基于随机森林非侵入式负荷分解的地区居民需求响应能力评估

需求响应在缓解供电不足、促进新能源消纳以及节约发电侧的资源投资方面意义重大,而需求响应能力评估可以为需求响应策略的制定提供依据。为解决需求响应能力评估困难的问题,本文提出一种基于非侵入式负荷分解的地区居民响应能力评估的方法。首先建立基于随机森林算法的非侵入式负荷分解模型,再使用该模型针对性的分解出单个用户的可中断负荷,然后基于可中断负荷的用电情况计算出单个用户在各个时刻的响应能力,最后再将区域内的所有用户聚合即可得到地区居民总的响应能力。在真实数据集上进行验证,结果表明所提出的基于随机森林非侵入式负荷分解模型可以更精确的得到用户可中断负荷的有功功率值,地区有功功率聚合误差也更小,可以较好的进行需求响应能力评估。     

Net-zero energy building clusters emulator for energy planning and operation evaluation

The emergence of smart grids, Net-zero energy buildings, and advanced building energy demand response technologies continuously drives the needs for better design and operation strategies for buildings and distributed energy systems. It is envisioned that similar to micro-communities in a human society, neighboring buildings will have the tendency to form a building cluster, an open cyber-physical system to exploit the economic opportunities provided by smart grids and distributed energy systems. To realize this building cluster envision, it requires better urban energy planning and operation control strategies to determine which type of buildings should be clustered and what operation strategies should be implemented to fully utilize the potential in load aggregation, load shifting, and resource allocation. However, most of the current tools are focusing on single buildings or devices, which are not suitable for building cluster studies. To this end, this study proposes to develop a Net-zero building cluster emulator that can simulate realistic energy behaviors of a cluster of buildings and their distributed energy devices as well as exchange operation data and control schemes with real-world building control systems. The developed emulator has the flexibility to integrate with different buildings and distributed energy systems to study the performance of this building cluster to propose suggestions in urban energy planning and operation. To show the application of this emulator, a proof-of-concept demonstration is also presented in this paper.     

计及碳捕集电厂灵活运行与需求响应的多时间尺度调度

充分挖掘电力系统潜在的灵活性资源可有效提高系统中可再生能源的消纳能力。碳捕集电厂可降低电力系统中碳排放,同时也提供潜在的灵活调节能力。本文建立了需求响应与碳捕集电厂的灵活调节模型,提出了计及碳捕集电厂灵活运行与需求响应的多时间尺度调度方法,并将其应用到电力系统的调度运行中,实现系统运行总成本的最小化。在日前调度阶段,采用需求响应、碳捕集电厂灵活调节来时移负荷需求,以实现系统低碳经济运行的目标;在日内调度阶段,采用预测控制模型来校正日前调度计划,以保证实时功率平衡。结果显示,需求响应和碳捕集电厂灵活运行可提高系统的可再生能源消纳量,同时可分别降低18.7%和1.4%的总成本,协同碳捕集电厂与需求响应可降低系统总成本20.1%,效果显著。     

邻域自适应粒子群算法求解地源热泵区域 能源系统鲁棒优化调度问题

针对地源热泵区域能源系统中冷热负荷和机组效能的不确定性, 本文提出了一种考虑双重不确定性的鲁棒优化调度方法. 首先, 基于多面体不确定模型描述调度模型中的鲁棒变量. 然后, 针对建筑冷热负荷不确定性, 采用对偶原理将双层优化模型等价为单层优化模型; 对于机组效能不确定性, 采用场景法进行分析. 最后, 采用多目标优化约束处理方法处理鲁棒优化调度模型中的约束条件. 同时, 为更加高效、准确求解所构建的优化调度模型, 提出了一种邻域自适应粒子群优化算法(NAPSO). 实验结果表明, 在制冷和制热工况下, 与经验运行策略相比, 本文所提方法可分别减少7.22%和5.55%的系统运行成本, 是一种解决地源热泵区域能源系统鲁棒优化调度的有效方法.     

