Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method

In this paper, wind power generators are being incorporated in the multiobjective economic emission dispatch problem which minimizes wind-thermal electrical energy cost and emissions produced by fossil-fueled power plants, simultaneously. Large integration of wind energy sources necessitates an efficient model to cope with uncertainty arising from random wind variation. Hence, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power. 2m point estimated method handles the system uncertainties and renders the probability density function of desired variables efficiently. Moreover, a new population-based optimization algorithm called modified teaching-learning algorithm is proposed to determine the set of non-dominated optimal solutions. During the simulation, the set of non-dominated solutions are kept in an external memory (repository). Also, a fuzzy-based clustering technique is implemented to control the size of the repository. In order to select the best compromise solution from the repository, a niching mechanism is utilized such that the population will move toward a smaller search space in the Pareto-optimal front. In order to show the efficiency and feasibility of the proposed framework, three different test systems are represented as case studies.     

The economics of wind power with energy storage

We develop a nonlinear mathematical optimization program for investigating the economic and environmental implications of wind penetration in electrical grids and evaluating how hydropower storage could be used to offset wind power intermittence. When wind power is added to an electrical grid consisting of thermal and hydropower plants, it increases system variability and results in a need for additional peak-load, gas-fired generators. Our empirical application using load data for Alberta's electrical grid shows that costs of wind-generated electricity vary from $37 per MWh to $68/MWh, and depend primarily on the wind profiles of installed turbines. Costs of reducing CO₂ emissions are estimated to be $41–$56 per t CO₂. When pumped hydro storage is introduced in the system or the capacity of the water reservoirs is enhanced, the hydropower facility could provide most of the peak load requirements obviating the need to build large peak-load gas generators.     

Impact assessment of using wind power

This paper discusses a methodology to accurately determine the impact of using wind-energy-conversion systems, WECS, on the operation of the central power system. To do so, the power-generation-simulation code PROMIX is used to simulate the operation of the power system on an hourly basis and on a power-plant level, including the technological restrictions of every plant. The actual impact assessment of the WECS is done by comparing the output of two scenarios; a base case and an alternative scenario which includes the WECS.To demonstrate the method, several case studies for WECS in different locations in Belgium are worked out. The impact is quantified by looking at the greenhouse-gas-emission reductions that can be obtained by using WECS. In these case studies, we closely look at the influence of the variability of the WECS power output, the geographical spread of the wind farms, the capacity factor and the capacity credit of the WECS and the effect of the power-generation mix.     

Simulation analysis of emissions trading impact on a non-utility power plant

Non-utility power plants can competitively participate in open electricity market to reduce operational costs but in the absence of pollution charges or emissions trading such generators are tempted to cause greater pollution for profit maximization. This paper presents a solution that incorporates pollution charges for nitrogen oxides and sulphur dioxide emissions in line with existing national environmental quality standards and a new carbon dioxide emissions trading mechanism. A novel approach has been used for allocation of allowable emissions that favors efficiently fuelled and environmentally friendly operation for maximizing profit. Impact of proposed carbon trading on economical utilization of enormous indigenous coal reserves has been analyzed and determined to be acceptable. Software developed in this paper, harnessing Sequential Quadratic Programming capabilities of Matlab, is shown to be adequate simulation tool for various emissions trading schemes and an useful operational decision making tool for constrained non-linear optimization problem of a non-utility power plant.     

Online and batch methods for solar radiation forecast under asymmetric cost functions

In electric power grids, generation must equal load at all times. Since wind and solar power are intermittent, system operators must predict renewable generation and allocate operating reserves to mitigate imbalances. If they overestimate the renewable generation during scheduling, insufficient generation will be available during operation, which can be very costly. However, if they underestimate the renewable generation, usually they will only face the cost of keeping some generation capacity online and idle. Therefore overestimation of renewable generation resources usually presents a more serious problem than underestimation. Many researchers train their solar radiation forecast algorithms using symmetric criteria like RMSE or MAE, and then a bias is applied to the forecast later to reflect the asymmetric cost faced by the system operator – a technique we call indirectly biased forecasting. We investigate solar radiation forecasts using asymmetric cost functions (convex piecewise linear (CPWL) and LinEx) and optimize directly in the forecast training stage. We use linear programming and a gradient descent algorithm to find a directly biased solution and compare it with the best indirectly biased solution. We also modify the LMS algorithm according to the cost functions to create an online forecast method. Simulation results show substantial cost savings using these methods.     

