RS-SVM forecasting model and power supply-demand forecast

A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.

Improved grey-based approach for power demand forecasting

Grey theory is a multidisciplinary and generic theory to cope with systems of poor or deficient information. We proposed in this paper an improved grey method (GM) to overcome the disadvantages of the general GM(1,1). In the improved GM(1,1), a new background value formula is deduced and Markov-chain sign estimation is imbedded into the residual modification model. We tested the efficiency and accuracy of our model by applying it to the power demand forecasting in Taiwan. Experimental results demonstrate the new method has obviously a higher prediction accuracy than the general model.

Power Market Analyses on 2001 and Demand Forecast for 2002

Based on the analysis on economic situation in China in 2001, the paperdiscusses power supply and demand features nationwide and by regions andprovinces, present estimation of power supply and demand in 2002. In conclusion,the paper presents suggestions to overcome difficulties on capital funds andtechniques.[

Analysis on the Situation of Power Supply and Demand in Shandong

In the first half of 2007, the power industry in Shandongprovince continued to maintain a rapid growth momentum.The gross electricity consumption amounted to 121.25 TWh,14.4% higher over that in the same period of last year. The totalinstalled capacity reached 53.29 GW. It was expected that bythe end of 2007, the gross electricity consumption in Shan-dong would reach 260 TWh, increasing by 14.4% on ayear-on-year basis; the maximum load would reach 40.

A Study of Power Sources Optimization in Guangdong

The main problem existing in Guangdong electric power sources is analyzed in this paper. Based on theanalysis on energy-supply features, power demand and the technical and economic performances of various powersources in Guangdong, the power sources construction scale and its structure are studied and analyzed in detail byusing Generation Expansion Software Package (GESP). The future development of Guangdong electric power sourcesunder the new situation of "Power from West to East" is studied as well.[

Operation Analysis of Electric Power Industry in the First Quarter 2001

The supply and demand features of China electric power market are elaborated in this paper, based on the data of power production and demand in the first quarter 2001, and the present situation on power supply and demand is analyzed from multi aspects.

Study of future power interconnection scheme in ASEAN

The current energy supply trajectory in the Association of Southeast Asian Nations(ASEAN)region is not sustainable.Factors such as rising standards of living and demographic patterns,including population growth,lead to continuous increase in power demand,which is difficult to meet using limited fossil fuel resources.Thus,a transition toward clean energy sources is needed in the region.While ASEAN member countries are rich in clean energy resources,such resources are located far from demand centers;thus,allocation of clean energy is necessary to increase its utilization.In this study,power demand is forecasted using a combination of prediction methods.A model to evaluate the installed capacity and power exchange potential is proposed to deal with mismatch between the location of the clean energy base and the load center.Furthermore,the concept of cross-regional allocation of clean energy between the ASEAN region,China,and South Asia is presented.A power interconnection scheme among the ASEAN member countries as well as neighboring countries is proposed based on the power exchange potential.The proposed grid interconnection scheme contributes to the utilization of clean energy in the ASEAN region,increasing the proportion of clean energy in the generation mix,which ensures that the region becomes a sustainable and resilient society with a clean and low carbon development route.Furthermore,the proposed power interconnection scheme will generate valuable economic,social,environmental,and resource allocation benefits.

Some Views about Recent Electric Power Supply Shortage in Shenzhen

Since the beginning of the year 2000, the power demands in Guangdong, Zhejiang provinces and Beijing Tianjin-Tangshan district have been increasing dramatically, power supply shortages have appeared again. This paper analyzes the reasons for the current power supply shortages in Shenzhen district and the problems existing presently in Shenzhen power system. It indicates that, to strengthen power demand forecast, to speed up power construction steps and with ’to develop power ahead of the rest’ as a fundamental target, are the precondition to the long term, steady development of power industry.

支撑新能源电力系统灵活性需求的用户侧资源应用与关键技术

伴随着传统电力系统向以新能源为主体的新型电力系统转型升级,高比例新能源的接入和传统机组占比下降导致电力系统灵活性产生缺额。电动汽车、数据中心、P2X(power-to-X)等需求侧资源可以在多时间尺度为电力系统提供灵活性,是新型电力系统灵活性的重要组成部分。该文首先描述高比例新能源背景下输电网和配电网在不同时间尺度的灵活性需求,然后对比总结了典型需求侧资源的调节特性与应用实践,研究了需求侧资源在支撑高比例新能源输电网和配电网中运行、规划2个层面多时间尺度灵活性需求的应用场景。最后针对未来需求侧资源的研究重点,从聚合技术、电碳协同优化调控策略、可信调节能力量化和通信与信息交换标准等角度,对支撑新型电力系统需求侧资源应用的关键技术进行了总结与展望。

Rethinking the Power Shortage of China in 2011

As the opening year of the ＂Twelfth Five-Year Plan,＂ driven by the steady and fast economic growth, the year of 2011 saw China＇s rising demand for electricity, resulting in regional power shortages. Sub）ected to multiple factors such as the weather conditions, the contradictions between coal supply and power generation and the structural problems in the power system, power supply shortage across the nation became increasingly critical At the same time, the Northeast and Northwest China, plus Inner Mongolia, often experienced power generation surplus and difficulties in sending power to other regions. This paper reviews the overall situation of the national electric power supply in 2011, elaborates on the current contradictions in the power demand and supply and presents an in-depth analysis of causes and corresponding countermeasures.

