Optimal dispatch of integrated energy system considering integrated demand response resource trading

The valve-side bushing of the UHV converter transformer is the key equipment in the DC transmission project, and its running state directly affects the security and stability of the power system. This paper analyses the attributes of the physical entities, uses the digital twins to establish the state feature set and proposes a zero-sample state evaluation algorithm for the valve-side bushing. First, the geometric, materials and electrical characteristics are analyzed, and the detailed components of carrier current are obtained by empirical mode decomposition. Then, COMSOL is used to establish digital twins, verify the validity of twins with axial heat distribution of bushing, and establish a state feature set with the extreme temperature inside and outside bushing. Finally, the fuzzy clustering algorithm is used to classify the state feature set, and the similarity is used as the index to realize the zero-sample state evaluation of the valve-side bushing. Through the demonstration and analysis of examples, the evaluation model solves the problems of difficulty in extracting the internal features, fewer fault samples, and training difficulty, which is conducive to improving the operation and maintenance management level of power transmission equipment.

Section: Attribute Analysis Algorithmmentioning

confidence: 99%

“…Under the background of low carbon and energy structure adjustment, higher requirements are put forward for the optimal allocation of power resources [1]. The key to realizing the safe transmission of large capacity and long-distance power is to improve the operation and maintenance management level of power equipment.…”

Section: Introductionmentioning

confidence: 99%

A zero‐sample state evaluation model for valve‐side bushing of UHV converter transformer oriented to digital twin under attribute analysis

Liu

Miao

et al. 2023

“…In 2008, the concept of blockchain was proposed in Nakamoto's article 'Bitcoin: a point-to-point electronic cash system' [19]. The blockchain is a distributed shared ledger that integrates technologies such as peer-to-peer transmission, consensus mechanisms, smart contracts, and encryption algorithms [20]. It has the characteristics of decentralization, tamper resistance, full process tracing, collective maintenance, and transparency.…”

Section: Fisco Bcos Blockchain Technologymentioning

confidence: 99%

“…The difference in incremental cost between microgrids is evaluated using (20), and this difference is adjusted towards intergrid consistency according to (21):…”

Section: Incremental Cost Consistencymentioning

confidence: 99%

Multimicrogrid collaborative economic scheduling method based on the FISCO BCOS blockchain

Wang

Yang

et al. 2023

With the advancement of carbon peaking and carbon neutrality goals, microgrid clusters have attracted widespread attention due to their high stability and energy efficiency. This article proposes a scheduling architecture for microgrid clusters that integrates blockchain smart contracts, consensus mechanisms, and encryption technologies to address the issues of data trust, privacy protection, and security reliability in microgrid clusters. An economic adjustment model for microgrid clusters is constructed that combines economic and environmental objectives. Finally, based on the RPBFT (Rotating Proof of Believability) algorithm and group architecture of FISCO BCOS blockchain technology, an economic scheduling method for microgrid clusters is designed. The authors built a microgrid cluster model on the FISCO BCOS blockchain platform and conducted experiments on the effectiveness, economy, fault tolerance, and scalability of economic scheduling methods. The experimental results showed that the economic scheduling method proposed in this paper can effectively reduce the risk of nodes tampering with data in a microgrid cluster system, ensure the privacy of submicrogrids, and support the deployment of large‐scale microgrid clusters, the realization of multiparty collaborative autonomy and the stable, low‐carbon, economic operation of microgrid clusters.

“…In recent years, the integration of renewable energy sources (RESs) has significantly as well as rapidly increased in the power systems generation sectors [1,2]. The proliferation of RESs with their intermittent generation outputs has demanded a higher degree of operational system flexibility [3][4][5]. To cope with the intermittency of RESs' outputs and achieve a higher level of system flexibility, power system investors and planners have tried to suggest short-and long-term solutions [3,6].…”

Section: Introductionmentioning

confidence: 99%

Harnessing power system flexibility under multiple uncertainties

Mazaheri

Saber

Fattaheian‐Dehkordi

et al. 2022

Increasing the intermittent outputs of renewable energy sources (RESs) has forced planners to define a new concept named flexibility. In this regard, some short‐ and long‐term solutions, such as transmission expansion planning (TEP) and energy storage systems (ESSs) have been suggested to improve the flexibility amount. A proper optimization procedure is required to choose an optimal solution to improve flexibility. Therefore, a mixed‐integer linear programming (MILP) direct‐optimization TEP versus ESSs co‐planning model is presented in this paper to enhance power system flexibility. In doing so, a novel RES‐BESS‐based grid‐scale system flexibility metric is proposed to investigate the improvement of flexibility amount via ESSs modules in the numerical structure. In this paper, a novel repetitive fast offline method has been proposed to quickly reach the desired amount of flexibility by defining an engineering price/benefit trade‐off to finally find the best investment plan. Also, multiple uncertainties associated with wind farms and demanded loads and a practical module‐type battery energy storage system (BESS) structure for each node are defined. The proposed model is applied to the modified IEEE 73‐bus test system including wind farms, where the numerical results prove the model efficiency as BESS impacts on flexibility, investment plans and power system economics.