An analysis of the potential of Wind Energy Conversion Systems

Wind Energy Conversion Systems (WECS) are solar systems because the sun drives the atmospheric circulation. About 20 TW of wind energy flows poleward annually, over land in temperate latitudes, in the 500 m deep atmospheric boundary layer. An average 500 GW of electricity could be generated by massive exploitation of the U.S. Great Plains wind field.There are, however, large fluctuations in available wind power. There are frequent 20% variations in annual supply; annual periodicity brings most wind power during the spring; there are storm cycles; and there is a diurnal cycle. Gusts and turbulence also require filtering to meet normal power requirements. Several schemes are evolving to tame this erratic wind power supply.Modern technology is refining horizontal-axis turbines of a wide size range. Progress is also being made toward producing an economical vertical-axis turbine. Standards for turbine performance evaluation and installation site selection are now being developed. Yet it will be a few years before proven systems can significantly affect national energy supplies.Eventually, mass-produced WECS may cost $1000 per installed, rated kW, but the wind does not often flow at turbine-rated speed. With some storage or filtering, problems with wind variability may be overcome. Then WECS electricity production may be as economical as other electric generators. No serious hazards or environmental impacts should slow WECS development.     

Reactive power compensation and active filtering capability of WECS with DFIG without any over‐rating

This paper presents a novel approach for reactive power compensation and active filtering capability of a variable speed wind energy conversion system (WECS) with doubly fed induction generator (DFIG), without any over‐rating. First, the WECS is capable of capturing maximum wind power under fluctuating wind speed. Second, depending on the available wind power value versus nominal WECS power, power quality can be improved by compensating the reactive power and the grid harmonic currents, without any system over‐rating. The proposed rotor side converter (RSC) control manages the WECS function's priorities, between main active power generation and power quality management. To ensure high filtering performances, we used an improved harmonic isolator in the time domain, based on a selective pass band filter (SPBF) developed in our laboratory. Moreover, we took advantage of the high amplification effect of the rotor side‐controlled DFIG to compensate harmonic currents. Consequently, no over‐rating is necessary for the proposed additional active filtering capability. Simulation results for a 2 MW WECS with DFIG confirm the effectiveness and the performances of the proposed approach. Copyright © 2009 John Wiley & Sons, Ltd.     

Market constrained optimal planning for wind energy conversionsystems over multiple installation sites

This paper presents two market dependent optimization algorithms that can be used to plan wind energy conversion system (WECS) installations simultaneously over several sites of interest to a utility, within the scope of (1) available WECS models, (2) power demand of the utility, and (3) wind characteristics at each site; both (2) and (3) being variable with time and subject to seasonal changes. A suitable case study illustrates application of the planning algorithms to a scenario comprising of eight installation sites, using a representative market database consisting of 37 available models of WECS     

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.     

A review on distributed generation impacts on electric power system

In 2021, the world's total installed capacity of generation units based on renewable energy sources (not including hydropower) amounted to about 1674 GW: over 825 GW and 849 GW of wind and solar power plants were installed respectively. The growing of the installed capacity of these distributed generators is a response to the increasing the power consumption, global environmental issues and has also become possible due to the development of technology in field of power semiconductor devices. However, on the way of large-scale implementation of distributed generators based on renewable energy sources, traditional electric power system meets new challenges to ensure the reliability and sustainability of new electric power systems with renewable energy sources. In particular, distributed generators change processes in the electric power system, impact to the parameters and power balance, change the magnitude and direction of power flow and short-circuit current, which determines the need to update the settings of the relay protection and automation systems of traditional electric power system and to coordinate their operation with automatic control systems of installed distributed generators. The above-mentioned tasks form a number of scientific research directions, one of which is a task of determining optimal size and location of distributed generators. The main purpose of this optimization task is to reduce power losses, operating and total electricity cost, improve the voltage profile, etc. In addition, the correct and reasonable placement of distributed generators defines an effective planning of the operating modes of electric power system and power plants (especially based on renewable energy sources, the operating modes of which depend on weather conditions and can be sharply variable).The paper highlighted the impacts of distributed generators on power losses, the voltage level, maintaining the power balance and the possibility of participating in the frequency regulation, and short-circuit current in power system. The optimization criteria, the main limiting conditions, as well as methods for solving this optimization problem are considered. This review will help the System operators and investing companies, especially in Russia, to form the main aim, objective function and constraints that will aid to meet their load demand at minimum cost and to choose from the options available for optimization of location and capacity of distributed generators.     

