Hasil untuk "Distribution or transmission of electric power"

A. Yazdani, R. Iravani

Farshid Zabihian

Živko Sokolović, Mileta Žarković

Hamad Alduaij, Yang Weng

Deepening the deployment of distributed energy resources requires the large-scale integration of inverter-based resources, which can deteriorate the frequency stability. Recent studies propose using neural Lyapunov-based reinforcement learning for control. While this method can be trained offline with performance guarantees, it is only optimal for specific values of system parameters, as it omits critical modeling factors like decreasing inertia and damping variation over time. To maintain the performance at varying operation points, we consider an adaptive neural Lyapunov framework that adapts the controller’s output in the presence of varying parameters. Neural networks require flexibility to maximize adaptive control performance, while stability demands monotonicity, creating an inherent conflict. In this paper, we design a partially monotonic controller that maintains stability with maximal representation capacity for parameter adaptation. Stability is ensured by having monotonicity retained for frequency while non-monotonicity is allowed for the system parameters, such as damping and inertia. The structural form of partially monotonic neural networks is used for the controller design to that end. Flexibility is allowed by the design when adaptation to changes to the system parameters is made, while the Lyapunov stability guarantee is retained. The non-monotonic layers are chosen through an adaptive layer that is designed for damping and inertia based on their relationship to control in the system equation, by which optimized output for different operating conditions is allowed.

F. Gulotta, Edoardo Daccò, Alessandro Bosisio et al.

Electric power systems are moving toward more decentralized models, where energy generation is performed by small and distributed power plants, often from renewables. With the gradual phase out from fossil fuels, however, Distribution Energy Resources (DERs) are expected to take over in the provision of all regulation services required to operate the grid. To this purpose, the opening of national Ancillary Service Markets (ASMs) to DERs is considered an essential passage. In order to allow this transition to happen, current opportunities and barriers to market participation of DERs must be clearly identified. In this work, a comprehensive review is provided of the state-of-the-art of research on DER integration into ASMs. The topic at hand is analyzed from different perspectives. First, the current situation and main trends regarding the reformation processes of national ASMs are analyzed to get a clear picture of the evolutions expected and adjustment required in the future, according to the scientific community. Then, the focus is moved to the strategies to be adopted by aggregators for the effective control and coordination of DERs, exploring the challenges posed by the uncertainties affecting the problem. Coordination schemes between transmission and distribution system operators, and the implications on the grid infrastructure operation and planning, are also investigated. Finally, the review deepens the control capabilities required for DER technologies to perform the needed control actions.

Haitao Zhang, Jizhi Han, Zihao Sha et al.

Abstract The fractional frequency offshore wind power system (FFOWPS) is a core technology for the long‐distance transmission and integration of the large‐scale offshore wind power. However, the risk of wide‐band oscillation in the FFOWPS has become increasingly prominent due to the inevitable presence of the power electronic devices. The traditional admittance of the frequency converter, which is a crucial component in the FFOWPS, may contain right‐half‐plane (RHP) poles when operating under various control modes. To address this deficiency, this paper establishes a four‐port small‐signal admittance model of a back‐to‐back frequency converter and demonstrates its interconvertibility with the traditional model. On this basis, the wide‐band oscillation analysis method for the FFOWPS is proposed, which explicitly describes the influence of the industrial frequency system, the fractional frequency system, and their coupling interactions on system stability. Simulation results in MATLAB/Simulink verify the proposed stability analysis method, highlight stability misjudgements associated with the traditional admittance, and analyse the impact of the coupling terms on system stability.

Mojtaba Shivaie, Reza Artis, Sanjeevikumar Padmanaban

Abstract This paper proposes a new multistage AC model for transmission expansion planning that finds an optimal combination of transmission lines, fault current‐limiting high‐temperature superconducting cables, and multiple distributed generations (DGs). On this basis, the proposed model, from a new perspective, allows for simultaneous improvement of the short‐circuit level and grid‐scale flexibility (GFLX) under both normal and fault conditions. The objective function to be minimized includes not only the net present worth of the total investment and operation costs but also the congestion‐induced GFLX degradation measure. This model also takes the AC power balance and flow relationships, equipment capacity limits, nodal voltage bounds, DG penetration level limit, as well as discrete logical and financial restrictions together into account with the short‐circuit level constraint. To overcome the complexity of solving the resultant non‐convex mixed‐integer non‐linear optimization problem, a multi‐objective integer‐coded melody search algorithm is employed, followed by a fuzzy satisfying decision‐making mechanism to obtain the final optimal solution. The exhaustive case studies conducted on the IEEE 24‐ and 118‐bus test systems verify the efficacy of the newly developed model in terms of cost‐effectiveness, flexibility, and short‐circuit level suppression when facing different normal and fault conditions.