Market Analyses on Both Ends of "Power from West to East" from Northwest Region (Excerption)

This paper analyzes the power markets both in northwest sending end and, east receiving ends, points out the favorable and unfavorable conditions for power development In, the northwest area, brings forward,the development planning of power sources and power network constructions, and presents the benefit estimation of sending power from northwest to east.

Green-Aware Token Based Demand Scheduling for Electricity Markets

Increasing consumption, changing nature of loads and the need to reduce carbon emission are some of the factors threatening electricity grid stability and reliability. Demand side management programs mainly work by shifting consumption from peak to off-peak period, which inconveniences some consumers and possibly creates a new peak (Reverse Peak) in off-peak hours. Growing use of Photovoltaic solar power in residences provides an opportunity to manage grid reliability and stability in a more flexible manner, and mitigates reverse peaks. We propose a community based scheduling algorithm that guarantees access to shared power capacity and integrates residences’ solar power into the grid. Results indicate peak demand can be reduced by up to 32.1%, while energy costs can be reduced by up to 14.0%. Furthermore, coordinated discharging can mitigate reverse peaks by up to 23.4%. Encouraging and integrating green energy generation and storage in the consumer side is crucial to grid stability and reliability.

电动汽车接入主动配电网协同储能研究应用综述

电动汽车的快速发展和普及已经呈现规模化效应,随着配电网中清洁能源逐渐呈现高比例趋势,规模化电动汽车接入主动配电网作为储能配置参与协同调度成为研究热点。然而在实际应用中,电动汽车参与储能的形式面临诸多不确定性与挑战。为此,分析了协同储能调度的目的及影响因素,从计及需求响应、考虑供需双方、结合多方利益、参与虚拟电厂储能四个方面综述协同储能调度的研究现状,结合国内外应用案例分析探讨其未来发展方向。

基于场景线性化重塑的用户侧储能容量高效规划方法

推进用户侧分布式光储一体化发展是提高新型电力系统新能源消纳能力的重要举措。然而,储能高昂的投资成本阻碍了用户侧光储系统的推广进程,亟需合理的储能容量优化配置方案为用户提供更加理性的决策依据,以提升系统经济性和环境友好性。现有容量规划方法往往基于典型场景进行储能运行模拟,未考虑全年每个典型场景之间的功率波动特征以及某些极端场景对于容量配置结果的影响,难以保证规划结果的准确性。为此,文中提出了一种基于场景线性化重塑的用户侧储能容量高效规划方法。首先,以聚类结果中的典型场景为基,通过最小二乘法近似地线性表示全年中的极端场景;其次,将场景线性化结果嵌入储能全年运行约束中,并通过重新构造决策变量来减小优化问题的规模;最后,通过实际算例分析了用户侧配置储能的经济效益,并将所提出的规划方法与已有方法进行仿真结果对比。结果表明,所提出的规划方法能够减小精确模型运行所需的决策变量规模,在提升计算效率的同时取得比已有近似方法更准确的规划结果。

Design Optimization and Operating Performance of S-CO_(2) Brayton Cycle under Fluctuating Ambient Temperature and Diverse Power Demand Scenarios

The supercritical CO_(2)(S-CO_(2)) Brayton cycle is expected to replace steam cycle in the application of solar power tower system due to the attractive potential to improve efficiency and reduce costs.Since the concentrated solar power plant with thermal energy storage is usually located in drought area and used to provide a dispatchable power output,the S-CO_(2) Brayton cycle has to operate under fluctuating ambient temperature and diverse power demand scenarios.In addition,the cycle design condition will directly affect the off-design performance.In this work,the combined effects of design condition,and distributions of ambient temperature and power demand on the cycle operating performance are analyzed,and the off-design performance maps are proposed for the first time.A cycle design method with feedback mechanism of operating performance under varied ambient temperature and power demand is introduced innovatively.Results show that the low design value of compressor inlet temperature is not conductive to efficient operation under low loads and sufficient output under high ambient temperatures.The average yearly efficiency is most affected by the average power demand,while the load cover factor is significantly influenced by the average ambient temperature.With multi-objective optimization,the optimal solution of designed compressor inlet temperature is close to the minimum value of35℃ in Delingha with low ambient temperature,while reaches 44.15℃ in Daggett under the scenario of high ambient temperature,low average power demand,long duration and large value of peak load during the peak temperature period.If the cycle designed with compressor inlet temperature of 35℃ instead of 44.15℃ in Daggett under light industry power demand,the reduction of load cover factor will reach 0.027,but the average yearly efficiency can barely be improved.