GHG emissions and energy performance of offshore wind power

This paper presents specific life cycle GHG emissions from wind power generation from six different 5 MW offshore wind turbine conceptual designs. In addition, the energy performance, expressed by the energy indicators Energy Payback Ratio (EPR) Energy Payback Time (EPT), is calculated for each of the concepts.There are currently few LCA studies in existence which analyse offshore wind turbines with rated power as great as 5 MW. The results, therefore, give valuable additional environmental information concerning large offshore wind power. The resulting GHG emissions vary between 18 and 31.4 g CO₂-equivalents per kWh while the energy performance, assessed as EPR and EPT, varies between 7.5 and 12.9, and 1.6 and 2.7 years, respectively. The relatively large ranges in GHG emissions and energy performance are chiefly the result of the differing steel masses required for the analysed platforms. One major conclusion from this study is that specific platform/foundation steel masses are important for the overall GHG emissions relating to offshore wind power. Other parameters of importance when comparing the environmental performance of offshore wind concepts are the lifetime of the turbines, wind conditions, distance to shore, and installation and decommissioning activities.Even though the GHG emissions from wind power vary to a relatively large degree, wind power can fully compete with other low GHG emission electricity technologies, such as nuclear, photovoltaic and hydro power.     

含风电场的电力系统经济——排放多目标调度

从火电机组燃料成本和污染物排放两方面入手,构建了含风电场的电力系统发电调度运营管理多目标优化模型。引入了一种新的概率分布模型——截断多用途分布模型(TVD)来表征风电场,并简化风电的不确定性,同时引入基于TVD的可调节置信区间(ACI)风电场成本函数模型及一种基于列维飞行及解决非凸问题的改进型闪电算法(ILFA),可在随机多目标框架中有效地解决经济—排放调度(EED)问题。最后,通过算例与其他经典分布模型进行对比分析,结果表明所提模型可更准确地反映风电情况,该算法在平衡经济成本和污染物排放方面有效。     

含高渗透率海上风电电网的DSSC优化配置与运行控制策略

随着海上风电并网规模的不断增大,高渗透率风电引起的线路潮流阻塞问题已成为制约风电并网规模的重要因素之一。针对高渗透率海上风电区域的输电线路阻塞问题,文章提出一种含高渗透率海上风电电网的分布式静态串联补偿器(DSSC)优化配置与运行控制策略。该策略包含两个阶段:第一阶段为考虑多场景下DSSC的优化配置,以线路阻塞程度最小为目标,确定DSSC的配置地点与容量;第二阶段为DSSC的运行控制,利用DSSC的潮流控制能力,优化调度系统中的发电机,降低系统运行成本,并考虑系统在出现风电水电高出力场景下DSSC的运行控制,从而提高系统可再生能源的消纳。仿真结果表明,与采用静态串联补偿器(SSSC)和不采用柔性交流输电(FACTS)设备相比较,所提策略可降低系统的运行成本,提高可再生能源的消纳水平。     

基于改进径向移动算法的含风电场电力系统优化调度

为应对风电接入对电力系统稳定运行带来的影响,考虑风电高估低估成本、阀点效应、旋转备用约束和网络损耗等常需因素,建立计及风电不确定性的通用经济调度模型。为求解此模型,提出一种改进的径向移动算法(IRMO),该算法针对基本径向移动算法易陷入局部最优解的不足,一方面结合遗传算法中种群变异的思想,在迭代过程中随机对一部分粒子进行突变,改善种群多样性,使算法能够跳出局部最优;另一方面引入凹抛物线式的惯性权值非线性递减策略,以进一步增强算法中后期的搜索精度,更易找到全局最优解。最后对含风电场的电力系统进行算例分析和算法对比,验证模型的合理性以及IRMO的优越性。     

Fuzzy logic control based maximum power tracking of a wind energy system

In this paper a utility interactive wind energy conversion system (WECS) with an asynchronous (AC–DC–AC) link is described. The control system has the objective of identifying and extracting the maximum power from the wind energy system and transferring this power to utility. A fuzzy logic control (FLC) technique has been implemented to design the tracking controller of the WECS. A wind speed step model was used in the design phase. The performance of the WECS with the proposed fuzzy logic controller is tested using real meteorological data. Its robustness and effectiveness are demonstrated by the simulation results of the controlled system.     