Muhammad Suhail Shaikh, Saurav Raj, Shah Abdul Latif et al.

Abstract Power flow, planning, economics, dispatch, and stability analysis rely on accurate transmission line parameters (TLPE). Standard optimization methods are employed to develop such analyses and obtain TLPE. Additionally, these methods have limitations, including precision, accuracy, and time complexity. It is challenging to find improved solutions using standard optimization methods due to slow convergence and limitations in identifying local optima. Concerned with these challenges, the study suggest a new application for an effective hybrid optimization method capable of addressing such limitations. The hybrid algorithm, named the Salp Swarm Algorithm with Sine Cosine Algorithm (HSSASCA), that aims to tackle the issues of slow convergence and local optima. The Sine Cosine Algorithm (SCA) is employed after the Salp Swarm Algorithm (SSA), and Salp integration is utilized to successfully explore and analyze the search space. To enhance the performance of HSSASCA, the hybrid technique aims to provide expanded exploration capabilities, effective exploitation of the search space, and a better convergence rate. These key features position the HSSASCA algorithm as an effective solution to complex optimization problems. To assess the efficiency of the HSSASCA algorithm, six different test systems are employed. Initially, the evaluation of exploration, exploitation, and minimized local optima is conducted using the CEC 2019 benchmark functions. Secondly, efficiency monitoring and verification of HSSASCA across different scenarios occur by comparing it with established optimization algorithms such as SSA, SCA, firefly optimization algorithm (FFO), Grey Wolf Optimization (GWO), student psychology‐based optimization (SPBO), and Symbiotic Organisms Search (SOS). Finally, statistical analysis is performed, revealing that the HSSASCA outperforms SSA, SCA, FFO, GWO, SPBO, and SOS. In terms of statistical results and convergence curves, the HSSASCA demonstrates superior performance in searching efficiency, convergence accuracy, and local optimum avoidance ability.

Hajar Kafshian, Mohammad Ali Saniee Monfared

Abstract Here, a novel tri‐level energy market model aimed at addressing the challenges posed by demand side management (DSM) in the electricity distribution company (EDC) is introduced. DSM has emerged as a new strategy employed by EDCs to manage and control electricity demand by encouraging end‐users to modify their electricity consumption patterns. This is achieved through the participation of demand response (DR) aggregators, which play a crucial role in assisting end‐users with strategies and technologies to reduce their electricity consumption during peak hours. The proposed tri‐level energy market model consists of four distinct players: EDC, microgrids, aggregators, customers. The interactions between these four actors are modelled within a tri‐level game framework, where the EDC and aggregators act as leaders, and the micro‐grids and customers are followers. This multi‐level and multi‐player game structure allows for a more realistic representation of the complexities involved in DSM programs within the energy market. To demonstrate the effectiveness of the proposed model, a real case study is utilized, showing that the new model better resembles real‐life market conditions. The results illustrate how the tri‐level energy market model can significantly reduce demand fluctuations during peak hours, leading to improved efficiency and effectiveness within DSM programs.

