In order to solve the problem of large parameter identification error caused by nonlinear links of excitation system being triggered easily when transient stability is under fault state, an improved differential evolu...
In order to solve the problem of large parameter identification error caused by nonlinear links of excitation system being triggered easily when transient stability is under fault state, an improved differential evolution algorithm for system parameter identification is proposed by using the characteristic of artificial intelligence algorithm that the nonlinear link is approximated infinitely through optimization. The improvement of the algorithm solves the problems of slow convergence speed, poor fine optimization ability and easily to produce local optimum when classical artificial intelligence algorithm identifies the parameters of non-linear links. At the same time, in order to solve the problem of inaccurate parameters in the whole identification, a decomposition link identification strategy is proposed. The example analysis shows that the algorithm improves the convergence speed, avoids local optimum and improves the convergence accuracy. According to the proposed parameter identification strategy, the excitation system is decomposed and identified, which improves the accuracy of generator excitation system parameter identification, and provides an accurate model and method for powersystem stability analysis
The DC distribution network can integrate the photovoltaic power generation system with high efficiency, but the random fluctuation of the photovoltaic output power is strong and there is a problem of PV consumption, ...
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ISBN:
(数字)9781839531248
ISBN:
(纸本)9781839531255
The DC distribution network can integrate the photovoltaic power generation system with high efficiency, but the random fluctuation of the photovoltaic output power is strong and there is a problem of PV consumption, which has a certain degree of impact on the economic optimization operation of the system. Therefore, the source-network-load-storage optimization interaction concept is introduced in the DC distribution network. Based on the in-depth analysis of the interactive load characteristics, the interaction load and energy storage technology can be fully utilized to the system to consumpt the photovoltaic. Combined with the features of DC distribution network structure, comprehensively consider the impact of the interactive load and energy storage system collaborative optimization on the system operating cost and power flow distribution, so that both the power generation side and the power side can participate in the resource optimization configuration of the grid operation. A multi-objective optimal scheduling model for photovoltaic DC distribution networks with operational cost, network loss and voltage deviation is established. The simulation example shows that: Collaborative optimization using interactive load and energy storage system can greatly reduce system operating cost, network loss and voltage deviation, effectively improve the level of PV consumption, and realize safe and reliable operation of DC distribution network.
Large electricity consumers (LEC) can purchase energy from various energy resources such as bilateral contracts, pool market, micro-turbines, battery storage systems, wind turbines, photovoltaic panels (PV). The uncer...
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Large electricity consumers (LEC) can purchase energy from various energy resources such as bilateral contracts, pool market, micro-turbines, battery storage systems, wind turbines, photovoltaic panels (PV). The uncertainty of market price leads to uncertainty in the total cost to the LEC. Therefore, in this article, the robust optimization (RO) technique is provided to investigate the uncertainty of the pool market price in the presented problem. Also, demand response program (DRP) is provided to decrease the purchased cost to the LEC as much as possible. According to the obtained results, without considering DRP, purchased cost is approximately $40,253.252 and $42,586.984, respectively in the risk-neutral strategy (ideal condition) and robust strategy (worst condition). Furthermore, the purchased cost is reduced nearly $36,945.362 and $39,789.267 in the risk-neutral and robust strategies with considering DRP. So, it can be concluded that the purchased cost to the LEC with considering DRP is reduced 8.2% and 6.5% in risk-neutral and robust strategies, respectively.
With the increasing proportion of renewableenergy generation into the power grid, more challenges are coming to the safe and stable operation of the powersystem. In order to keep the balance in energy market, system...
ISBN:
(数字)9781839530043
With the increasing proportion of renewableenergy generation into the power grid, more challenges are coming to the safe and stable operation of the powersystem. In order to keep the balance in energy market, system operator has to purchase much service in ancillary service market to guarantee the stable operation of the power transmission. Virtual power plant (VPP) has been extensively studied as a concept that aggregates multiple resource forms to serve the electricity market. Meanwhile, with the development of energy Internet (EI) Error! Reference source not found., more attention has been focused on the optimization and operation of Integrated energysystem (IES), therefore, the introduction and exploration of Multi-energy Virtual power Plant (MVPP) provide possibilities for IES to participate in the Electricity Market and Ancillary Services Market. This paper extracts the flexible electric and heat load in the industrial production process, combining the CHP units and Electric Boiler (EB), which are main heat energy supply devices as well as energy Storage system (ESS) as a MVPP to provide Frequency Regulation (FR) service to the Auxiliary Service Market. Model Predictive control (MPC) method is applied to control the industrial load, the operation of CHP, EB and ESS are gonging to follow the AGC signal issued by the FR market effectively while avoiding impacts on the production process of the factory. Finally, case study validates the effectiveness of the model.
A microgrid system in the stand-alone mode with photovoltaic, wind turbine, microturbine, fuel cell and energy storage unit is studied. Mathematical models of different distributed power supply and energy storage devi...
A microgrid system in the stand-alone mode with photovoltaic, wind turbine, microturbine, fuel cell and energy storage unit is studied. Mathematical models of different distributed power supply and energy storage devices are established. The load demand of the system, the price of purchasing and selling electricity when interacting with the power grid and other constraints are considered. An economic model for optimizing stand-alone operation cost is established. According to the characteristics of the model, an improved genetic algorithm is selected to optimize the nonlinear system. The algorithm has better stability in solving the optimization problem of large state space dimension. The case study show that the proposed economic model is reasonable and the algorithm is effective.
Nowadays, the demand for energy is expanding, the fossil resources are on the verge of exhaustion, and the ecological environment is getting worse and worse. In this form, this paper studies the economic optimal dispa...
Nowadays, the demand for energy is expanding, the fossil resources are on the verge of exhaustion, and the ecological environment is getting worse and worse. In this form, this paper studies the economic optimal dispatch of microgrid under the background of energy saving and emission reduction. Firstly, the mathematical model of microgrid composed of distributed power, energy storage devices and loads is established. Secondly, under the background of energy saving and emission reduction, the objective function of multi-objective optimal operation of microgrid is established considering both economic and environmental aspects. Finally, the improved Genetic Algorithm is used to solve the objective function. The results of optimization can reduce microgrid system generation cost.
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