A multi-energy virtual power plant can be defined as flexible cooperation of multi-energy distributed energy resources including heating and cooling devices that operates as a single entity and participates in the power markets. To exploit the potential of multi-energy distributed resources, this paper proposes a model for the aggregation of a multi-energy virtual power plant that participates in day-ahead energy and reserve markets. The reserve capacity brought by the multi-energy quick-start devices is considered in this paper, which adds binary variables to the recourse problem. The proposed model is an adjustable robust optimization problem that guarantees all possible deployment requests can be realized by the virtual power plant. Moreover, the optimal offering strategy is determined, and the total cost of the multi-energy virtual power plant is ensured to not exceed the optimal value of the objective function. A modified nested column-and-constraint generation algorithm is proposed for solving the adjustable robust optimization problem with mixed-integer recourse in specified precision efficiently compared with other KKT-based algorithms. The results from a case study of an actual industrial park demonstrate the satisfactory performance of the proposed model.

Using thermal inertia in district heating systems (DHSs) to improve the dispatch flexibility and economy of integrated heat and electricity systems (IHESs) is a research hotspot and difficulty. In most existing studies, the partial differential equations (PDEs) of thermal inertia are approximated by discrete-time models, making it difficult to accurately describe the continuous dynamic processes. In this paper, we propose a novel generalized phasor method (GPM) for thermal inertia in DHSs with constant mass flow. Based on the analytical solution of the PDEs and the Fourier transform, the intractable PDEs are transformed into a series of complex algebraic equations represented by phasors. The GPM has higher accuracy compared to traditional discrete models because it is essentially a continuous model in the time domain. Then, we present a different representation of an integrated heat and electricity dispatch (IHED) model combining a DHS model in phasor form and a traditional electrical power system model. The IHED model is a convex programming problem and can be easily solved. The effectiveness of the proposed GPM and dispatch model is verified in three test systems. Compared with traditional methods for modeling the thermal inertia, the proposed GPM is more accurate.

Massive adoptions of combined heat and power (CHP) units necessitate the coordinated operation of the power system and district heating system (DHS). Exploiting the reconfigurable property of district heating networks (DHNs) provides a potentially cost-effective solution to enhance the flexibility of the power system by readjusting the configuration for heat supply, which has not been addressed in the literature. To address this issue, a unit commitment considering combined electricity and reconfigurable heating network (UC-CERHN) is proposed in this paper to coordinate the day-ahead scheduling of power system and DHS. The DHS is formulated as a nonlinear and mixed-integer model considering the reconfigurable DHN. To make the commitment problem tractable, an auxiliary heat quantity variable is introduced, and the DHS model is reformatted to a linear energy flow model by approximation of heat loss, where the computational burdens are significantly reduced. Extensive case studies are presented to validate the effectiveness and accuracy of the approximated model and illustrate the potential benefits of the proposed method with respect to congestion management and wind power accommodation.

Water electrolysis is a clean, non-polluting way of producing hydrogen that has seen rapid development in recent years. It offers the possibility of resolving the issue of excessive carbon emissions in conventional hydrogen production methods. In addition, waste heat recovery in hydrogen fuel cells can significantly increase the efficiency of energy use. Thus, to combine the electric power system, the hydrogen energy system, and the district heating system, this research suggests a novel optimal multi-energy complementary electricity–hydrogen–heat model. Rooftop photovoltaics, energy storage batteries, electric boilers, and hydrogen energy systems made up of hydrogen generation, hydrogen storage, and hydrogen fuel cells are all included in the suggested model. Furthermore, the electricity–hydrogen–heat system can be connected successfully using waste heat recovery in hydrogen fuel cells to create a coordinated supply of heat and power. In this work, the waste heat of hydrogen fuel cells is taken into account to increase the efficiency of energy use. To show the effectiveness of the suggested optimal multi-energy complementary model, many case studies have been conducted.

A combined heat and power virtual power plant (CHP-VPP) can effectively control the distributed resources in an electric–thermal coupling system and solve the problem of lack of flexibility caused by large-scale renewable energy grid connection. Similar to the optimal reconfiguration of distribution network topology by operating switches, the district heating system is also equipped with tie and sectionalizing valves to realize the optimal adjustment of district heating network (DHN) topology, which provides an economical and effective method for improving the power system’s flexibility. Based on this, this paper proposes a CHP-VPP economic scheduling model considering reconfigurable DHN. Firstly, the energy flow model is introduced to reduce the computational complexity. Secondly, adaptive robust optimization solved by the column-and-constraint generation algorithm is used to settle the randomness of wind power to ensure that the results are feasible in all worst scenarios. Finally, the feasibility of the proposed model is illustrated by case studies based on an actual CHP-VPP. The results show that compared with the reference case, considering the reconfigurability of DHN in the CHP-VPP optimization scheduling process can reduce the cost by about 2.78%.

Coordinated fault recovery is essential for the resilience enhancement of integrated electric and heating systems (IEHS) following natural catastrophes as the linkage of the power distribution system (PDS) and district heating system becomes tighter. DHS reconfiguration is a viable method for service restoration because it could adjust the energy between energy sources and achieve uninterrupted energy supplies. In this paper, a collaborative service restoration model considering DHS reconfiguration is proposed to achieve better recovery after natural disasters. DHS reconfiguration could guarantee interrupted power supply in non-fault regions by shifting electric loads between power sources and accomplish optimal service restoration by adjusting the power output of combined heat and power units. Numerous case studies are undertaken to demonstrate the performance of coordinated reconfiguration on resilience enhancement and to confirm the efficacy of the proposed paradigm.