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| Decomposition Analysis on Locational Marginal Energy Prices in Regional Integrated Energy System Considering Flexibility Provision Constraints |
| Chen Hongkun, Wang Xuechun, Chen Lei |
| School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China |
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Abstract Regional integrated energy system (RIES) expands the operation boundary of a single energy system through distributed multi-energy coupling and conversion equipment, which is of great significance to local renewable energy consumption. However, as the multi-energy coupling deepens and distributed renewable energy integration grows, the RIES faces great challenges in maintaining flexible and economic operation. Some research efforts have been conducted to optimize the economic operation of RIES with distributed renewable energy by increasing its flexibility. However, the impact of flexible supply on operational economy of RIES has not been further analyzed. To tackle this problem, a method to calculate the locational marginal energy prices (LMEPs) of RIES considering flexibility provision constraints was proposed. The LMEPs explicitly reflect the operating economy of RIES, and the decomposition analysis for LMEPs can help regional integrated energy system operators (RIESO) to seek the balance between flexibility and economy.
Firstly, the operation framework of RIES was constructed under the regional integrated energy market environment, where the RIESO cleared the market and multi-energy generators participated in the market. Secondly, the RIES scheduling model considering flexibility provision constraints, including the multi-energy supply and the multi-ramping capacity constraints, was established. Then, based on the model, the LMEPs of RIES were calculated and decomposed, with respect to the influence of the combined heat and power (CHP) units' flexible provision constraints on energy prices coupling and the peak prices formation. Finally, a numerical example was carried out on a combined electrical-thermal RIES to verify the effectiveness of the proposed method.
To analyze the impact of flexibility provision on the operating cost, the scheduling results, and the LMEPs of RIES under different scenarios, 4 cases were set for comparison. The comparison of optimized operation results showed that the more abundant flexibility provision, the lower the operating cost, and the more violent fluctuation of the distributed wind power generation led to an increase in flexibility demand and operating cost. The LMEPs can be decomposed into the marginal cost component, the network transmission loss component, the congestion component, the operation domain component, and the flexible ramping component. The marginal cost component reflected the coupling relationship between LMEPs. The network transmission and the congestion component reflected the influence of the power flows in RIES on LMEPs. The operation domain and flexible ramping component reflected the abundance of flexibility provision. When flexibility provision was insufficient, the energy price peaks would emerge. Finally, to verify the flexibility provision of the district heating network, it was considered as passive energy storage and jointly operated with CHP units. The fluctuation of LMEPs was significantly reduced through the joint operation.
The following conclusions can be drawn from the cases study: (1) The scheduling model of the RIES considering flexibility provision constraints under the market environment can effectively solve the LMEPs, which provide effective price information. (2) By decomposing and analyzing the LMEPs under different flexibility provision cases, the coupling relationship between the LMEPs was proved, and energy price peaks would emerge when the flexibility provision was insufficient. (3) The district heating network can be considered as passive energy storage to jointly operate with condensing CHP unit, the joint operation optimized effectively suppressed the energy price peaks.
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Received: 14 April 2022
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2023, Vol. 38 
