With the exploration of deep decarbonization around the world, the contradiction between the low-carbon operation and energy supply in energy systems has been aggravating. There is an urgent need to tap the interactive potential between source and demand sides. In view of the current lack of efficient incentive measures for low-carbon energy consumption, an integrated demand response exchange (IDRX) mechanism is proposed to promote the coordinated low-carbon dispatching on source-demand side for integrated electricity-gas system (IEGS). The value model of IDRX for emission reduction is built to measure the ability of multi-energy load aggregators (MELAs) for decarbonization, and guide the IEGS operator to trade with the appropriate MELAs. An IDRX market clearing model is established based on non-cooperative game theory to allocate the decarbonization benefits among the entities in IEGS, thereby motivating the low-carbon demand response of users. Combined with the optimal operation of carbon capture power plant and power-to-gas (CCPP-P2G) on the source side, a two-stage low-carbon dispatching model for IEGS is established. Case studies are carried out with seasonal and uncertainty scenarios to verify the effectiveness of IDRX in emission mitigation and highlight the economic benefits of the proposed low-carbon dispatching model.

With the exploration of deep decarbonization around the world, it has become a broad consensus that the carbon trading mechanism can promote the low-carbon operation of the energy system by exploring the underlying driver of emissions. The end-users, as the motivator of emission in the integrated electricity-gas system (IEGS), have not been developed so far to participate in the carbon market and help emissions abatement. This paper proposes a bi-level carbon trading scheme on demand side considering the energy consumption level of users and low-carbon demand response. In the upper-level market, an optimal step-based carbon prices customization model is built to impose differentiated incentives on users, thereby balancing the emission mitigation and social welfare. In the lower-level market, a carbon trading mechanism based on the competitive auction program is proposed, then an optimal carbon trading strategy is studied to maximize the consumer surplus and further motivate the low-carbon energy consumption. On the source side, a low-carbon dispatching model of IEGS considering the flexible carbon capture power plant and power-to-gas (CCPP-P2G) is established. Moreover, the Benders decomposition algorithm is used to solve the bi-level optimal model. Case studies verify the feasibility of carbon trading on demand side and demonstrate the environmental and economic benefits of the proposed bi-level carbon trading mechanism.

The integration of the variable renewable energies makes the operation conditions of the power system ever-changeable. Consequently, the power system operational reliability evaluation is increasingly important. This paper introduces the concept of decision-dependent uncertainty (DDU) in the operational reliability evaluation. Unlike the exogenous uncertainties, DDU reveals that the decisions of the system operation could significantly affect the resolution of the uncertainties which influence the reliability metrics. In this paper, the proposed DDU modeling method links the device reliability indices, i.e., the forced outage rate, and the operational-decision variables. The impacts of DDU on operational reliability are analyzed based on a reliability-constrained stochastic unit commitment (UC) model. An adaptive reliability improvement UC (ARIUC) algorithm is proposed to efficiently solve the problem. Case studies underline the necessity of considering DDU in power system operational reliability evaluations.

The ever-increasing penetration of renewable generation is demanding additional flexibility for the operation of power systems. In this sense, it has been proved that wind power generators (WPGs) can provide part of the required operating reserve through pitch angle control (PAC) under a deloaded strategy. Unlike conventional operating reserve sources, however, the operating reserve provided by WPGs can't always be considered reliable, which renders the power system dispatch more challenging. In this research, the reserve capacity of the WPGs is modeled considering the decision-dependent uncertainty (DDU). The random wind speed introduces uncertainty to the available reserve capacity of the WPGs while the decisions on the deloading degrees of the WPGs directly affect their coefficients between wind speed and usable wind power, making the uncertainty decision-dependent. Moreover, the operational technical limits of the WPGs and the multiple possible wind speed scenarios are also considered in the wind power reserve capacity modeling. Then, a two-stage reliability constrained stochastic economic dispatch model with WPGs’ reserve provision (SED-WRP) is developed to jointly dispatch the generation and reserve. A group-based multi-cut Benders decomposition method is applied to improve the convergence performance of the solution algorithm. Case studies are solved to quantify the impact of considering the reserve provision of WPGs and the inherent DDU in power system dispatch decisions.

With the penetration rate of distributed generator and distributed energy storage growing, the frequency stability of micro-grid is severely affected. In this paper, a self-adaptive secondary frequency regulation (FR) strategy based on virtual synchronous generator (VSG) for a micro-grid containing wind turbine, photovoltaic array, and electric vehicle cluster is proposed. First, modified VSG control is applied to renewable energy units and electric vehicle cluster, where non-error frequency regulation is realized by introducing proportional-integral control into power-frequency controller of VSGs. Secondly, the FR reserve capacity of wind turbine, photovoltaic array, and electric vehicle are predicted in real time through their respective characteristics. Then, a self-adaptive adjustment strategy for secondary FR parameters of VSGs is designed to control the FR power of VSGs according to real-time predicted FR capacity. Finally, the coordinated FR strategy of VSGs and conventional unit is proposed considering the situation of insufficient FR capacity of VSGs. Through the analysis of simulation results, the reasonability and validity of proposed self-adaptive FR strategy for multiple VSGs have been verified.