Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems

Demand Response (DR) provides both operational and financial benefits to a variety of stakeholders in the power system. For example, in the deregulated market operated by the Electric Reliability Council of Texas (ERCOT), load serving entities (LSEs) usually purchase electricity from the wholesale market (either in day-ahead or real-time market) and sign fixed retail price contracts with their end-consumers. Therefore, incentivizing end-consumers’ load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market. As the first-of-its-kind implementation of Coupon Incentive-based Demand Response (CIDR), the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements, individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets, as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts. A number of methodologies are developed for this special type of DR program including price/baseline prediction, individualized target setting and a lottery mechanism. This paper summarizes the methodologies, design, critical findings, as well as the potential generalization of such an experiment. Comparison of the EnergyCoupon with a conventional Time-of-Use (TOU) price-based DR program is also conducted. Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries, the effective cost for demand response providers in EnergyCoupon can be substantially reduced, while achieving a similar level of demand reduction as conventional DR programs.     

综合考虑电动汽车充电与储能及可中断负荷调度的配电网两阶段灵活性提升优化方法

分布式电源出力的强波动性及电动汽车(EV)的无序充电使配电网的灵活性不足问题日益凸显,因此非常有必要通过灵活性资源的有效调度提高配电网灵活适应性。在充分分析配电网灵活性提升措施的基础上,提出了能够表征配电网灵活性的净负荷峰值裕度、净负荷谷值裕度、净负荷允许波动裕度3个灵活性评价指标;建立了综合考虑EV充电与储能及可中断负荷调度的配电网两阶段灵活性提升优化模型,阶段1构建了基于蒙特卡洛树搜索的EV有序充电策略,合理引导EV负荷在谷时段进行充电;阶段2在阶段1的基础上,建立了计及储能及可中断负荷的优化调度模型,并采用粒子群优化算法进行优化求解。IEEE 33节点系统算例验证了所提灵活性指标及EV有序充电模型的有效性,结果表明配电网两阶段灵活性提升优化方法能有效提升配电网的灵活性且整体经济性最优。     

清洁能源主导系统频率峰值特性分析

以清洁能源为主的异步送端电网频率稳定问题较为严重。为研究异步送端电网频率峰值变化机理,进一步提升频率质量、优化调频资源的分配,本文提出了一种清洁能源主导调频系统频率峰值及峰值时间的简化计算模型,该模型主要包括水电调速器主导调频模型及直流频率限制器(Frequency Limit Controller,FLC)主导调频模型。大系统的时域仿真结果表明了该模型的可靠性和准确性。本文还进一步探究了风电等新能源参与调频的可行性并评估了在不同季节下风电参与调频对频率质量的改善情况。     

基于博弈理论的电力系统扩展规划方法研究

随着我国电力建设的加强以及对电力系统研究的不断深入,如何根据电力市场中不同投资主体的优势和特点研究最合理的电力系统扩展规划方案,对于我国电力系统的可持续发展具有重要意义。提出了一种基于合作博弈的电力系统扩展规划方法。首先,根据电力市场下各主体的投资和收入情况,分别建立相对应的经济规划模型,进而,基于发电公司和电网公司之间的影响机理以及博弈行为分析,构建电力系统中不同投资主体间的合作博弈规划模型;然后,利用迭代搜索法对模型进行求解;最后,基于仿真算例验证了所提方法的正确性和有效性。     

基于改进花朵授粉算法与K-means算法的人体姿态库构建方法研究

为了解决现有人体姿态库构建方法存在的装备维修性仿真验证任务针对性不足的问题,提出了一种基于改进花朵授粉算法与K-means算法的人体姿态库构建方法。针对花朵授粉算法寻优精度不够理想的问题,将乌鸦搜索算法引入花朵授粉算法。提出了一种改进花朵授粉算法。测试结果表明：相比粒子群算法和花朵授粉算法,改进花朵授粉算法具有搜索范围广和寻优精度高的优点。为避免K-means算法易陷入局部最优解,将改进花朵授粉算法引入K-means算法,在提出个体编码方式与定义个体操作函数的基础上,设计了改进花朵授粉算法的计算步骤,使改进花朵授粉算法与K-means算法相融合,进而对装备维修人员的维修作业姿态进行聚类。提取各类中心数据,将其作为人体姿态库中虚拟人体的部位动作角度输入参数,构建了具有装备维修性仿真验证任务针对性的人体姿态库。仿真实验结果表明：相比基于粒子群算法与K-means算法融合的人体姿态库构建方法等5种方法,改进花朵授粉算法与K-means算法的融合方法具有寻优精度高和聚类效果好等优点,适用于装备维修性仿真验证工程实践。     

