Because of their renewable and non-polluting characteristics in power production, distributed photovoltaics have been developed, but they have also been criticized for the volatility of their output power. In this paper, an integrated energy system optimal dispatching model is proposed to improve the local absorption capacity of distributed photovoltaics. First, an integrated energy system consisting of electricity, heat, cooling, gas, and hydrogen is modeled, and a mathematical model of the system is constructed. After that, the uncertainty of distributed photovoltaic power and load demand is modeled, and a typical scenario data set is generated through Monte Carlo simulation and K-means clustering. Finally, an optimal dispatching model of the integrated energy system is constructed to minimize the daily operating cost, including energy consumption, equipment operation and maintenance, and curtailment penalty costs, as the optimization objective. In the objective, a segmented curtailment penalty cost is Introduced. Moreover, this paper presents a chance constraint to convert the optimization problem containing uncertain variables into a mixed integer linear programming problem, which can reduce the difficulty of the solution. The case shows that the proposed optimal dispatching model can improve the ability of photovoltaics to be accommodated locally. At the same time, due to the introduction of the segmented curtailment penalty cost, the system improves the absorption of distributed photovoltaic generation at peak tariff intervals and enhances the economy of system operation.
Pumped hydropower is one of the most important renewable energy in a power grid, which is converted into electricity through pumped storage hydropower systems (PSHS). However, the energy conversion process of a PSHS may be greatly threatened by extreme working conditions, especially successive load rejections (SLR). In order to obtain the optimal control scheme for SLR, this paper aims to study the control optimization strategies so as to achieve safe and stable operation of PSHS. Firstly, a refined nonlinear PSHS model for SLR is constructed and validated by field data. Then, a novel optimization strategy incorporating multiple objectives, multiple guide vane control law (GVCL) schemes and multiple engineering constraints are proposed. The result shows that the proposed optimization strategy is effective for solving the control problem of PSHS under SLR, the optimal GVCL for SLR can be obtained by only one optimization.
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