多台冷水机组联合运行优化控制策略

冷水机组通常占建筑物系统总能耗的主要部分,因此冷水机组运行数量控制在实现空调系统节能方面起着重要作用。针对多台冷水机组联合运行时台数选择和负荷分配不合理的问题,文章将通过TRNSYS模拟得出的负荷值聚类分析,确定不同负荷值对应的冷水机组运行台数,并提出一种冷水机组排序优化控制方法改善顺序控制方式以实现其合理运行与节能。以某大型办公建筑为例,将优化控制前后冷水机组运行的进行总能耗对比。实验结果表明:与顺序控制相比,冷水机组优化控制后两个工作日总能耗分别节约126.1kW和342.5 kW,节能率分别为4.15%和5.22%。通过利用冷水机组顺序优化控制可满足建筑的冷负荷需求同时实现降低系统能耗,在空调系统节能方面具有工程实际应用价值。     

考虑共享电池站和温控负荷响应的综合能源系统优化调度

针对区域综合能源系统协同优化调度问题,构建基于能量枢纽(energy hub,EH)的分层能量管理框架,充分考虑新能源电厂、气-电、电-气能源转换装置调节能力,以共享电池站(shared battery station,SBS)替代传统储能电站,为能源系统提供电能存储功能,采用温控负荷为能源系统提供需求侧响应,保障异质...     

Graph-based algorithmic design and decision-making framework for district heating and cooling plant positioning and network planning

Although buildings are the single largest users of energy in cities, many individual building HVAC (heating, ventilation, and air conditioning) systems are energy inefficient. Sustainable district heating and cooling systems have been developed to address this inefficiency, however, the implementation of district heating and cooling systems is a complex, capital intensive multivariate problem. One critical engineering problem, the location of energy production plant and pipe network topology, has a major influence on the system performance as well as the life cycle cost, and therefore should be comprehensively studied and chosen. This paper proposes a novel algorithmic design and decision-making framework that uses multiple simultaneous criteria to generate and evaluate design alternatives of site selection and pipe network layout. The framework consists of three components: site location and topology generation, network sizing and evaluation, and multi-objective decision-making assistance. The proposed framework has been validated in a real-world district cooling greenfield project in China's metropolitan area. Results were compared against the engineers’ best practices. It has shown that the proposed framework could find equally good or better designs in engineering and financial performance with CAPEX reduction of up to 15%.     

Nonlinear model reduction and model predictive control of residential buildings with energy recovery

Residential and commercial buildings account for a significant portion of the electricity consumed in the United States. Their operation is subject to fluctuations in weather and occupancy which, in turn, are reflected in large variations in the load that buildings impose on the grid during the day and at night time. In view of mitigating such fluctuations (and their broader impact on energy generation), understanding the dynamic behavior of buildings and a focus on energy management (rather than simply temperature control), is essential. In this paper, we begin by analyzing building dynamics and use singular perturbation arguments to provide a theoretical justification for the empirically acknowledged multiple time scale dynamic response of buildings. We also derive reduced-order models for the dynamics in each time scale for a prototype residential building. Our analysis accounts for the potential use of heat recovery ventilators (HRVs), and we show that the presence of energy recovery leads to the emergence of a dynamic behavior with three time scales, including an overall, system-wide component which involves both the building and the HVAC system. We use our dynamic results to formulate a set of synthesis guidelines for control systems addressing either temperature regulation or geared towards minimizing operating cost. A detailed simulation case study demonstrates the application of the derived reduced-order models in the design of a nonlinear predictive model-based optimal energy management strategy for a model of a single-zone test building situated on the University of Texas campus. The proposed controller exhibits excellent performance, can easily be executed in real-time and has the capability to shift peak loads as part of a demand flattening strategy.     

多区域互联综合能源系统的双层博弈优化运行

为保障用户日益增长的能源消费需求、提高能源利用率,本文面向多区域综合能源系统,考虑综合需求响应,提出基于聚合商和用户双层博弈的优化运行方法.在包含聚合商、用户、综合能源系统和能源互联网络的多园区综合能源系统架构的基础上,建立了包括下层用户间非合作博弈和上层聚合商联盟合作博弈的双层博弈优化模型.其中,上层聚合商以多区域综...     

考虑需求响应激励机制的园区综合能源系统博弈优化调度

建设源荷协调、灵活互动的综合能源系统是构建新型电力系统的有效路径.在综合能源系统下,通过价格、补贴等激励手段合理调节用户侧需求响应机制可以促进综合能源系统的经济高效运行.为制定合理的需求响应激励机制,首先充分考虑源侧可再生能源出力和负荷侧多类能源需求的不确定性,提出随机场景生成策略;然后提出计及用户需求响应的综合能源系统博弈优化框架,分别以园区综合能源系统运营商和综合能源用户效益最大化为目标,建立双主体博弈优化调度模型,并提出快速高效的求解算法;最后,基于某实际园区综合能源系统开展多场景算例仿真分析,制定合理有效的需求响应价格激励方案.调度结果表明,所提出方案可以有效提升综合能源系统运行商和用户的效益.     

