A study of robust generation mix under uncertain environments

In recent years, the trend has been toward factors (e.g., demand for load, energy cost) becoming more and more uncertain in power system expansion planning. Thus, it has become necessary to take this uncertainty into account in determining generation plans. In this paper, a robust generation plan is defined explicitly as a plan that ensures fixed performance (economy) despite deviations in these factors. In addition, a new formulation of the robust generation mix problem, whose purpose is to determine the most robust combination of plants in a target year, is proposed. It is generally difficult to solve the formulated problem with parameters. However, by analyzing a proposed formulation from the viewpoint of optimization, we show that the proposed formulation is transformed into the conventional optimization problem without parameters. The simulation results on a typical model show that the generation mix produced by the proposed formulation is more robust than that produced by the conventional formulation. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(1): 26–35, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.2009     

基于不确定条件下的北京电源规划优化模型

电源规划是电力系统中非常重要的规划,直接影响系统今后运行的可靠性、经济性、电能质量、网络结构及其将来的发展.以北京地区为例,建立了一个不确定性电源规划优化模型.本模型引入区间混合整数线性规划方法,可以有效地解决电源规划模型中存在的不确定性问题和发电机组的装机扩建问题.结果表明:北京市将初步建立起以煤、气发电为主,新能源和可再生能源发电等为补充的多元化电源结构,为首都经济社会发展和人民生活水平的提高提供安全可靠、稳定充足的电力供应.     

The right mix of drivers and power generation

This work presents an analytical methodology for selecting the most economical mix of drivers for large mechanical load and power generation for offshore production in the Gulf of Mexico. These method accounts for CAPEX, life-cycle costs and the effect of emissions and production availability in the selection of drivers and associated equipment. Result of driver studies have shown that all electric designs are viable on floating platforms in the Gulf of Mexico.     

Flexible mix and match approach for network fixed cost allocation

Different transmission fixed cost allocation methods lead to different nodal charges. Development of new transmission pricing scheme is guided by generic principles of transmission pricing. Each method available in the literature and used in practice, conforms to a certain set of principles, if not all. A transmission pricing mechanism for a system is chosen so that it tries to satisfy most of the country and system specific requirements. The ever conflicting requirements do not allow choice of a single method that satisfies all principles. This paper proposes a new transmission pricing paradigm based on flexible mix and match approach. Aim here is to create a generic flexible toolbox that considers viewpoints and preferences of all stake-holders in terms of principles of transmission pricing, rather than devising a new transmission fixed cost allocation methodology. Thus, the final constitution of nodal transmission charges embeds relative weights given to each principle by each stakeholder. Analytical Hierarchical Process (AHP) is used as a tool for the said approach. The results have been obtained on IEEE 30 bus system to demonstrate the suitability of the scheme.     

Applying portfolio theory-based modified ABC to electricity generation mix

Portfolio theory has found its model in numerous engineering applications for optimizing the electrical generation mix of an electricity area. However, to have better performance of this theory, this paper presents a new heuristic method as known modified artificial bee colony (MABC) to portfolio optimization problem. Moreover, we consider both dis-patchable and non-dis-patchable constrains variables and energy sources. Note that the proposed MABC method uses a Chaotic Local Search (CLS) to enhance the self searching ability of the original ABC algorithm. Resulting, in this paper a portfolio theory-based MABC model that explicitly distinguishes between electricity generation (energy), installed capacity (power) and actual instantaneous power delivery is proposed. Therefore, in this model, the uncertainties of wind power and ramp-up/down constrains of traditional power plants are correctly considered in the investment cost. The numerical results show the great potential of proposed model with lowest risk on generation cost. Also, they are show that MABC approach is successful in portfolio optimization.     

Must-run generation: can we mix regulation and competition successfully?

In restructuring, certain generators will continue to be required to operate during critical times to assure local reliability. Regulation must allow these generators to participate in the competitive market, while assuming their availability to operate when needed and addressing concerns about their market power     

考虑发电和负荷不确定因素的输电网灵活规划

电力市场改革给输电网规划带来了新的挑战,传统的只考虑一种未来场景的输电网规划方法不能满足实际要求.对市场环境下的不确定性因素进行建模并反映到输电网规划模型中,按照线路概率性的N-1准则建立输电网灵活规划模型,采用基于蒙特卡罗仿真和遗传算法的求解方法,最终得到未来不确定性环境下投资风险最小的输电网规划方案,仿真验证了该模型的合理性和求解方法的有效性.     

