首页> 外文会议>IEEE Power Energy Society Innovative Smart Grid Technologies Conference >Impact of Incentive Based Demand Response on large scale renewable integration
【24h】

Impact of Incentive Based Demand Response on large scale renewable integration

机译:基于激励的需求响应对大规模可再生整合的影响

获取原文

摘要

The large scale deployment of renewable generation is generally seen as the most promising option for displacing fossil fuel generators, especially coal-fired power plants. A key challenge in integrating Renewable Energy Resources (RERs) is to find approaches that ensure long term sustainability and economic profit. One approach for mitigating the variability issue of integrating RERs is Demand Response (DR). The majority of current research is focuses on the role of DR for reliability support while economic concerns of RERs are barely addressed. In this paper, we investigate how DR can provide a potential solution to improve economic integration of RERs. More specifically, we propose Incentive Based DR (IBDR) programs, which is generally more attractive than real-time pricing programs for small customers. The proposed optimization framework in this paper finds an adequate amount of load change and incentive payments at each hour using a behavior model of customers. For this case study, the retirement of seven coal-fired power plants and expansion of RERs from less than 5% to 30%, is simulated for one year using data in the reduced WECC 240-bus system. Results show although renewable expansion could lead to benefit loss for utilities and sharp changes in market price, the proposed IBDR program could minimize these impacts.
机译:可再生生成的大规模部署通常被视为使化石燃料发电机(特别是燃煤发电厂)的最有前途的选择。整合可再生能源资源(RERS)的关键挑战是寻找确保长期可持续性和经济利润的方法。用于减轻整合RERS的变异性问题的一种方法是需求响应(DR)。大多数目前的研究专注于DR为可靠性支持的作用,而RERS的经济问题几乎没有解决。在本文中,我们调查DR如何提供潜在的解决方案,以改善RERS的经济融合。更具体地说,我们提出了基于激励的博士(IBDR)计划,这通常比小客户的实时定价计划更具吸引力。本文所提出的优化框架在每小时使用客户的行为模型找到了足够的负载变化和激励付款。为此,使用减少的WECC 240总线系统中的数据,将七个燃煤发电厂的退休和从少于5%的膨胀率低于5%至30%。结果显示虽然可再生扩张可能导致公用事业损失和市场价格急剧变化,所提出的IBDR计划可以最大限度地减少这些影响。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号