多级压缩空气储能系统变工况的优化运行控制

多级压缩空气储能系统以压缩空气储能及热存储技术为基础,具备冷、热、电多种能量存储及供给能力.针对多变复杂工况下系统热能合理分配问题,提出了一种多级压缩空气储能系统变工况优化运行控制策略.首先基于热力学方法分析,建立压缩空气储能系统模块化数学模型.其次根据系统负荷需求,在"以电定热"及"以热定电"两种工作模式下,分别以储热热量消耗量最小及输出电功最大为优化目标建立优化模型,求解得到不同工况下系统各部件运行参数,并以1 MW多级压缩空气储能系统为例,进行优化求解.该控制策略有效地解决了多级压缩空气储能系统在变工况下的内部能量调配、系统内部运行参数选取的问题,为实现系统高效运行提供有效途径.     

Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch

At the central energy management center in a power system, the real time controls continuously track the load changes and endeavor to match the total power demand with total generation in such a manner that the operating cost is minimized while all the operating constraints are satisfied. However, due to the strict government regulations on environmental protection, operation at minimum cost is no longer the only criterion for dispatching electrical power. The idea behind the environmentally constrained economic dispatch formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and harmful emission levels are both simultaneously minimized for a given load demand. Conventional optimization techniques become very time consuming and computationally extensive for such complex optimization tasks. These methods are hence not suitable for on-line use. Neural networks and fuzzy systems can be trained to generate accurate relations among variables in complex non-linear dynamical environment, as both are model-free estimators. The existing synergy between these two fields has been exploited in this paper for solving the economic and environmental dispatch problem on-line. A multi-output modified neo-fuzzy neuron (NFN), capable of real time training is proposed for economic and environmental power generation allocation.This model is found to achieve accurate results and the training is observed to be faster than other popular neural networks. The proposed method has been tested on medium-sized sample power systems with three and six generating units and found to be suitable for on-line combined environmental economic dispatch (CEED).     

基于时序计算的电力系统风电并网接纳能力研究

为了准确评估区域电力系统风电并网接纳能力．针对目前风电规划问题,给出了一种基于时序计算的分步优化方法。根据序列相等性原则,将系统负荷与系统机组出力视作供需双方,对系统机组出力进行序列化分析,在时序上达到供需匹配平衡。将系统消纳风电过程分解为两级过程,以分步求取系统最优运行方式。利用时序计算方法,定性分析系统风电消纳空间,结合风资源信息及系统负荷信息定量计算系统可接纳的风电电量。结合实际区域电网负荷数据及机组发电数据进行了仿真计算,仿真结果表明,该规划方法能准确评估区域电力系统风电接纳能力,从而可为风电产业规划提供技术参考指标。     

一种改进的智能电网能耗调度算法

为了提高电网的运行效率,提出一种新的实时能耗调度算法,通过考虑负载不确定性来实现每个用户的电费最小化.我们将负载调度描述为一个优化问题.为了降低计算复杂度,提出一种近似动态规划算法,以解决电器运行的调度问题.在研究问题时,考虑了必须运行和可控运行在内的不同电器.与大部分当前需求侧管理算法假设完全知晓用户用电需求不同,算法只需知道将来部分需求的估计即可.仿真结果表明,能量调度算法既降低了用户用电支出,又提高了负载需求的峰均比,为用户和电力公司带来收益.     

换热站并联水泵分布式优化控制

针对现有换热站并联水泵优化算法在集中式架构下控制适应性不足的问题,本文提出了一种改进的分布式并联水泵优化算法.首先,建立了并联水泵的分布式控制系统,并对该优化问题的数学模型进行描述,在目标函数中引入自适应非线性因子;然后,设计了改进的分布式果蝇优化算法,在该算法中每台水泵的控制器仅通过与邻居控制器交互信息即可完成并联水泵的优化;并且,在嗅觉搜索阶段,使用正弦余弦策略替代赋予个体距离与方向的随机策略;最后,以两个实际换热站中不同并联水泵系统为例对算法进行仿真验证,并基于仿真结果进行性能分析.结果表明,相较于传统算法,改进的分布式果蝇优化算法能得到更优的控制策略,有着收敛速度快、稳定性好和鲁棒性强的特点;并且该算法适用于不同系统的并联水泵优化问题,具有可扩展性.在实际工程验证中相较于集中式算法,该算法在总功率和计算时间上分别平均降低了5.47%和29.90%,因此,能够满足实际换热站中对并联水泵热负荷优化分配的需求.     

