Focused on carbon capture, utilization and storage (CCUS) technology, development of relevant policies from major developed economies in recent years are introduced. In the respective of national and local governments, relevant policies or plans for CCUS in China are reviewed and analyzed comprehensively. In the past decade, the release of these policies or plans had strongly promoted the layout and development of CCUS technology in China, and it has come into the stage of industrial demonstration. However, compared with developed economies such as the United States and the European Union, China still has a certain gap on the level of technology development and project scale, and there exist some deficiencies mainly including lack of finance and tax incentive or subsidy policies, slow construction for system of laws, regulations and standards, incomplete layout of CCUS industrial chain, and relatively weak speaking right in international cooperation, etc. In the future, it is suggested that according to the basic national conditions, on the basis of learning from the good policies and practical experience from other countries, China should speed up the research and development of low-cost, low-energy-consumption, safe and reliable CCUS technologies and the construction of industrial clusters, and deepen international cooperation. Then the leading advantage of CCUS industry development could be established gradually which is beneficial to achieve the double carbon target.

After a large number of distributed power sources such as distributed photovoltaic power and energy storage devices are connected to an active distribution network (ADN), the multiple uncertainties of photovoltaic output, load and rotating reserve capacity bring new challenges to the reliability of economic dispatching of ADN. Considering the uncertainty of photovoltaic output and load, this paper puts forward an economic optimization scheduling model of ADN with the objective function of minimizing operation cost. In this paper, the chance constrained programming (CCP) model is transformed into a deterministic mixed integer linear programming (MILP) model, which is easy to solve, by using CPLEX solver. The proposed method is verified by IEEE 33-node distribution system. The calculation results show that the proposed strategy significantly reduces the system calculation time and achieves better optimization effect, and the balance between the reliability and economy of ADN can be achieved by appropriately setting the confidence level of the probability constraint of rotating reserve capacity.

Reserve can effectively deal with the risk brought by uncertainties and ensure the safe operation of park integrated energy system (PIES). However, previous studies mainly focused on the reserve capacity of generators to deal with the risk brought by uncertainties, and did not consider the reserve role of other flexible resources such as energy storage devices. An economic scheduling model of PIES is proposed in this paper, which considers the participation of energy storage devices in reserve allocation. The reserve capacity provided by electric energy storage, diesel generator and combined heat and power (CHP) is utilize to stabilize the volatility of wind and photovoltaic power. In order to balance the influence of reserve allocation on the operation safety and economy of PIES, a reserve allocation model considering renewable energy and load uncertainties is constructed on the basis of chance constrained programming (CCP). The reserve allocation model is embedded into the day-ahead optimal scheduling model to improve the rationality of day-ahead energy and reserve decision-making plan. By using discrete step transformation and stochastic simulation method, the original non-convex CCP problem is transformed into a solvable mixed integer linear programming (MILP) problem. The simulation results show that the participation of energy storage devices in reserve allocation can improve the operation flexibility of generators, thus improving the economy of system operation. By adjusting the confidence level of the upward and downward reserve constraint, the conservative degree of the park reserve decision can be changed, thus balancing the economy and reliability requirements of the system operation.

This paper proposes to integrate carbon emission trading into peak-shaving trading, to account for the carbon variation effects produced by thermal power peak-shaving, and proposes a multi-source low-carbon peak-shaving cost accounting method. Aiming at the uncertainty of wind power, this paper uses the information gap decision theory (IGDT) to reflect the information gap between the predicted value and the actual value of wind power, and constructs an uncertainty multi-source low-carbon peak-shaving transaction optimization model. Finally, a local power grid in northwest China is selected as the simulation system to verify the correctness and validity of the proposed model. Results show that the proposed multi-source low-carbon peak-shaving transaction model can promote the integration of wind power generation, ensure all participants obtain the cooperation incremental benefits, and establish a peak-shaving transaction plan for decision makers with different risk attitudes.