A virtual power plant (VPP) can aggregate distributed renewable energy and flexible load to participate in the electricity market as a virtual controllable assembly. This pattern can effectively avoid the bidding risk of users, and produce cooperation benefits such as reducing transaction costs. Reasonable profit allocation is the key factor to determine the formation and survival of a VPP, which means a reasonable allocation for the VPP’s market income among participating members. In view of that, this paper proposes a framework of profit allocation in VPPs based on cooperative game theory. Aiming at the competitive environment with multiple VPPs in the electricity market, a VPP’s profit allocation model based on bidding optimization is built, which considers multiple objectives such as fairness of profit allocation, stability of cooperation alliance, and attraction of participating members. Furthermore, a multi-objective evolutionary optimization algorithm based on reference points is introduced to solve the model. Then, a VPP composed of prosumers is taken as an example to carry out the emulation. The results show that all participating members can get satisfactory profit allocation. Its cost-saving ratio ranges from 7.82% to 18.66%, and it confirms that the proposed profit allocation method can encourage prosumers of small size to participate in the VPP cooperation effectively.

With a substantial fraction of renewable energy integrated into the electrical grid, the new power system urgently requires grid planning scheme displaying adaptability to different energy types and their volatility. Considering the indeterminacy of renewable energy generation output and the different attitudes of decision-makers towards its risk, this paper proposes an adaptability assessment methodology for power grid planning schemes considering multiple decision psychology. First, an evaluation indicator framework is established based on the adaptive requirements of the grid planning for novel power system, and the weights of indicators are calculated based on an improved AHP-CRITIC combination weighting method. Second, improved cumulative prospect theory (ICPT) is adopted to improve to the calculation method of the distance between the evaluation program and the positive and negative ideal programs in the GRA and TOPSIS, which effectively characterize the different decision-making psychologies, and a combination evaluation model is constructed based on a cooperative game (CG), namely, an adaptability evaluation model of grid planning schemes for novel power systems based on GRA-TOPSIS integrating CG and ICPT. Finally, the proposed model serves to evaluate grid planning schemes of three regions in China’s 14th Five-Year Plan. The evaluation results show that the adaptability of the schemes varies under different decision-making psychologies, and under the risk-aggressive and loss-sensitive decision-making psychologies, grid planning scheme of Region 1 with the greatest accommodation capacity of renewable energy is preferable.

In the context of vigorously advocating the transformation of electric energy production to green and low emission, it is very important to rationally allocate the wind-solar storage capacity of micro-grid. Based on this, this paper aims at the micro grid with wind-solar storage. Firstly, the output model of wind-solar storage unit is established, combined with the system scheduling strategy. Then, the optimization objective was to minimize the total cost of investment and operation, and the benefits of carbon emission reduction were taken into account. Genetic particle swarm optimization algorithm is used to solve the optimal capacity allocation. Finally, according to the calculation results of the example, the proposed wind-solar storage capacity configuration considering the benefits of carbon emission reduction can effectively reduce the cost and carbon emissions of the microgrid.

Hydrogen energy storage, as a new type of energy storage with zero carbon emission, multi-energy federal reserve and combined supply, has a good development prospect in the integrated energy system. Based on the integrated energy system with hydrogen storage equipment, this paper proposes the operation mechanism of the integrated energy system with hydrogen storage equipment in the environment of electricity market and carbon market. On this basis, considering the time value of money, the life-cycle economic evaluation model of the integrated energy system with hydrogen storage equipment is constructed. The model is applied to calculate the investment benefit of a community integrated energy system with hydrogen storage equipment in the whole life cycle. The result of an example shows that the integrated energy system with hydrogen storage equipment is of good economic benefits.

To promote low-carbon transformation and achieve carbon peak and neutrality in the energy field, this study proposes an operational optimization model considering the energy- and load-side dual response (ELDR) mechanism for electrothermal coupled virtual power plants (VPPs) containing a carbon capture device. The organic Rankine cycle (ORC) waste heat boiler (WHB) is introduced on the energy side. The integrated demand response (IDR) of electricity and heat is performed on the load side based on comprehensive user satisfaction (CUS), and the carbon capture system (CCS) is used as a flexible resource. Additionally, a carbon capture device operation mode that makes full use of new energy and the valley power of the power grid is proposed. To minimize the total cost, an optimal scheduling model of virtual power plants under ladder-type carbon trading is constructed, and opportunity-constrained planning based on sequence operation is used to address the uncertainty problems of new energy output and load demand. The results show that the application of the ELDR mechanism can save 27.46% of the total operating cost and reduce CO₂ emissions by 45.28%, which effectively improves the economy and low carbon of VPPs. In particular, the application of a CCS in VPPs contributes to reducing the carbon footprint of the system.

In pursuit of energy decarbonization and supply security, the integrated energy production unit (IEPU) is regarded as a notable multi-technology energy production model integrating coal-fired power, carbon capture, and renewable energy. As a core component of the IEPU, Power-to-X (P2X) technology encompasses various technical routes with distinct economic performance and technological maturity at different development stages. Thus, selecting the most techno-economically optimal route is critical. In view of this, this paper proposes an integrated decision-making framework for the selection of P2X technology routes in IEPU, which combines “technology selection—economic analysis—risk assessment”. Firstly, a decision model for key P2X processes is established, with the levelized cost of hydrogen and unit hydrogen conversion revenue as core performance metrics to identify the optimal technology combination for hydrogen production and utilization. Secondly, integrating the aforementioned optimized technical route, a life-cycle economic benefit evaluation model is constructed for IEPU retrofit projects to systematically assess the overall economic feasibility of the IEPU project. Thirdly, an investment risk assessment model for P2X-integrated IEPU retrofits is established based on interval number theory, which can quantify project risks under fluctuations of critical parameters such as electricity and carbon prices. Finally, a case study of a 600 MW coal-fired unit retrofit demonstrates that “alkaline electrolysis + methane synthesis” constitutes the optimal P2X technology combination. However, its profitability is relatively sensitive to fluctuations in external market parameters, necessitating the implementation of corresponding risk management strategies.