A. M. Pourrahimi, R. Olsson, M. Hedenqvist

Fatih Özveren, Ömer Usta

Ahmad M. Alshamrani

Carlos Abel Perdomo Pérez, Lester González Espinosa, Ariel Santos Fuentefria

Abstract In Latin America, distribution networks are mostly radial, with high energy losses, representing about 16% of the region's electricity consumption. In Cuba, one of the alternatives that has been proposed to reduce these losses is the distribution of photovoltaic (PV) power plants of up to 3 MWp in them. This paper presents a new hybrid optimization algorithm to localize and size PV power plants to minimize energy losses in radial distribution networks. The method localizes the power plants using Empirical Discrete Metaheuristic in conjunction with a novel strategy that reduces the execution time of the algorithm. The sizes are found using the Coordinate Search Method, which performs one‐dimensional searches in the directions of the variables of the objective function. The algorithm was run on a 33‐bus IEEE test system in which up to five power plants were optimally installed, taking into account load variations at the distribution level and changes in the weather conditions under which the power plants operate. It should be noted that the execution times for each scenario did not exceed 30 s. The algorithm was validated by comparing it with other methods found in the literature and proved to be more efficient than them.

Shengwen Shu, Yangyang Chen, Shiyun Cao et al.

Abstract Monitoring and alarm play an important role in preventing trip‐out caused by wildfires for high‐voltage transmission lines. This paper proposes a multi‐Doppler weather radar‐based method for monitoring and alerting of wildfires near transmission lines. Firstly, characteristic parameters are mathematically proposed to distinguish wildfire's radar echoes. Then, the four‐site neighbourhood algorithm and the multithreading method are used to extract all possible wildfire echo units detected by various Doppler weather radars, and a cumulative probability is calculated to identify the wildfire. Finally, a regional block search method is used to quickly locate wildfire‐affected transmission towers. The membership function of spread time in the fuzzy set is proposed to determine the alarm level, which takes into account the influences of environment, topography, and vegetation on wildfire spread rate. The application to a provincial power grid demonstrates that the proposed method has an accuracy of 82.4%, a missing alarm rate of 27.4%, and a delay of fewer than 15 min. In addition, the joint observation of wildfires by multi‐Doppler weather radars and satellites indicates a promising application prospect for transmission line wildfire fighting.

Karthik Rajashekaraiah, Cosimo Iurlaro, Sergio Bruno et al.

This article proposes a new method of modelling dynamic loads based on instantaneous p-q theory, to be employed in large powers system network simulations in a digital real-time environment. Due to the use of computationally heavy blocks such as phase-locked-loop (PLL), mean calculation,and coordinate transformation blocks (e.g., abc–dq0), real-time simulation of large networks with dynamic loads can be challenging. In order to decrease the computational burden associated to the dynamic load modelling, a p-q theory-based approach for load modelling is proposed in this paper. This approach is based on the well-known p-q instantaneous theory developed for power electronics converters, and it consists only of linear controllers and of a minimal usage of control loops, reducing the required computational power. This improves real-time performance and allows larger scale simulations. The introduced p-q theory-based load (PQL) model has been tested on standard networks implemented in a digital real time simulator, such as the SimBench semi-urban medium voltage network and the 118-bus Distribution System, showing significant improvement in terms of computational capability with respect to standard load models (e.g., MATLAB/Simulink dynamic load).

Chutong Wang, Xiaoyan Zhang, Yuanxing Xia et al.

Abstract Cloud energy storage system (CESS) can effectively improve the utilization rate of the energy storage system (ESS) and reduce the cost. However, there is a lack of a model designed for large‐scale renewable energy power plants (REPPs). Due to the volatility and intermittency of renewable energy power generation, as well as the demand of following scheduling plan and market arbitrage, it is also necessary to configure ESS for REPPs. However, if the REPP builds ESS by itself, the investment is relatively high. Therefore, the application of CESS on the renewable energy generation side can reduce the investment cost and increase the revenue by utilizing the difference between actual output and demand. Considering the uncertainties of renewable energy, this paper proposes a robust optimal configuration model of CESS based on the cooperative game. Firstly, the CESS model on the generation side is developed to describe the formation mechanism of ESS supply and demand. Then, the proposed model aims at maximizing the revenue of REPPs. The participants of the coalition are each REPP. By taking the renewable power uncertainty into consideration, the novel nested column‐and‐constraint generation (nested C&CG) method is utilized to solve the proposed model based on the min–max–min form. Furthermore, the Shapley‐value method is used to distribute the benefits to each member of the grand coalition. Finally, case studies verify the rationality and validity of the proposed model.

Feng Zhou, Jicheng Yu, Xiaodong Yin et al.

