Reasonably arranging the matching of power sources is an effective mean to improve the capacity of new energy consumption. Using the dispatching characteristics of the transferable load of the energy storage systems c...
Reasonably arranging the matching of power sources is an effective mean to improve the capacity of new energy consumption. Using the dispatching characteristics of the transferable load of the energy storage systems can play an important role in the actual dispatch of the powersystem. From the perspective of flexible scheduling, a multi-domain scheduling method is proposed, which comprehensively considers the influence of factors such as load, wind power output random fluctuations and system adjustment capabilities, and redistributes it into three control domains. That is, the normal control domains with the goal of completely absorbing wind power, anomaly control domain where the energy storage systems needs to be used to absorb wind power, and the emergency control domain where there is no regulation ability and forced to abandon wind. To maximizing clean energy consumption, CPLEX software is used to optimize output and realize multi-domain green economic dispatch. The calculation example shows that this method can effectively improve the absorption capacity of clean energy.
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
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.
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.
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