Features and Problems of the Chinese Electric Power System

This paper proposes the concept and framework of smart operating system based on the artificial intelligence U+0028 AI U+0029 techniques. The demands and the potential applications of AI technologies in power system control centers is discussed in the beginning of the paper. The discussion is based on the results of a field study in the Tianjin Power System Control Center in China. According to the study, one problem in power systems is that the power system analysis system in the control center is not fast and powerful enough to help the operators in time to deal with the incidents in the power system. Another issue in current power system control center is that the operation tickets are compiled manually by the operators, so that it is less efficient and human errors cannot be avoided. Based on these problems, a framework of the smart operating robot is proposed in this paper, which includes an intelligent power system analysis system and a smart operation ticket compiling system to solve the two problems in power system control centers. The proposed framework is mainly based on the AI techniques, especially the neural network with deep learning, since it is faster and more capable of dealing with the highly nonlinear and complex power system.

95/06137 The Chinese electric power system: Myths and realities

In recent years, continuous and reliable electric energy supply is the objective of any power system operation. FACTS devices are promising devices from the past ten years and are becoming popular. Also FACTS devices are very effective solution for many power system transmission problems. FACTS controllers can be used for steady state voltage regulation and control, steady state power flow can be controlled on a transmission line, transient stability enhancement, along with this it also reduces the problem of sub synchronous resonance. In this regard, Flexible Alternating Current Transmission Systems (FACTS) devices play a key role in enhancing controllability and to increase power transfer capability of the network. Thyristor Controlled Series Compensator (TCSC) is an upcoming FACTS device which can be used to meet this objective. The conventional methods in solving optimization problems in power systems suffer from several limitations due to necessities of derivative existence, providing suboptimal solutions, etc. computational Intelligence plays an important role in finding the optimal solutions for multi-objective functions. A combinatorial analysis problem in power systems can be solved by modern heuristic methods in finding optimal solution. Thus, in this paper, Genetic Algorithm, a type of evolutionary computation encapsulated with heuristic approach, is proposed for finding optimal location of TCSC. IEEE standard 30bus system is considered to test the credibility of the proposed algorithm and the results obtained are subjected to analysis to determine the optimal location.

It's essential to maintain a consistent and dependable energy supplies given the rising global demand for energy. When there is a crisis, such as a malfunction or an imbalance between energy production and load demand, the Frequency system becomes unstable. A load shedding scheme is an important key to recover frequency system and ensure the obtainability of electrical power for serious loads in a plant. Therefore, it is necessary to provide reliable technologies to quickly and accurately way to prevent breakdown in the system energy. Under Frequency Load SheddingUFLS is one of the important systems protection, and as is currently the case in many instances, it is the final step to prevent the system's collapse following an interruption or failure energy in the system. In this paper, the review of the literature is presented, along with a look at the various methods employed in the electrical power system and a comparison of traditional, adaptive, and intelligent load-shedding strategies. In order to clarify the intended function (entity) and preserve system stability, extra classification of additional elements is suggested. The various load shedding systems were addressed, along with their benefits and drawbacks, and a comparison between them was made with a list of the most significant justifications for doing so.

Recently, there has been a focus on natural and man-made disasters with a high-impact low-frequency (HILF) property in electric power systems. A power system must be built with “resilience” or the ability to withstand, adapt and recover from disasters. The resilience metrics (RMs) are tools to measure the resilience level of a power system, normally employed for resilience cost–benefit in planning and operation. While numerous RMs have been presented in the power system literature; there is still a lack of comprehensive framework regarding the different types of the RMs in the electric power system, and existing frameworks have essential shortcomings. In this paper, after an extensive overview of the literature, a conceptual framework is suggested to identify the key variables, factors and ideas of RMs in power systems and define their relationships. The proposed framework is compared with the existing ones, and existing power system RMs are also allocated to the framework’s groups to validate the inclusivity and usefulness of the proposed framework, as a tool for academic and industrial researchers to choose the most appropriate RM in different power system problems and pinpoint the potential need for the future metrics.

Electric power system is one of the largest and complex infrastructures made by mankind during the last century. The total investment associated with it in trillions of dollars. As it is a very expensive, large and complex physical system, secure network operation without having any system wide instability issue and catastrophic consequences is sought. As a result power system educators and researchers are constantly scrutinizing power system with changing scenarios and coming up with the new solutions to keep the most important infrastructure intact in order to make the economy and society sustainable. It is tough, but not impossible, and expensive to build physical test power systems to perform various researches. Hence, the test power systems models have been playing a key role for better understanding, development, and deployment of new solutions in power system problems. There have been many test systems with varying complexities and sizes used all around the world. However, there is no common platform where the most of these test systems are documented so that the educators and researchers can chose an appropriate test system suitable for their studies. The paper presents a collection of commonly used test systems for various dynamic stability studies.