Faced with the pressure of energy conservation and emission reduction, the power industry is urgently requires low-carbon transformation. The carbon flow calculation theory redistributes the actual carbon generated by the power plant to the branch and loads customers with the power flow. This paper first introduces the theory of carbon flow calculation and the carbon metrics corresponding to the electricity metrics. Second, a time-synchronous technology is introduced for the carbon flow calculation of transmission, transformation, and distribution networks, and a time-synchronous-based carbon metering system is conceived. The impact of time deviation on carbon metering is elucidated through simulation experiments of IEEE14 standard nodes, and finally, relevant suggestions are made for future research ideas and technical routes.

Atousa Elahidoost, Elisabetta Tedeschi

Abstract Interconnection and expansion of AC networks through high‐voltage direct current grids based on modular multilevel converters to form a multiterminal hybrid AC/DC grid can pose stability issues. These challenges can arise from dynamic interactions between/within AC and DC subgrids due to poorly damped modes that are potential sources of persistent and disruptive oscillations. This paper aims to ensure the stability of multiterminal hybrid AC/DC grids via a decentralized optimal controller. The proposed methodology analytically and simultaneously identifies both the decentralized optimal controller and the worst‐case perturbation scenario under the grid control inputs' and state variables' constraints, without the need for detailed and time‐consuming dynamic simulations of all possible scenarios. Eigenvalue stability analysis and time‐domain simulations show that the proposed controller can efficiently enhance the test grid stability margins and reduce the oscillations, not only under the worst‐case perturbation scenario (increasing damping ratios of the two pairs of least damped modes by 2.34 and 4.05 times) but also under other critical fault conditions. Furthermore, the controller's superior performance is validated through comparison with the power system stabilizer and modular multilevel converter droop controller under small and large disturbances, and its robustness is assessed against parametric uncertainties.

Jiahui Zhang, Peng Xue, Bin Xiang et al.

Abstract Superconducting energy pipeline (SEP) is a new type of electrical energy transmission. It contains high‐temperature superconducting cables and liquefied natural gas pipelines and can simultaneously transmit electricity and liquefied natural gas (LNG). However, when the superconducting tapes in the superconducting cables in SEP quench and generate heat, bubbles will generate in the butt‐gaps of the insulation layer of superconducting cables, which can reduce the insulation strength of the cables significantly. In addition, the effects of bubbles in the butt‐gap of the insulation layer on the insulation properties of the superconducting cables are unknown. The objective here is to obtain the influences of bubbles in the insulation layer of superconducting cables in capacitive field, transitional field, and resistive field. Simulation results show that: Compared with the absence of bubbles, the big bubbles can increase the capacitive field strength of the PP film, the butt‐gap, and the kraft by 37.54%, 30.89%, and 18.5%, and increase the transition time from the capacitive field to the resistive field, but has almost no effect on the butt‐gap in the resistive field.

Xu Han, Qizi Huangpeng, Xiaojun Duan et al.

Abstract Power system controlled islanding is an emergency control method used to stop the propagation of disturbances and avoid blackouts. Intentional controlled islanding (ICI) has been proposed as a corrective measure of last resort to split the power system into several sustainable islands. Complex network community detection is widely used in network partitioning and can be used to solve controlled islanding problems. The objective of this study is to apply the dynamic network community detection method to solve ICI problems. Using dynamic network modelling, the division‐agglomeration (Di‐Ag) algorithm is proposed. Dynamic modelling presets the computation task of the algorithm in the healthy grid phase. The algorithm balances the efficiency of the algorithm, power imbalance, and power flow disruption, without sacrificing other objectives to optimise one objective. Specifically, the grid topology is taken into account when the grid is divided using betweenness as edge weight. The first step of the Di‐Ag algorithm uses the dynamic Girvan–Newman algorithm to achieve the goal of power imbalance. Moreover, only the islands' involved lines (nodes) are updated, which improves the efficiency of the algorithm. In the second step of the Di‐Ag algorithm, the algorithm merges the islands to reduce power flow disruption. The IEEE 39‐bus and 118‐bus system are used to compare the performance of the proposed dynamic modelling method and the static network community discovery method in three different cases.