Highways are a critical consumer of energy. The integration of the highway and the energy system (ES) is a proven method towards carbon neutrality. The increasing energy demands of highway transportation infrastructure and the development of distributed energy and energy storage technologies drive the coupling between the highway system (HS) and the energy supply network, which is becoming tighter than ever before. Many scholars have explored the mode and path of integrated transportation and energy development. However, the energy and transportation systems’ coupling relationship and the collaborative planning scheme have not been thoroughly studied. Facing the increasing interconnection between transportation and energy networks, as well as addressing the demand for clean energy in highway transportation effectively, this paper proposes a highway self-consistent energy system (HSCES) planning model integrating uncertain wind and photovoltaic (PV) power output, so as to analyze the energy supply mode of the HS and determine the multi-energy capacity configuration of the self-consistent energy system (SCES). Firstly, the mathematical model related to each micro-generator of the SCES and the load aggregation scenario of the HS is established. Secondly, considering the uncertainty of renewable energy, this paper focuses on wind and PV power generation, and abatement technology, under uncertain conditions to ensure the best solution for reliability. Thirdly, taking the economy, reliability and the renewable energy utilization rate of the system into account, the system planning model is established under the condition of ensuring the system correlation constraints. Finally, the proposed method is validated using a section of the highway transportation system in western China. The results show that the hybrid energy storage planning scheme can cause the system’s renewable energy utilization rate to reach 99.61%, and the system’s power supply reliability to reach 99.74%. Therefore, it is necessary to carry out coordinated planning while considering the characteristics of the HS and the ES, which can minimize the planning cost of a HSCES, reduce the waste of wind and solar energy, and ensure the reliability of the power supply for the HS.
Under the background of “carbon peaking and carbon neutrality goals” in China, the Highway Self-Consistent Energy System (HSCES) with renewable energy as the main body has become a key research object. To study the operational status of the HSCES in a specific region and realize the economically optimal operation of the HSCES, an HSCES model in a low-load, abundant-renewable-energy and no-grid scenario is established, and a two-stage optimal scheduling method for the HSCES is proposed. Moreover, in the day-ahead stage, uncertainty optimization scenarios are generated by Latin hypercube sampling, and a definition of the self-consistent coefficient is proposed, which is used as one of the constraints to establish a day-ahead economic optimal scheduling model. Through the case comparison analysis, the validity of the day-ahead scheduling model is confirmed and the optimal day-ahead scheduling plan is attained. Furthermore, in the intra-day stage, an intra-day rolling optimization method is proposed, which can effectively track the day-ahead scheduling plan and reduce the impact of forecast errors and energy fluctuations by coordinating the unit output within the HSCES system. It is verified that the HSCES can operate economically and safely in Western China, and self-consistently, without grid support.
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