半月刊
ISSN 1000-1026
CN 32-1180/TP
半月刊
ISSN 1000-1026
CN 32-1180/TP
1.南京工业大学电气工程与控制科学学院，江苏省南京市 211816;2.国网青海省电力有限公司，青海省西宁市 810008;3.中国电力科学研究院有限公司(南京)，江苏省南京市 210003
文中建立了考虑长期合约交易电量约束的新能源高占比送端电网随机生产模拟两层框架。其中，上层根据系统多年运行数据提取负荷和新能源出力特性，并考虑水电丰、枯水期的季节特性进行长周期随机生产模拟，求解送端电网待优化目标年、月内的日直流外送电量；下层结合上层优化得到的日直流外送电量和日前预测场景进行日前直流外送功率的调整优化，采用分布鲁棒优化模型，根据不确定分布集合的形式，将不确定问题转换为确定性二次约束二次规划(QCQP)问题，进一步采用重构线性化技术将QCQP模型转化为易于求解的线性规划问题，将日前优化得到的直流外送修正电量返送至上层，通过重启上层优化可以更新后续剩余合约电量及分配计划，以更新后续日前调度优化的直流外送初值。参照中国西北某省级送端电网的能源构成和分布建立仿真算例进行验证，结果表明所提方法在保证安全性的同时，有效提高了系统运行的经济性，促进了新能源的消纳。
国家电网公司科技项目（全清洁能源的特高压跨区外送系统源网协调关键技术研究，4000-202034053A-0-0-00）。
陈浩(1996—)，男，硕士研究生，主要研究方向：电力系统调度运行与控制。E-mail：934775061@qq.com
郝丽丽(1979—)，女，通信作者，副教授，主要研究方向：电力系统调度运行与控制。E-mail：lili_hao@163.com
吕肖旭(1998—)，男，硕士研究生，主要研究方向：新能源发电规划与运行控制。
1.School of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China;2.State Grid Qinghai Electric Power Co., Ltd., Xining 810008, China;3.China Electric Power Research Institute (Nanjing), Nanjing 210003, China
A two-layer stochastic production simulation framework for the sending-end power grid with a high proportion of renewable energy resource is established considering the trading electricity quantity constraint of long-term contract. In the upper layer, based on the characteristics of the load and renewable energy output extracted from the system multi-year operation data, the long-term stochastic production simulation is carried out considering the seasonal characteristics of hydropower during the high-water period and low-water period to solve the daily DC transmission electricity quantity of the sending-end power grid in the target year and month to be optimized. In the lower layer, the day-ahead DC transmission power is optimized and adjusted based on the daily DC transmission electricity quantity obtained by the optimization in the upper layer and the day-ahead forecasting scenario. The uncertain problem is transformed into a deterministic quadratically constrained quadratic programming (QCQP) problem by the distributionally robust optimization model according to the form of an uncertain distribution set. Furthermore, the QCQP model is transformed into a linear programming problem which is easy to solve by the reformulation linearization technique. The DC transmission revised electricity quantity obtained by the day-ahead optimization is sent back to the upper layer. The optimization of the upper layer is then restarted to update the remaining contract electricity quantity for the subsequent period and its distribution plan, so as to update the initial DC transmission value of the day-ahead scheduling optimization. According to the energy composition and distribution of a provincial sending-end power grid in northwest China, a simulation example is established for verification. The results show that the proposed method can not only ensure the safety, but also effectively improve the economy of system operation and promote the consumption of renewable energy resource.
| [1] | 陈浩,郝丽丽,吕肖旭,等.特高压直流合约交易电量约束下送端电网日前调度优化[J].电力系统自动化,2022,46(17):218-227. DOI:10.7500/AEPS20211028005. CHEN Hao, HAO Lili, LYU Xiaoxu, et al. Day-ahead Scheduling Optimization of Sending-end Power Grid Under Trading Electricity Quantity Constraint of UHVDC Contract[J]. Automation of Electric Power Systems, 2022, 46(17):218-227. DOI:10.7500/AEPS20211028005. |
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