The electricity output of combined heat and power (CHP) units is constrained by their heat output corresponding to customers' heat demand, which makes it difficult for the CHP units to frequently adjust their electricity output. Therefore, additional balancing power is required to integrate the variable wind power in the CHP-based heat and electricity integrated energy system (HE-IES). This paper expands the demand response (DR) concept to the HE-IES. A comprehensive DR strategy combining energy substitution and load shifting is first developed to exploit the demand flexibility of smart buildings. Besides electric balancing power, heat balancing power is also provided to relax the production constrains of CHP units. Moreover, a real-time DR exchange (DRX) market is developed where the building aggregators are stimulated to adjust buildings' energy consumption behaviors and provide the required balancing power. Compared with the existing day-ahead DRX market, the real-time DRX market can balance the very short-term wind power fluctuation and reduce price spikes. Additionally, a novel optimum feasible region method is proposed to achieve the fast clearing of the DRX market to meet the higher requirement for clearing speed in the real-time market. Simulation results verify the advantages of the proposed technique.

With the development of energy intelligent technology, integrated energy system (IES) has been widely used in the field of energy supply. While the IES significantly improves energy efficiency, the interaction between different energy systems may also bring multiple operational risks to the reliability of the energy supply, which necessitates an effective IES reliability assessment technique. Considering the dynamic characteristics of gas and heat systems can reduce energy losses during contingencies, which provides an instrument to improve the IES reliability. This paper for the first time contributes to a novel emergency dispatch formulation based on the IES dynamic optimal energy flow (OEF). A reliability assessment framework for IES is proposed by combining the IES dynamic OEF and Monte Carlo simulation (MCS). By taking into account the emergency dispatch formulation, the unreliability degree of IES can be mitigated. The IES dynamic OEF model is transformed into a linear programming problem under reasonable assumptions and simplifications due to its high degree of nonlinearity. Several novel reliability indices for heat system are proposed by incorporating the impacts of the IES dynamic characteristics on the reliability. The proposed model and method are validated by using an integrated gas, power and heat testing system.

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.