反潜巡逻机使用磁探仪应召搜潜效能模型

为快速发现锁定潜艇位置,对反潜巡逻机使用磁探仪应召搜潜效能模型进行研究。根据应召搜潜的特点, 结合反潜巡逻机使用磁探仪对潜搜索的方法,分析在应召搜潜条件下潜艇的机动模型和反潜巡逻机的航路模型方法, 建立反潜巡逻机使用磁探仪应召搜潜的效能模型,并进行仿真计算。在此基础上,分析了应召距离、潜艇航速、磁 探仪作用距离、飞机飞行高度、潜艇航向对发现概率的影响,对反潜巡逻机使用磁探仪应召搜潜的效能研究有一定 参考价值。     

基于网络搜索的商品房成交量预测研究

以全国商品房销售面积作为研究对象,以百度指数数据为基础,构建回归模型对全国商品房销售面积进行拟合和预测。结果表明:基于网络搜索数据的预测模型不仅能较好地预测全国商品房销售面积,具有较高的时效性,同时能够分析房地产市场各参与主体的行为趋势与规律。     

Shunt capacitor placement in radial distribution networks considering switching transients decision making approach

This paper provides a new approach in decision making process for shunt capacitor placement in distribution networks. The main core of the evaluation process is a multi-objective framework to allocate the capacitor banks. The power loss and the total harmonic distortion (THD) are the objective functions of the system under study in a long-term planning horizon. In order to select the executive plan introduced by using a multi-objective model, transient switching overvoltages have been considered. As the size and location of shunt capacitors may result in unacceptable overvoltages, the proposed technical decision making framework can be applied to avoid corresponding damages. In this paper, an iterative conventional power flow technique is introduced. This technique can be applied to evaluate THD for distribution networks as well as other power flow based objectives, such as power losses calculation and voltage stability assessment. The presented framework is a two stage one where at the first stage, a non-dominated sorting genetic algorithm (NSGA-II) augmented with a local search technique is used in order to solve the addressed multi-objective optimization problem. Then, at the second stage, a decision making support technique is applied to determine the best solution from the obtained Pareto front. In order to evaluate the effectiveness of the proposed method, two benchmarks are addressed in this paper. The first test system is a 9-bus distribution network and the second one is an 85-bus large scale distribution network. The simulation results show that the presented method is satisfactory and consistent with the expectation.     

基于万有引力搜索算法的微电网风光储容量优化配置

针对规模化风光储发电单元运行可靠性差、经济效益低等问题,通过采用多目标万有引力搜索算法,实现对风光储发电单元的优化配置。建立发电单元的输出功率模型,包括风力发电机输出功率模型、光伏电池输出功率模型和储能电池输出功率模型;采用某地区2015年1月至12月的风光数据,得出风机、光伏电池一年的输出功率。以风机、光伏电池及蓄电池的容量为决策变量,以成本、能源浪费率及缺电率最小为优化目标,得到最优风光储容量配置组合。     

基于日前调度的大规模中央空调调峰方法

共楼宇中央空调负荷具有时段性集中、负荷基数大、调控方式多、调控影响小等特点,已成为电力公司调峰的重要手段。首先分析了中央空调的能耗组成,基于示范实证提出了公共楼宇中央空调参与电网调峰的主要策略及效果,构建了大规模中央空调参与日前调峰的技术架构,并以电网公司补偿调峰用户费用最少为目标,计及调峰选项、调峰总量、调峰偏差等约束,提出了基于日前调度的大规模中央空调调峰优化模型,最后以江苏非工空调调控示范为例,借助CPLEX优化软件得出中央空调参与早、腰、晚高峰的调控组合方案。