Optimal coordination of wind-hydro-thermal based on water complementing wind

The increasing integration of wind power into the existing power system demands for effective strategies to deal with wind intermittency and uncertainty. Relying solely on thermal power to cover wind uncertainty will sacrifice the operating efficiency and economy of thermal generators. In view of this, the adjustable hydropower is preferred for complementing wind fluctuation and uncertainty and the coordinated dispatch problem of wind-hydro-thermal power is established. Based on a newly designed water supplementing wind strategy, the original complex problem is decomposed into wind-hydro subproblem and thermal subproblem. A novel stochastic constraint related to wind power uncertainty is proposed and handled according to stochastic programming theory. By introducing the concept of expected breed rate and elitist preservation strategy, the particle swarm optimization (PSO) algorithm is improved and combined with the exterior penalty function method for solving the complete optimization problem. Optimal generation scheduling schemes that can make full use of wind energy and ensure efficient and economic operating of thermal generators are obtained by the proposed approach. Meanwhile the coordinating operation of wind, hydro and thermal power under different water resources and wind penetrations respectively are revealed and discussed.     

Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties

Increasing penetration of wind power in power systems causes difficulties in system planning due to the uncertainty and non dispatchability of the wind power. The important issue, in addition to uncertain nature of the wind speed, is that the wind speeds in neighbor locations are not independent and are in contrast, highly correlated. For accurate planning, it is necessary to consider this correlation in optimization planning of the power system. With respect to this point, this paper presents a probabilistic multi-objective optimal power flow (MO-OPF) considering the correlation in wind speed and the load. This paper utilizes a point estimate method (PEM) which uses Nataf transformation. In reality, the joint probability density function (PDF) of wind speed related to different places is not available but marginal PDF and the correlation matrix is available in most cases, which satisfy the service condition of Nataf transformation. In this paper biogeography based optimization (BBO) algorithm, which is a powerful optimization algorithm in solving problems including both continuous and discrete variables, is utilized in order to solve probabilistic MO-OPF problem. In order to demonstrate performance of the method, IEEE 30-bus standard test case with integration of two wind farms is examined. Then the obtained results are compared with the Monte Carlo simulation (MCS) results. The comparison indicates high accuracy of the proposed method.     

Performance of residential fuel-cell-combined heat and power systems for various household types in Japan

A residential fuel-cell-combined heat and power (FC-CHP) system is considered a promising low-carbon technology that can reduce residential energy consumption and thus, achieve Japan's greenhouse gas (GHG) emissions reduction targets. However, to consider future directions for the systems' research and development, it is critical to understand the relationships between the performances of FC-CHP systems and residential energy demand profiles, which vary by household characteristic. This study evaluates the effects of applying city gas-fueled FC-CHP systems to Japanese households with different attributes. We compare total costs and GHG emissions for residential energy use between the FC-CHP systems and a conventional system. The economic performance results suggest that the basic PEMFC-CHP systems have an economic advantage only for four-person families with teenage children and further development efforts for low-output FC-CHP systems are required to enable various households save energy costs. The environmental evaluation results show that SOFC-CHP systems can drastically reduce GHG emissions from particularly small-sized households.     

风电与储能联合运行的碳减排效果

在全球能源危机和环境污染的背景下,风电—储能联合运行系统对电力行业的节能减排有重大影响。将风电和储能变量同时引入供给函数均衡模型来模拟风电—储能联合运行系统提供的基荷电量,并在此基础上通过情景分析分别估算了发电企业在风电系统、储能系统及风电—储能联合运行系统3种情景下的污染气体排放量。结果表明,各发电企业在利益最大化目标的驱使下将不断增加储能量,使得联合运行系统比单独的风电或储能系统具有更高的排放量,且排放量的大小受储能容量的影响。     

Wind power myths debunked

The rapid growth of wind power in the United States and worldwide has resulted in increasing media attention to--and public awareness of--windgeneration technology. Several misunderstandings and myths have arisen due to the characteristics of wind generation, particularly because wind-energy generation only occurs when the wind is blowing. Wind power is therefore not dispatchable like conventional energy sources and delivers a variable level of power depending on the wind speed. Wind is primarily an energy resource and not a capacity resource. Its primary value is to offset fuel consumption and the resulting emissions, including carbon. Only a relatively small fraction of wind energy is typically delivered during peak and high-risk time periods; therefore, wind generators have limited capacity value. This leads to concerns about the impacts of wind power on maintaining reliability and the balance between load and generation. This article presents answers to commonly asked questions concerning wind power. It begins by addressing the variability of wind and then discusses whether wind has capacity credit. The article addresses whether wind can stop blowing everywhere at once, the uncertainty of predicting wind generation, whether it is expensive to integrate wind power, the need for new transmission, and whether wind generation requires backup generation or dedicated energy storage. Finally, we discuss whether there is sufficient system flexibility to incorporate wind generation, whether coal is better than wind because coal has greater capacity factors, and whether there is a limit to how much wind power can be incorporated into the grid.