考虑发电和负荷不确定因素的输电网灵活规划

电力市场改革给输电网规划带来了新的挑战,传统的只考虑一种未来场景的输电网规划方法不能满足实际要求。对市场环境下的不确定性因素进行建模并反映到输电网规划模型中,按照线路概率性的N-1准则建立输电网灵活规划模型,采用基于蒙特卡罗仿真和遗传算法的求解方法,最终得到未来不确定性环境下投资风险最小的输电网规划方案,仿真验证了该模型的合理性和求解方法的有效性。     

计及分布式电源和负荷不确定性的多目标配网重构

构建多目标配网重构模型,该模型充分考虑了风电出力、光伏发电以及负荷的不确定性,并且同时优化配网的3个重要评估指标:有功损耗、节点最小电压值、负荷均衡度。采用场景分析法处理不确定性因素,采用同步回代缩减法进行场景削减,讨论不同场景数对优化结果的影响,并利用多目标扰动生物地理学算法求解模型,利用模糊集理论确定最终重构方案。某69节点配网系统测试结果表明:所用算法能够快速找到多目标配网重构模型的决策解,具有较高的搜索效率,验证了在消纳分布式电源的情况下,通过网络重构能够明显改善网络的各项指标。     

Optimal generation dispatch with renewable energy embedded using multiple objectives

Traditional economic dispatch focuses mainly on minimizing the total operation cost of the power system. With the appearance of energy crisis and environmental pollution becoming a public issue, environmental effect of generator should be taken into consideration through the dispatch process. In this paper a multi-objective dispatch problem considering the integration of wind power is solved whose objectives include the generation cost, the reserve capacity and the environmental emission. To compromise different objectives, a coordination degree combined with a satisfaction degree are introduced in order to transform the multi-objective dispatch problem into a single-objective one, i.e., the optimal generation dispatch (OGD) model. Then the OGD is solved by a particle swarm optimization algorithm on an IEEE 30-bus system, with wind power generation and coal-fired generation embedded. The simulation results show that better results in terms of all the three objectives can be obtained from the OGD model, in comparison with two other multi-objective dispatch models. The simulation results also show that the integration of wind power will cause the increase of both the generation cost and the reserve capacity but will decrease the environmental emission.     

灵活的5G波形及超宽带信号生成和分析测试系统

目前5G技术研究遇到的一大挑战是：需要对太多的波形、频率和带宽加以分析。除了6 GHz以下频率的波形之外,还包括微波和毫米波频率的波形。有的波形可能还涉及到大带宽。所有这些因素对5G信号的生成和分析提出了新的测试挑战,因此灵活性是当今5G研究的关键要求。本文将讨论部分候选波形,并介绍一款创新和灵活的、适用于5G波形生成和分析的测试台。该测试系统将软件解决方案和测试设备完美结合起来,通过仿真前沿的5G波形应用场景来执行“假设－分析”研究。文中还将分析候选5G波形与4G波形共存的场景,并将讨论微波和毫米波频段、调制带宽高达2 GHz的宽带信号生成和分析案例。     

An evaluation of the optimal generation mix for controlling carbon dioxide emissions

This paper presents an efficient computational algorithm for selecting the optimal generation mix considering CO₂ emissions. To demonstrate the effectiveness and feasibility of the proposed method, a fundamental study of the evaluation of the optimal generation mix for controlling CO₂ emissions is indicated. Furthermore, by using a parametric analysis which considers load characteristics as parameters, a general trend for the optimal generation mix which is affected by controlling CO₂ can be derived. The proposed method is based on an optimization method known as simulated annealing. In the method, solutions in a generation mix problem are equivalent to state of a physical system, and the cost of a solution is equivalent to the energy of a state. The proposed method can easily accommodate not only CO₂ emissions but also many practical constraints of generation expansion planning, such as integer solutions of unit capacities, condition of existing units, and so on. Case studies with various annual load patterns (combinations of annual load factors and the shapes of annual load duration curve) are presented and discussed. Consequently, a general trend for selecting generation technologies that should be added to a power system is derived, i.e., a useful guideline for studying generation expansion planning under controlling CO₂ emissions can be provided.     

