In this paper, an efficient methodology is proposed to deal with segmented-time reconfiguration problem of distribution networks coupled with segmented-time reactive power control of distributed ...generators. The target is to find the optimal dispatching schedule of all controllable switches and distributed generators' reactive powers in order to minimize comprehensive cost. Corresponding constraints, including voltage profile, maximum allowable daily switching operation numbers (MADSON), reactive power limits, and so on, are considered. The strategy of grouping branches is used to simplify the formulated mathematical problem and a hybrid particle swarm optimization (HPSO) method is presented to search the optimal solution. Fuzzy adaptive inference is integrated into basic HPSO method in order to avoid being trapped in local optima. The proposed fuzzy adaptive inference-based hybrid PSO algorithm (FAHPSO) is implemented in VC++ 6.0 program language. A modified version of the typical 70-node distribution network and several real distribution networks are used to test the performance of the proposed method. Numerical results show that the proposed methodology is an efficient method for comprehensive cost minimization in distribution systems with distributed generators.
With the growing integration of distributed energy resources (DERs), flexible loads, and other emerging technologies, there are increasing complexities and uncertainties for modern power and energy ...systems. This brings great challenges to the operation and control. Besides, with the deployment of advanced sensor and smart meters, a large number of data are generated, which brings opportunities for novel data-driven methods to deal with complicated operation and control issues. Among them, reinforcement learning (RL) is one of the most widely promoted methods for control and optimization problems. This paper provides a comprehensive literature review of RL in terms of basic ideas, various types of algorithms, and their applications in power and energy systems. The challenges and further works are also discussed.
Grid-connected wind turbines are fluctuating power sources that may produce flicker during continuous operation. This paper presents a simulation model of a megawatt-level variable-speed wind turbine ...with a full-scale back-to-back power converter developed in the simulation tool of PSCAD/EMTDC. Flicker emission of this system is investigated. Reactive power compensation is mostly adopted for flicker mitigation. However, the flicker mitigation technique shows its limits, when the grid impedance angle is low in some distribution networks. A new method of flicker mitigation by controlling active power is proposed. It smoothes the 3p active power oscillations from wind shear and tower shadow effects of the wind turbine by varying the dc-link voltage of the full-scale converter. Simulation results show that damping the 3p active power oscillation by using the flicker mitigation controller is an effective means for flicker mitigation of variable-speed wind turbines with full-scale back-to-back power converters during continuous operation.
A time-variable time-of-use electricity price can be used to reduce the charging costs for electric vehicle (EV) owners. Considering the uncertainty of price fluctuation and the randomness of EV ...owner's commuting behavior, we propose a deep reinforcement learning based method for the minimization of individual EV charging cost. The charging problem is first formulated as a Markov decision process (MDP), which has unknown transition probability. A modified long short-term memory (LSTM) neural network is used as the representation layer to extract temporal features from the electricity price signal. The deep deterministic policy gradient (DDPG) algorithm, which has continuous action spaces, is used to solve the MDP. The proposed method can automatically adjust the charging strategy according to electricity price to reduce the charging cost of the EV owner. Several other methods to solve the charging problem are also implemented and quantitatively compared with the proposed method which can reduce the charging cost up to 70.2% compared with other benchmark methods.
There is more wind with less turbulence offshore compared with an onshore case, which drives the development of the offshore wind farm worldwide. Since a huge amount of money is required for ...constructing an offshore wind farm, many types of research have been done on the optimization of the offshore wind farm with the purpose of either minimizing the cost of energy or maximizing the total energy production. There are several factors that have an impact on the performance of the wind farm, mainly energy production of wind farm which is highly decided by the wind condition of construction area and micro-siting of wind turbines (WTs), as well as initial investment which is influenced by both the placement of WTs and the electrical system design, especially the scheme of cable connection layout. In this paper, a review of the state-of-art researches related to the wind farm layout optimization as well as electrical system design including cable connection scheme optimization is presented. The most significant factors that should be considered in the offshore wind farm optimization work is highlighted after reviewing the latest works, and the future needs have been specified.
► Quantify the extent to which electric vehicle can further the renewable energy integration. ► Electric vehicle can increase wind power integration by 8% in the case of Inner Mongolia. ► Mutual ...benefits have achieved between energy system and transport. ► Some negative consequences are caused when applying fuel cell vehicle.
