There are the transmission loss of the electric power network, the delay and loss of the heating network, the insufficient utilization of flexible resources such as energy storage in the integrated electric-heat system, which may lead to the imbalance of supply and demand and energy waste. In this paper, the coordinated dispatch of integrated electric-heat system (IEHS) considering the transmission characteristics of the electric power network and heating network, which is formulated as a convex quadratic program. The strong linkage of electric power and heat supplies can be decoupled to reduce wind power curtailment by exploiting the energy storage and regulation capabilities of the district heating network (DHN), storage batteries, electric boilers (EBs) and heat storage tanks (HSs). The energy storage system works according to the situation division strategy designed in this paper. This paper introduces the wind curtailment boundary power and optimizes dispatch based on the wind curtailment boundary power and unit output, which can make full use of the energy storage capacity and reduce the wind abandonment power. Since the electric power system (EPS) and the distribution heating system (DHS) are controlled separately by different operation organizations, IEHS is solved using double- iterative algorithm. The double- iterative algorithm, with guaranteed convergence for convex programs, can achieve a fully distributed solution for the IEHS and requires only a small amount boundary information exchange between the EPS and the DHS. At last, one integrated electric-heat system was studied to demonstrate the effectiveness of the proposed method which achieves the effective solution in a moderate number of iterations. This system includes two 10-nodes heating system and one 14-nodes electric power system. INDEX TERMS Integrated electric-heat system, Energy storage situation, Network transmission characteristics, Wind power accommodation, Double- iterative algorithm This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.
The uncertainty and volatility of renewable energy generation lead to large amounts of abandoned electricity. The electricity-hydrogen coupling microgrid (EHCM) consists of the proton exchange membrane electrolytic cell (PEMEC), liquid organic hydrogen carrier (LOHC) hydrogen storage, proton exchange membrane fuel cell (PEMFC). The structure helps to increase the utilization of wind and photovoltaic power. The scheduling of an EHCM is very challenging. This paper proposes the optimal operation of a microgrid considering the uncertainty of wind speed, light, and the coupling of electricity and hydrogen. The electricity-hydrogen coupling model and hydrogen market model are constructed. The microgrid provides ancillary services to the grid while meeting hydrogen demand. The above model is solved using a two-stage optimization method with time scales of day-ahead and intra-day. Finally, taking the IEEE 33-node microgrid as an example, the effectiveness of the proposed model is verified. The results of the case show that the proposed method can obtain more benefits and reduce carbon emissions.
The electricity-heat integrated system can realize the cascade utilization of energy and the coordination and complementarity between multiple energy sources. In this paper, considering the thermal comfort of users, taking into account the difference in dynamic characteristics of electric and heating networks and the response of users’ demands, a dispatch model is constructed. In this model, taking into account the difference in the time scale of electric and thermal dispatching, optimization of the system can be improved by properly extending the thermal balance cycle of the combined heat and power (CHP) unit. Based on the time-of-use electricity prices and heat prices to obtain the optimal energy purchase cost, a user demand response strategy is adopted. Therefore, a minimum economic cost on the energy supply side and a minimum energy purchase cost on the demand side are considered as a bilevel optimization strategy for the operation of the system. Finally, using an IEEE 30 nodes power network and a 31 nodes heating network to form an electricity-heat integrated system, the simulation results show that the optimal thermal balance cycle can maximize the economic benefits on the premise of meeting the users’ thermal comfort and the demand response can effectively realize the wind curtailment and improve the system economy.
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