Abstract
The collaborative planning of a wind-photovoltaic (PV)-energy storage system (ESS) is an effective means to reduce the carbon emission of system operation and improve the efficiency of resource collaborative utilization. In this paper, a wind-PV-ESS collaborative planning strategy considering the morphological evolution of the transmission and distribution network is proposed. Firstly, aiming at the optimal economy of transmission and distribution network and considering the constraints of safe and stable operation of the system, the planning model of the transmission network based on DC power flow and the planning model of the distribution network based on AC power flow are constructed. Further, considering the coupling interaction between the transmission and distribution networks, a collaborative planning model of transmission and distribution networks based on second-order cone relaxation (SOCR) is constructed. Secondly, in order to reduce the computational complexity of the model and ensure the global optimality of the model solution, a fast model solution method based on heterogeneous decomposition architecture is proposed. Thirdly, the multiple driving factors of the morphological evolution of transmission and distribution network are analyzed, the morphological evolution path and typical characteristics of transmission and distribution network are determined, and a wind-PV-ESS collaborative planning strategy considering the morphological evolution of a transmission and distribution network is proposed. Finally, the results show that, compared with the sprouting period, the overall economy of the development period and maturity period is improved by 3342 k$ and 5751 k$ respectively, and the effectiveness and necessity of the collaborative planning strategy proposed in this paper is verified.
Highlights
New energy power generation has the characteristics of environment-friendly, low carbon emission, and rich resources
To address the above problems, this paper proposes a wind-photovoltaic-energy storage system collaborative planning strategy considering the morphological evolution of transmission and distribution networks
Based on the above research, this paper further proposes a cooperative planning strategy for wind-PV-energy storage system (ESS) in transmission and distribution networks based on heterogeneous decomposition architecture
Summary
New energy power generation has the characteristics of environment-friendly, low carbon emission, and rich resources. Collaborative planning and operation optimization of an active distribution network (ADN) considering large-scale new energy access has gradually become a hot academic research topic. The existing studies on transmission and distribution cooperative optimization mainly focus on the optimal power flow and day-ahead dispatching level, and fail to fully consider the impact of transmission and distribution network coupling interaction on the planning results. To address the above problems, this paper proposes a wind-photovoltaic-energy storage system collaborative planning strategy considering the morphological evolution of transmission and distribution networks. The construction of the wind-PV-ESS collaborative planning model for transmission and distribution networks is the basis for planning strategy development, and its general expression form can be written as follows: min f T − D = min[ f trans Xtrans,i ,Mtrans,i + f dis Xdis,j ,Mdis,j ]. Considering the structural characteristics of the transmission and distribution networks and the overall computational efficiency of the model, this paper constructs the transmission network scenic storage cooperative planning model considering DC power flow constraint and the distribution network scenic storage cooperative planning model based on AC power flow, further considers the transmission and distribution network coupling, and uses SOCR to perform convex relaxation on the non-convex terms of the distribution network model and, the SOCR-based transmission and distribution cooperative convex optimization model is obtained
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