The ε-coupling method has been applied to the solution of the load-flow problem in power systems in connection with the weak coupling between the subsystems for active and reactive power flows. The load-flow algorithm, based on this method, confirms the theoretical expectation of being considerably more efficient than the Newton-Raphson algorithm, as far as computing time and memory requirements are concerned, which are on the level of those required by the decoupled algorithms. The algorithm may be adapted to problems demanding efficient load-flow computations, such as security monitoring and optimal load-low problems.

In this article, an attempt has been made to find an effective solution of load frequency control problem in power system employing a powerful and stochastic optimization technique called “Ant Lion Optimization” (ALO). The proposed algorithm is inspired by the interaction strategy between ants and ant lions in nature. To appraise the effectiveness of ALO algorithm, a widely used two-area multi-unit multi-source power plant equipped with distinct PID-controller is investigated. The integral time absolute error-based objective function has been defined for fine tuning of PID-controller gains by ALO algorithm. To judge the acceptability of ALO algorithm, the simulation results are compared with some recently published algorithms. The simulation results presented in this paper confirm that the proposed ALO algorithm significantly enhanced the relative stability of the power system and can be applied to the real-time problem.

In this paper, an probability offset BPSO (binary particle swarm) method is proposed to solve the unit commitment problems in power systems with wind farms. Firstly, the initial unit commitment is determined by the prioritization method, and according to this result, the range of an optimization window is determined, and the BPSO is used to solve the solution in this range. During each iteration, the heuristic adjustment strategy enables the particles in each generation to meet the constraints. On the issue of economic load distribution, the classical Lagrange multiplication method combined with the dichotomy method is used to solve the problem, which greatly improves the efficiency of the solution. Finally, the results obtained are compared with those obtained by other algorithms, which proves that the proposed method has strong superiority and practicability.

Initial allocation modes and schemes are studied in this paper to provide guidelines for allocation of carbon emission permits in power system. We first introduce different allocation modes and the need to apply free allocation to assignability of emission permits. Then, we compare two different allocation schemes, which are based on historical emissions and generation performance standard. Further, a new allocation scheme based on Boltzmann distribution is proposed. Finally, a case study on Shanghai power grid in China is conducted to compare the allocation effects of these schemes respectively. The analytical results show that Boltzmann distribution based scheme has the best performance and should be adopted when developing initial allocation of carbon emission permits in Chinese power systems.

Small Modular Reactors (SMR) are gaining new momentum as a key technology for achieving global carbon neutrality targets due to their inherent advantages, including enhanced safety, lower financing costs, shorter pre-project and construction timelines, and broad applicability across diverse energy sectors. At present, over 70 Small Modular Reactor (SMR) designs are in development globally. In China, the first commercial SMR, Linglong One, located in Hainan, is scheduled for completion by 2026. Furthermore, High-Temperature Gas-Cooled Reactors are being increasingly deployed for industrial heat applications. However, the high cost of SMR construction poses a significant challenge to its commercial viability. This study quantitatively evaluates the impact of cost reductions in SMR on their deployment within China’s evolving power system, utilizing the Dynamic Optimal Power Expansion Model for China. The findings indicate that accelerated cost reductions would significantly expedite SMR deployment. When SMR costs reach parity with or fall below those of large-scale reactors (LRs), nuclear energy could account for over 22% of total installed capacity and 59% of total electricity generation in China. Furthermore, the stable power supply from SMR would mitigate the curtailment of variable renewable energy sources and enhance regional electricity reliability.

Voltage sag is a major problem in power system that must be solved. T o overcome the occurrence of the voltage sag, a system that well known as Dynamic Voltage Restorer (DVR) is needed. In an electrical power system, DVR is positioned in series between a source and load. There are several DVR voltage compensating methods, such as pre-sag method, inphase method and in-phase advance compensation. DVR need synchronization time for equals phase injection voltage so it can compensate voltage sag due to short circuit current. This work employs Discrete Fourier Transform (DFT) for phase detection and hysteresis voltage control. This paper presents modeling, analysis and simulation of DVR by using MATLAB.

Chapter 29 - Application of Fuzzy Methods in Power System Problems

Analysis of the CCS Considering Environment Co-benefit of Air Pollutants in China

This paper proposes a new method for solving economic dispatch problems in electrical power systems through the application of multithread programming. Multi-Thread Interior Point Barrier Algorithm, an efficient quadratic programming algorithm, is used to solve economic dispatch problem. The barrier algorithm also caters for any combination of polynomial functions such as polynomial cost functions. Nonlinear characteristics of electrical power system such as generators limitations, transmission losses and nonlinear cost functions are considered in the economic dispatch formulation. Exact transmission loss formula is used in the equality constraint in the economic dispatch equations. The transmission loss coefficients are calculated by using a multi-thread programming. To ensure the optimal dispatch satisfies the line flow limits, line flow constraints has been added to formulation as a security constraint. This optimization problem enable us to solve economic dispatch problems faster, so it is suitable for unit commitment problems and the other power system problems which need to get reasonable speed. IEEE 30, 57, 118 bus case studies are presented and tested with the proposed method.