Abstract:The growth in volatile renewable energy (RE) generation is accompanied by an increasing network load and an increasing demand for storage units. Household storage systems and micro power plants, in particular, represent an uncertainty factor for distribution networks, as well as transmission networks. Due to missing data exchanges, transmission system operators cannot take into account the impact of household storage systems in their network load and generation forecasts. Thus, neglecting the increasing number… Show more
“…The energy level of energy storage is expressed by the state of charge of the battery 25 . After a period of time, the state of charge is: where SOC( t + t 1 ) and SOC( t ) are the state of charge of energy storage at time t + t 1 and time t , respectively.ΔSOC( t 1 ) is the change of the state of charge of energy storage in t 1 period.…”
Section: Mathematical Model Of Mitigation Equipmentmentioning
Summary
To reduce the investment cost of voltage sag mitigation equipment and the probability of voltage sag at the installation nodes of sensitive load, a comprehensive voltage sag mitigation strategy based on sensitive load clustering is proposed. The Monte Carlo method is used to get the stochastic estimation model of voltage sag to determine the lines with high fault probability, so as to get the weak links in the power grid, that is, the voltage sag vulnerable area. This paper proposes four sensitive indicators called tolerance magnitude of voltage sag, endurance duration of voltage sag, equipment capacity, and power dependence. The weight of each indicator is determined by the combination weighting method, and the affinity propagation (AP) clustering algorithm is used to classify different sensitive loads. The sensitive loads are mitigated by installing the energy storage equipment and dynamic voltage restorer (DVR), and the energy storage capacity is configured with the goal of minimum life cycle cost under the premise of voltage compensation. The result using MATLAB/Simulink and the laboratory equipment shows that, compared with existing mitigation strategies, the proposed mitigation strategy can not only effectively reduce the investment cost and the probability of voltage sag but also make the voltage distribution more reasonable.
“…The energy level of energy storage is expressed by the state of charge of the battery 25 . After a period of time, the state of charge is: where SOC( t + t 1 ) and SOC( t ) are the state of charge of energy storage at time t + t 1 and time t , respectively.ΔSOC( t 1 ) is the change of the state of charge of energy storage in t 1 period.…”
Section: Mathematical Model Of Mitigation Equipmentmentioning
Summary
To reduce the investment cost of voltage sag mitigation equipment and the probability of voltage sag at the installation nodes of sensitive load, a comprehensive voltage sag mitigation strategy based on sensitive load clustering is proposed. The Monte Carlo method is used to get the stochastic estimation model of voltage sag to determine the lines with high fault probability, so as to get the weak links in the power grid, that is, the voltage sag vulnerable area. This paper proposes four sensitive indicators called tolerance magnitude of voltage sag, endurance duration of voltage sag, equipment capacity, and power dependence. The weight of each indicator is determined by the combination weighting method, and the affinity propagation (AP) clustering algorithm is used to classify different sensitive loads. The sensitive loads are mitigated by installing the energy storage equipment and dynamic voltage restorer (DVR), and the energy storage capacity is configured with the goal of minimum life cycle cost under the premise of voltage compensation. The result using MATLAB/Simulink and the laboratory equipment shows that, compared with existing mitigation strategies, the proposed mitigation strategy can not only effectively reduce the investment cost and the probability of voltage sag but also make the voltage distribution more reasonable.
“…Various electricity storage systems can contribute achieving the following goals [9][10][11][12]: to balance the energy production and consumption; to reduce the total installed capacity of the power system; to increase the efficiency of energy use. Today different types of storage systems are used.…”
Improvement of the efficiency of modern power systems requires the development of storage technologies, optimization of operation modes, and increased flexibility. Currently, various technical solutions are used for electricity storage. The results of a literary review with an analysis of existing energy storage systems are presented, their advantages and disadvantages are considered. One of the promising solutions is the use of hydrogen as an energy storage medium. The creation of corresponding energy complexes makes it possible to obtain hydrogen by electrolysis of water, and then use it to cover peak loads. Various schemes with hydrogen-fired gas turbines with a pressure up to 35 MPa and a temperature of 1500–1700 °C were considered. The new scheme of power plant with hydrogen-fired gas turbines was synthesized, which includes a power block, hydrogen generation blocks and hydrogen and oxygen preparation unit for burning. An atmospheric electrolyzer was considered as a hydrogen and oxygen generator. For the proposed scheme, parametric optimization was performed, where the storage efficiency factor has been used as a criterion. The influence of inlet temperature in the combustion chamber, the compression rate of hydrogen and oxygen, as well as the specific energy costs of the electrolyzer were analyzed. The results of the numerical experiment were approximated in the form of polynomial dependencies, and can be used in further research on the economic efficiency of proposed power plant.
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