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The complex energy conversion and the volatility of renewable energy/load bring great challenges to the operation of the park‐level integrated energy system (PIES). To overcome this challenge, this paper proposes a multi‐timescale flexible dispatching method to fully exploit the flexibility of PIES in the energy cascade utilization mode. The cascade utilization model for energy flow is firstly established to analyse the coupling and complementary of heterogeneous energy. On this basis, the supply‐demand general equations of multi‐energy flexibility are proposed, which accurately quantify the ability to cope with uncertainty through mutual flexibility. Through coordinated complementation and mutual exchange of multi‐grade flexibility, the system realizes the suppression of random power fluctuations. The scheduling model includes day‐ahead dispatch and intraday multi‐time scale dispatch, which can satisfy the adjustment speed requirements of different energy. Numerical results demonstrate that the proposed method effectively enhances the flexibility and economy of system operation. The flexible demand for energy of all grades can be satisfied. Compared with the flexible dispatch in the triple energy supply structure, the operating cost is reduced by 9.07%.
The rampant growth in penetration of gas-fired distributed units (GFDUs) is recasting the role of the integrated energy service provider (IESP) as a price-maker player. Nevertheless, it is threatening the well-being and reliability of the natural gas networks (NGNs). In this regard, this paper investigates the strategic participation of integrated 20-node NGN and an 33-bus active distribution system (ADS) in the day-ahead wholesale market (WM), which consists of a six-bus transmission network (TN), through a bi-level optimization framework. The upper-level objective is to minimize the operational costs of the IESP as well as the cost of energy that is purchased/sold in day-ahead WM. The lower-level problem models the optimal response of the wholesale market operator (WMO) that has the objective of maximizing social well-fare by clearing the day-ahead wholesale market. To alleviate the NGN's pipeline congestion, the linepack capability of the pipelines is deployed, while demand response program (DRP) and interruptible loads (IL) are integrated into the ADS side. As a computationally efficient method, robust optimization (RO) is utilized to handle the uncertainties. The results emphasize the necessity of integrating NGN into this problem. Eventually, different case studies illustrate the impact of line pack and DRP in reducing market-clearing price.
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