projected 2040 power demand could result in a reduction of 85% in emissions of CO₂ relative to what might be expected if the power sector were to continue its current coal dominated trajectory.

China can use the latest offshore wind technologies to cost-competitively supply a notable portion of its energy demand.

Offshore wind power, with accelerated declining levelized costs, is emerging as a critical building-block to fully decarbonize the world’s largest CO₂ emitter, China. However, system integration barriers as well as system balancing costs have not been quantified yet. Here we develop a bottom-up model to test the grid accommodation capabilities and design the optimal investment plans for offshore wind power considering resource distributions, hourly power system simulations, and transmission/storage/hydrogen investments. Results indicate that grid integration barriers exist currently at the provincial level. For 2030, optimized offshore wind investment levels should be doubled compared with current government plans, and provincial allocations should be significantly improved considering both resource quality and grid conditions. For 2050, offshore wind capacity in China could reach as high as 1500 GW, prompting a paradigm shift in national transmission structure, favoring long-term storage in the energy portfolio, enabling green hydrogen production in coastal demand centers, resulting in the world’s largest wind power market.