基于灰熵关联择优的含不确定性预算调节策略的微电网鲁棒调度
发布时间：2019-02-09 15:18
【摘要】：以运行成本、环境成本和可再生能源波动最小为目标,建立了以灰熵关联度为最优解评价标准的微电网调度模型。针对风光发电的不确定性,构造以预测值为中心的不确定性集,引入鲁棒优化理论改进调度模型。针对储能系统在调度过程中可能过早到达其限值的问题,提出了一种通过储能运行状态来估计风光发电不确定性预算的策略。采用改进微分进化算法对算例进行求解,该算法结合云模型增强其局部搜索能力,依据混沌算法提升其全局搜索能力。仿真结果验证了模型和算法的可行性,从Pareto前沿的变化与最优解集的特征值两方面分析了鲁棒调度模型的优越性;讨论了在不同场景下不确定性预算值对微电网调度的影响,并验证了不确定性预算调节策略能更有效地防止储能系统到达储能上下限,从而进一步提高微电网调度的鲁棒性。
[Abstract]:Aiming at the minimum fluctuation of operation cost, environmental cost and renewable energy, a micro-grid dispatching model with grey entropy correlation degree as the optimal solution evaluation criterion is established. Aiming at the uncertainty of wind power generation, the uncertainty set centered on prediction value is constructed, and the robust optimization theory is introduced to improve the scheduling model. In order to solve the problem that the energy storage system may reach its limit too early in the dispatching process, a strategy for estimating the uncertain budget of wind-to-wind power generation by the storage state is proposed. An improved differential evolution algorithm is used to solve the numerical examples. The algorithm combines cloud model to enhance its local search ability and improves its global search ability according to chaos algorithm. The simulation results verify the feasibility of the model and the algorithm. The superiority of the robust scheduling model is analyzed from two aspects: the variation of the Pareto frontier and the eigenvalue of the optimal solution set. The effects of uncertain budget values on microgrid scheduling in different scenarios are discussed, and it is verified that the uncertain budget regulation strategy can more effectively prevent the energy storage system from reaching the upper and lower limits of energy storage, thus further improving the robustness of micro-grid scheduling.
【作者单位】： 广西大学电气工程学院;
【基金】：国家自然科学基金资助项目(61364027) 广西自然科学基金资助项目(2014GXNSFAA118384)~~
【分类号】：TM73
[Abstract]:Aiming at the minimum fluctuation of operation cost, environmental cost and renewable energy, a micro-grid dispatching model with grey entropy correlation degree as the optimal solution evaluation criterion is established. Aiming at the uncertainty of wind power generation, the uncertainty set centered on prediction value is constructed, and the robust optimization theory is introduced to improve the scheduling model. In order to solve the problem that the energy storage system may reach its limit too early in the dispatching process, a strategy for estimating the uncertain budget of wind-to-wind power generation by the storage state is proposed. An improved differential evolution algorithm is used to solve the numerical examples. The algorithm combines cloud model to enhance its local search ability and improves its global search ability according to chaos algorithm. The simulation results verify the feasibility of the model and the algorithm. The superiority of the robust scheduling model is analyzed from two aspects: the variation of the Pareto frontier and the eigenvalue of the optimal solution set. The effects of uncertain budget values on microgrid scheduling in different scenarios are discussed, and it is verified that the uncertain budget regulation strategy can more effectively prevent the energy storage system from reaching the upper and lower limits of energy storage, thus further improving the robustness of micro-grid scheduling.
【作者单位】： 广西大学电气工程学院;
【基金】：国家自然科学基金资助项目(61364027) 广西自然科学基金资助项目(2014GXNSFAA118384)~~
【分类号】：TM73
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