请求下降邻域叠加选取分布式P2P 视频点播调度

为实现对等架构的低成本视频流传输和实时播放要求,提出基于请求下降叠加选 取的分布式P2P 视频点播调度算法。首先,基于叠加技术构建P2P 视频点播的技术指标,充分 考虑输入邻域节点、输出邻域节点和媒体服务器负载3 组优化指标,构建叠加架构和分布式算 法流程;其次,利用请求下降策略对发送节点和服务节点选取进行改进,解决可能出现的带宽 低利用率和无效的视频播放问题;最后,通过BitTorrent 视频点播系统对所提算法的有效性进 行了验证。     

Efficient immune algorithm for optimal allocations in series-parallel continuous manufacturing systems

This paper uses an immune algorithm (IA) meta-heuristic optimization method to solve the problem of structure optimization of series-parallel production systems. In the considered problem, redundant machines and buffers in process are included in order to attain a desirable level of availability. A procedure which determines the minimal cost system configuration is proposed. In this procedure, multiple choices of producing machines and buffers are allowed from a list of product available in the market. The elements of the system are characterized by their cost, estimated average up and down times, productivity rates and buffers capacities. The availability is defined as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. The proposed meta-heuristic is used as an optimization technique to seek for the optimal design configuration. The advantage of the proposed IA approach is that it allows machines and buffers with different parameters to be allocated.     

Development of a tool for urban microgrid optimal energy planning and management

Small-sized variable renewable energy sources (RES) live a large-scale development in urban electrical systems. They increase local high dynamic unbalancing and then can create instabilities on the inertia response. Thus, setting an adequate operating reserve (OR) power to compensate the unpredicted imbalance between RES generation and consumption is essential for power system security. Indeed, effective calculation and dispatching of OR considering inaccurate forecast of both RES and load demand can provide substantial cost reductions. Thus, to facilitate the energy management and system optimization in an urban microgrid (MG), a user-friendly tool for Energy Management System and Operational Planning has been developed. The tool provides a complete set of user-friendly graphical interfaces to study the details of photovoltaic (PV) and batteries, load demand, as well as micro gas turbines (MGTs). Furthermore, this energy management system allows system operators to properly model RES uncertainty. In addition, it could assist operators for the day-ahead energy management with an efficient information system and an intelligent management.     

Synthesis of nonlinear controller for wind turbines stability when providing grid support

This paper presents a new nonlinear polynomial controller for wind turbines that assures stability and maximizes the energy produced while imposing a bound in the generated power derivative in normal operation (guarantees a smooth operation against wind turbulence). The proposed controller structure also allows eventually producing a transient power increase to provide grid support, in response to a demand from a frequency controller. The controller design uses new optimization over polynomials techniques, leading to a tractable semidefinite programming problem. The ability of the wind turbine to increase its power under partial load operation has been analysed. The aforementioned optimization techniques have allowed quantifying the maximum transient overproduction that can be demanded to the wind turbine without violating minimum speed constraints (that could lead to unstable behaviour), as well as the total generated energy loss. The ability to evaluate this shortfall has permitted the development of an optimization procedure in which wind farm overproduction requirements are divided into individual turbines, assuring that the total energy loss in the wind farm is minimum, while complying with the maximum demanded power constraints. Copyright © 2013 John Wiley & Sons, Ltd.     

基于改进烟花算法的并联冷机负荷分配优化

针对并联冷机负荷分配优化问题提出一种改进烟花算法,以并联冷机系统功耗最小为优化目标,以每台冷机的部分负荷率作为优化变量进行求解.在改进烟花算法中,首先针对基本烟花算法搜索初始解不均匀问题,提出基于混沌初始化的变量定义方法;然后针对高斯突变不利于跳出局部最优问题,采用变异范围更大的莱维飞行变异方法,提高了基本烟花算法的搜索能力;最后针对改进的烟花算法,以两个并联冷机系统测试案例对所提出的改进烟花算法性能进行测试,并与其他的优化算法的结果进行对比.实验表明,相比于其他算法,改进烟花算法可以得到较优的运行策略,具有较好的节能效果.