基于信息物理系统的灵活智能发电控制技术

智能发电技术中系统各组成元素的自主性和基于自学习机制的智能化程度的提高,对其架构的灵活性提出了更高的要求。信息物理系统(CPS)是一种对物理过程进行控制的新的理念与体系结构,其高度的灵活性和智能性使其非常适合智能发电技术的应用。本文介绍了CPS的基本概念和特征;论述了基于CPS的灵活智能发电的基本特点;给出了基于CPS的智能发电控制的体系结构;有针对性地给出了现阶段智能发电体系元素向基于CPS的灵活智能发电体系的映射关系。CPS体系使智能发电控制技术逐渐趋于向基于系统组成元素高度智能的"自主化"、SDE/SDS等高度灵活的方向发展,为灵活发电的实现提供了一条新的途径。     

基于并联运行方式下的多变压器经济运行分析

通过分析电力变压器负荷与损耗的关系,从变压器并联运行的角度阐述变压器经济运行方式,从而找到变压器实际运行中的最佳经济运行方式。     

含多种分布式电源的微网经济运行优化研究

微网能够有效地利用各种分布式电源,在解决能源短缺、环境保护和改善电能质量等方面表现出极大潜能。建立热电联产型微网系统经济调度模型,以一个包含风、光、储、微型燃气轮机、燃料电池、柴油发电机以及热电负荷的微网为例,总结了孤网运行方式下的调度策略,并运用改进遗传算法优化了各微源的出力,验证了所提模型、策略和算法的有效性。     

不确定性的电厂动力配煤优化模型

动力配煤是适合中国国情的一种洁净煤技术,可以降低燃煤电厂二氧化硫的排放,改善电厂的经济效益和燃烧性能。然而煤质参数是不确定的和可变的,电厂优化配煤决策必须处理这些不确定性。因此,建立了一个不确定性电厂优化配煤线性模型,处理以区间参数表征的不确定性。结果表明,可得到稳定和可行的区间解,决策者可根据实际情况,在解区间内调整决策变量值,从而得到多个决策替代方案。     

不确定因素耦合下输电网风险规划研究综述

传统的确定性风险分析方法由于存在多种弊端,难以适应新形势下的输电网规划和方案评估,为了更加合理地管控输电网风险水平,基于概率性分析方法对输电网风险规划和评估等研究成果进行了综述。介绍了输电网中的安全、设备、结构、管理和市场等一系列风险因素及相应建模方法;从场景规划、随机规划、模糊规划和区间规划等方面,评述了考虑多种不确定因素的输电网风险规划方法;基于评估指标和方法,综述了近年来国内外考虑多种不确定因素的系统风险评估体系研究成果。在此基础上,结合高比例可再生能源、交直流混联、网源协调、需求响应和建模优化等研究热点,展望了未来考虑多种不确定因素的输电网风险规划领域中需要关注的问题。     

Integrated distribution network expansion planning incorporating distributed generation considering uncertainties,reliability, and operational conditions

In this paper, an integrated methodology is proposed for distribution network expansion planning which considers most of the planning alternatives. The planning aims to determine the optimal reinforcement of existing medium voltage lines and high voltage/medium voltage substations, or installation of new ones to meet the load growth in the planning horizon subject to the technical and operational constraints. Also, to take the advantages of new technologies, the renewable and non-renewable distributed generations have been included in the problem as another alternative. The uncertainties related to renewable DGs, load demand, and energy price have been considered in the calculation of cost components. The load duration curve has been utilized for loads such that the results be more precise. The possibility of islanding and load transferring through the reserve feeders have been regarded in the problem to improve the reliability of the network. Also, the required condition for successful and safe operation of island considering all of uncertainty states have been checked out to accurately calculate the reliability. The genetic algorithm is employed to solve this integrated problem. Finally, the proposed method is applied to the 54-bus system and also a real large-scale distribution network, and the results are discussed. The results verify the effectiveness of the presented method.