Abstract
Based on the high proportion of renewable energy connected to the active distribution network, this article studies the joint planning of demand-side response and energy storage. Firstly, a two-level optimization model is established for the planning of active distribution network. The upper level objective function is the investment, operation and maintenance cost of energy storage and fan, and the lower level objective function is the annual network loss cost. Then, the improved Longhorn algorithm is used to solve the two-layer programming model, and the combination of Longhorn beard algorithm and particle swarm optimization algorithm not only improves the iteration speed, but also improves the global searching ability. Finally, the example analysis proves the effectiveness of joint planning to solve the high proportion of renewable energy, thus improving the economic benefits.
Highlights
Due to the energy crisis, the development of power sources in the power grid is more diversified, and the massive access of Distributed Generator (DG) brings many problems to the distribution network [1]
In order to solve the problem between network collaborative planning of distributed power supply, literature [7] proposes to establish an overall planning framework and model aiming at the comprehensive economic benefits of DG and Active distribution network (ADN)
The above studies have achieved in-depth results in terms of energy storage and demand side response, but few studies have considered the impact of large-scale renewable energy access to the power system on the power system, and no in-depth studies have been carried out in terms of calming wind power fluctuations, including Battery Energy Storage System (BESS) and DSR, which are considered comprehensively
Summary
Due to the energy crisis, the development of power sources in the power grid is more diversified, and the massive access of Distributed Generator (DG) brings many problems to the distribution network [1]. In order to solve the problem between network collaborative planning of distributed power supply, literature [7] proposes to establish an overall planning framework and model aiming at the comprehensive economic benefits of DG and ADN. Literature [9] further solves the load fluctuation problem caused by large-scale renewable energy access to the power system, proposes a BESS configuration method combining local and overall, and uses particle swarm optimization algorithm to solve the optimization problem. The above studies have achieved in-depth results in terms of energy storage and demand side response, but few studies have considered the impact of large-scale renewable energy access to the power system on the power system, and no in-depth studies have been carried out in terms of calming wind power fluctuations, including BESS and DSR, which are considered comprehensively. Vr ≤ v ≤ vout , where Pw is the output power of wind turbine, Pwr is the rated active power of the wind turbine, vin, vr, vout are the inlet value, outlet value and rating value of wind speed respectively
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