研究目的
To minimize the developer’s investment cost associated with energy supply requirements over a predefined planning period in distribution networks with high penetration of photovoltaic-based distributed generation, considering uncertainties in supply, demand, and energy prices, and introducing smart curtailment of renewable resources.
研究成果
The proposed planning scheme effectively optimizes the sizing and allocation of renewable DG units in distribution networks, reducing overall investment costs. Smart curtailment allows for higher installed capacities of PV DG by mitigating technical system violations, leading to higher savings and renewable DG penetration.
研究不足
The study assumes a smart distribution system with communication infrastructure for implementing smart curtailment. The selection of candidate buses for DG allocation is arbitrary, and detailed techno-economic planning analysis for bus selection is outside the scope of this work.
1：Experimental Design and Method Selection:
The study employs a planning algorithm for a distribution system to find the optimal scenario that minimizes the developer’s investment cost over a 20-year study period, considering smart curtailment to avoid technical violations.
2：Sample Selection and Data Sources:
The study uses a 38-bus 12.66kV distribution system for case studies, with six candidate buses selected for DG allocation. Solar irradiance historical data and load demand data are utilized for modeling.
3：66kV distribution system for case studies, with six candidate buses selected for DG allocation. Solar irradiance historical data and load demand data are utilized for modeling.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Not explicitly mentioned in the abstract.
4：Experimental Procedures and Operational Workflow:
The methodology involves modeling the output power of PV DG units, load variability, and energy prices, and combining these models to form a multi-state system model. The planning problem is solved to satisfy active and reactive power balance constraints, voltage limits, and thermal limits.
5：Data Analysis Methods:
The fitness function to be minimized is represented by the overall cost composed of initial costs and continuing costs, with results analyzed for three cases: base case without DG, DG allocation without curtailment, and DG allocation with smart curtailment.
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