Renewable energy is one of the possible solutions when addressing climate change. Today, large-scale renewable energy integration needs to include the experience to balance the discrepancy between electricity demand and supply. The electrification of transportation may have the potential to deal with this imbalance and to reduce its high dependence on oil production. For this reason, it is interesting to analyse the extent to which transport electrification can further the renewable energy integration. This paper quantifies this issue in Inner Mongolia, where the share of wind power in the electricity supply was 6.5% in 2009 and which has the plan to develop large-scale wind power. The results show that electric vehicles (EVs) have the ability to balance the electricity demand and supply and to further the wind power integration. In the best case, the energy system with EV can increase wind power integration by 8%. The application of EVs benefits from saving both energy system cost and fuel cost. However, the negative consequences of decreasing energy system efficiency and increasing the CO2 emission should be noted when applying the hydrogen fuel cell vehicle (HFCV). The results also indicate that developing renewable energy is crucial for transportation electrification.
Conventional methods for calculating tension currently suffer from an excessive simplification of boundary conditions and a vague definition of effective cable length, both of which cause inaccurate ...cable tension calculations. Therefore, this study utilizes bridge field data to establish a BP neural network for tension prediction, with design cable length, line density, and frequency as the input parameters and with cable tension as the output parameter. After disregarding the selection of effective cable length and innovatively integrating the particle swarm optimization–back propagation (PSO-BP) neural network for tension prediction, it is found that the MAPE between the predicted results of the BP neural network and the actual tension values is 7.93%. After optimization using the particle swarm optimization algorithm, the mean absolute percentage error (MAPE) of the neural network prediction is reduced to 2.78%. Both of these values significantly outperform those obtained from the theoretical equations of string vibration. Moreover, the MAPE of PSO-BP also surpasses that of the optimized calculation formulas in the literature. Utilizing the PSO-BP neural network for tension prediction avoids inaccuracies in tension calculation caused by an excessive simplification of boundary conditions and a vague definition of effective cable length; thus, it possesses certain engineering practical value.
The Danish power system has a large penetration of wind power. The wind fluctuation causes a high variation in the power generation, which must be balanced by other sources. The battery storage-based ...Plug-In Electric Vehicles (PEVs) may be a possible solution to balance the wind power variations in the power systems with high wind power penetrations. In this paper, the integration of plug-in electric vehicles in the power systems with high wind power penetrations is proposed and discussed. Optimal operation strategies of PEV in the spot market are proposed in order to decrease the energy cost for PEV owners. Furthermore, the application of battery storage based aggregated PEV is analyzed as a regulation services provider in the power system with high wind power penetrations. The western Danish power system where the total share of annual wind power production is more than 27% of the electrical energy demand is chosen as the studied case. The results show that an optimal operation of PEV in both spot market and regulation market can not only decrease the energy costs for PEV owners, but also significantly decrease the power deviations between West Denmark and Union for the Coordination of Electricity Transmission (UCTE) control areas.
Due to the wind speed variation, wind shear and tower shadow effects, grid connected wind turbines are the sources of power fluctuations which may produce flicker during continuous operation. This ...paper presents a model of an MW-level variable-speed wind turbine with a doubly fed induction generatorto investigate the flicker emission and mitigation issues. An individual pitch control (IPC) strategy is proposed to reduce the flicker emission at different wind speed conditions. The IPC scheme is proposed and the individual pitch controller is designed according to the generator active power and the azimuth angle of the wind turbine. The simulations are performed on the NREL (National Renewable Energy Laboratory) 1.5-MW upwind reference wind turbine model. Simulation results show that damping the generator active power by IPC is an effective means for flicker mitigation of variable speed wind turbines during continuous operation.
In recent years, the global environmental pollution and energy crisis are becoming more and more serious. The Li-ion battery is widely used in vehicles due to long cycle life and high energy density. ...The state of charge (SOC) of Li-ion battery is an important indicator. The accurate estimation of SOC can ensure the safe operation of Li-ion battery. However, the traditional estimation method, the ampere-hour integration method, has a cumulative error and cannot maintain good results for a long time in an operating environment with the Gaussian noise. To this end, this paper firstly applies Thevenin equivalent circuit model of a battery to establish estimation model, and it can reflect the working state of the battery. Then, the extended Kalman filtering algorithm is employed to solve the estimation error caused by Gaussian noise. Finally, the test system is built in MATALAB/Simulink to investigate the performance of the proposed method. Simulation results show that the proposed method achieves better performance, and it has higher estimation accuracy in comparison with traditional methods under different working conditions.
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