A strategy for strengthening chaotic mixing of dual shaft eccentric mixers by changing non-Newtonian fluids kinetic energy distribution

Efficiently modulating the velocity distribution and flow pattern of non-Newtonian fluids is a critical challenge in the context of dual shaft eccentric mixers for process intensification,posing a significant barrier for the existing technologies.Accordingly,this work reports a convenient strategy that changes the kinetic energy to controllably regulate the flow patterns from radial flow to axial flow.Results showed that the desired velocity distribution and flow patterns could be effectively obtained by varying the number and structure of baffles to change kinetic energy,and a more uniform velocity distribution,which could not be reached normally in standard baffle dual shaft mixers,was easily obtained.Furthermore,a comparative analysis of velocity and shear rate distributions is employed to elucidate the mechanism behind the generation of flow patterns in various dual-shaft eccentric mixers.Importantly,there is little difference in the power number of the laminar flow at the same Reynolds number,meaning that the baffle type has no effect on the power consumption,while the power number of both unbaffle and U-shaped baffle mixing systems decreases compared with the standard baffle mixing system in the transition flow.Finally,at the same rotational condition,the dimensionless mixing time of the U-shaped baffle mixing system is 15.3%and 7.9%shorter than that of the standard baffle and the unbaffle mixing system,respectively,which shows the advantage of the U-shaped baffle in stirring rate.

基于改进的差分进化算法求解SWMP问题

需求侧响应可以为电网带来可观的收益,计及需求响应的电力系统经济调度优化方法研究成为国内外学者的关注的课题。提出了一种可以用于解决计及需求侧响应的电力系统经济调度问题的基于随机黑洞模型的差分进化算法(sequence-based differential evolution hole,S-DEH),该算法基于原始的差分进化算法结合随机黑洞模型,对初始序列敏感性高,稳定可靠,计算量小,能够针对不同的问题选择最佳的控制参数,能够减少人为的操作失误和调整优化算法参数所需要的时间,具有很高的求解效率。同时所采用的演算模型为计及需求侧响应的求解电力系统的单时段的社会效益最大化问题(social welfare maximization problem,SWMP),以验证算法的性能,并通过求解多时段的SWMP优化调度问题验证了算法在处理高维度复杂优化问题时仍能保持高效的性能。

基于电力需求侧响应的主动配电网分布式发电单元优化调度

为了平衡主动配电网中可再生能源与负荷间的出力差值,降低预算成本和用户购电费用,研究提出基于电力需求侧响应的主动配电网分布式发电单元优化调度方法。以电力需求侧响应为前提,设定分布式发电单元优化调度优先级,结合以主动配电网发电成本费用总值最低为目标而建立的目标函数,设置主动配电网调度周期内所有时间段的节点电压、潮流方程、储能系统荷电状态以及柔性负荷的功率极限约束条件,并以此为基础构建主动配电网分布式发电单元优化调度模型。最后,再利用改进后的粒子群算法对模型进行求解,从而得到最终的优化调度结果。实验结果表明,所提方法可以有效平衡可再生能源与负荷之间的发电出力差值,既提升了主动配电网对可再生能源的消纳能力,也降低了发电预算开支和用户购电成本。

煤电高增速背后电力供求分析研究

近年来国内煤电增速同比加快,2023年以不到40%的装机容量,实现了近60%的发电量。阐述了煤电的作用、地位及其相关政策变化;从制造业电力消费增长、社会电力消费量提高、长期电力需求空间大,以及短期内新能源无法满足电力需求、煤电可缓解高负荷压力、电力系统调节能力仍待完善、煤电用能成本相对较低等电力需求侧和供给侧两方面,深入分析了煤电高增速背后的主要原因。研究认为,未来国内能源需求随产业升级和人均能耗提高仍将大幅增加,煤电的电力主体作用短期内不会动摇;同时,认为目前增补煤电势在必行。提出煤电应加快向“调节器”作用转型、继续推动燃煤清洁发电、加快与新能源耦合发展等具体建议。

电网需求侧资源动态分布式k-means聚类算法

为有效聚合电网需求侧资源,合理、高效利用电网资源,提出基于分布式k-means的电网需求侧资源动态聚类算法。通过基于置信半径的分布式k-means算法聚类采集到的电网需求侧资源数据,在模糊C均值进化神经网络中,以聚类得到的电网需求侧资源数据为输入向量,输出电网需求侧资源场景,依据场景存在概率,以电网侧资源日均峰谷差最小、DG消纳程度最高与日均负荷波动率最小为目标函数,以电网需求侧资源曲线波动率与负荷互补为约束条件,构建电网需求侧资源多场景聚类模型,经动态改变惯性因子(DCW)粒子群算法求解模型后,实现电网需求侧资源多场景聚类。试验结果表明:该方法可实现电网需求侧资源动态聚类,应用该方法聚类不同场景电网需求侧资源时的日负荷率较低,聚类效果较好,可满足实际电力需求侧资源动态聚类工作的需要。