This paper introduces a new framework for optimum design and operation of hybrid renewable energy plants (HREP) augmented with battery energy storage systems (BESS). A new renewable energy management system (REMS) is developed comprising three components: 1) Enhanced joint forecasting of wind and solar outputs based on deep neural networks and also multiplicative weights update (MWU); 2) an advanced optimization model for sizing the HREP-BESS components and the policy of BESS operation; and 3) Augmenting the rolling hourly dispatch for HREP-BESS with a novel dynamic ramping limit and a criterion for reduction of deviations from the hour-ahead dispatch schedule. The proposed REMS tool enables maintaining the inter-hourly ramping of the HREP-BESS output within a threshold. In this context, a novel dynamic ramp limit is proposed to minimize the energy curtailment during operation and maximize energy sales to the power grid. The advantage of the proposed REMS tool over the classical renewable energy systems operation scheme is the mitigation of the volatility of renewable energy sources (RES) by suppressing extreme ramping events with minimum curtailment. Moreover, the costs and revenues of the HREP-BESS design and operation are assessed over a 25 years period. The design problem is solved for different scenarios, and the optimal solution always encloses a hybrid mix of renewables where the share of the PV plant can reach up to 37.1% of the total plant size. With the proposed REMS, the curtailment of RES never exceeds 12.9% even when the HREP is operated without a reserve margin. For the selected design, the optimum BESS capacity is 12.9% of the HREP capacity. The number of hours which observe a ramping violation event is 2.4% of the season's length (2184 hours). 99% of all ramping events fall within the defined ramping limits. The use of the MWU method increases the total profit by 2.53% compared with adopting the average forecast.

中文翻译：

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可再生能源管理系统：优化设计和每小时调度


本文介绍了一个新的框架，用于优化设计和运行混合可再生能源工厂（HREP）并增强电池储能系统（BESS）。开发了一种新的可再生能源管理系统（REMS），包括三个组成部分：1）基于深度神经网络和乘法权重更新（MWU）增强风能和太阳能输出的联合预测； 2）用于调整 HREP-BESS 组件大小和 BESS 运行策略的高级优化模型； 3) 通过新颖的动态爬坡限制和减少与提前一小时调度计划的偏差的标准，增强 HREP-BESS 的滚动每小时调度。所提出的 REMS 工具能够将 HREP-BESS 输出的每小时斜坡保持在阈值内。在此背景下，提出了一种新颖的动态斜坡限制，以最大限度地减少运行期间的能源削减并最大限度地提高向电网的能源销售。与传统的可再生能源系统运行方案相比，所提出的 REMS 工具的优点是通过以最小的限电抑制极端的斜坡事件来减轻可再生能源 (RES) 的波动性。此外，HREP-BESS 设计和运营的成本和收入是在 25 年期间进行评估的。针对不同场景解决设计问题，最佳解决方案始终包含可再生能源的混合组合，其中光伏电站的份额最高可达电站总规模的37.1%。根据拟议的 REMS，即使 HREP 在没有准备金的情况下运行，RES 的削减也不会超过 12.9%。对于所选设计，最佳 BESS 容量为 HREP 容量的 12.9%。观察到超速违规事件的小时数占赛季长度（2184 小时）的 2.4%。 99% 的斜坡事件都在定义的斜坡限制范围内。采用MWU方法，与采用平均预测相比，利润总额增加了2.53%。