Genetic fuzzy rule extraction for optimised sizing and control of hybrid renewable energy hydrogen systems

A major challenge related to the design of a hybrid renewable energy hydrogen system is which energy sources to include and at what capacity, for regionally different potentials of renewable energy and hydrogen demand. In addition, once the plant is in operation, control variables need to be optimised. The problem resorts to an area of multiple criteria decision making referred to as multi-objective optimisation. The results obtained from these type of algorithms include not only one optimal solution, but a set of optimal solutions (Pareto front) thereby offering a system designer several options. This set of solutions can be hard to interpret and a method is needed to automatically extract useful design and control strategies from this information. A methodology that is quite successful in deriving human interpretable rules from this type of information is genetic fuzzy systems. In this work a k-means clustering algorithm is used to generate membership functions and a fuzzy rule-base is trained by means of a genetic algorithm. The genetic fuzzy system obtained is reduced by determining the minimum number of rules followed by a membership function reduction process. The reduced genetic fuzzy system is deemed more interpretable. Geographic weather data from three different sites are used to generate data to be used in the genetic fuzzy method. Results show that the technique provides valuable information that can be used for the design of such hybrid renewable energy hydrogen production systems.     

A new perspective in optimum sizing of hybrid renewable energy systems: Consideration of component performance degradation issue

The ever increasing demand for energy and the concerns on the environmental sustainability issue all around the world lead to more interest in alternative sources for energy production. However, as the current costs of the alternative sources such as solar, wind energy conversion systems etc. are relatively higher as compared to the conventional means of energy production, an optimum sizing approach is quite necessary in order to avoid over-sizing of such systems without lowering the reliability of load demand supply in all possible conditions including the variability of meteorological conditions or the changing power demand of load. There are many research papers available in the literature dealing with this optimum sizing issue. Even the mentioned papers significantly contribute to the wider penetration of such sources, none of them consider the power output degradation of alternative energy sources due to aging during their pre-defined operating life time. Besides, there are a few studies utilizing detailed dynamic models of energy sources apart from first-degree linear equations based models that may fall short in presenting the exact dynamics of the related system. Thus, an “observe and focus” algorithm based optimization of a hybrid alternative energy system considering the power output degradation and detailed models of each hybrid system component is performed in this study. Related details presented within the paper can provide a new perspective in optimum sizing of such hybrid systems and may further be considered in future updates of famous sizing software programs commercially or freely available in websites of several laboratories or universities.     

A topological reconfiguration procedure for maximising local consumption of renewable energy in (Italian) active distribution networks

Distribution networks (DNs) are facing great changes, due to the strong increase in distributed generation (DG), often driven by renewable energy sources. Designed to deliver electrical power from the transmission system to the final consumers, they are now becoming active and may inject power into the transmission network. In case of large DN, a portion of the system can be absorbing power from the transmission grid, while another portion injects power into it. In order to satisfy the power balance as much as possible at the local level, the distribution system operators are interested in the minimisation of the power exchange with the transmission network, maximising the local consumption of DG energy. This paper presents a topological reconfiguration procedure, based on the branch exchange technique, for the maximisation of the local consumption of renewable energy. A case study is presented, based on a real DN located in northern Italy.     

Reviewing optimisation criteria for energy systems analyses of renewable energy integration

The utilisation of fluctuating renewable energy sources is increasing world-wide; however, so is the concern about how to integrate these resources into the energy systems. The design of optimal energy resource mixes in climate change mitigation actions is a challenge faced in many places. This optimisation may be implemented according to economic objectives or with a focus on techno-operational aims and within these two main groupings, several different criteria may potentially be applied to the design process.In this article, a series of optimisation criteria are reviewed and subsequently applied to an energy system model of Western Denmark in an analysis of how to use heat pumps for the integration of wind power.The analyses demonstrate that the fact whether the system in question is modelled as operated in island mode or not has a large impact on the definition of the optimal wind power level. If energy savings and CO₂ emission reductions beyond the system boundary are not included in the analysis, then it is either not feasible to expand wind power to a high degree or it is conversely more feasible to install relocation technologies that can utilise any excess production. The analyses also demonstrate that different optimisation criteria render different optimal designs.     

风光互补独立供电系统的优化设计

在设计风光互补独立供电系统时,系统中需要优化的不仅有光伏电池和蓄电池的容量,还应该有风力发电机种类和容量以及光伏电池的倾角。优化目标为系统安装成本,约束条件为供电可靠性,其指标负载缺电率LP- SP需经仿真运行得到。本问题属于非线性整数规划,也是一个NP-hard问题。用包含精英策略的遗传算法优化,以自适应罚函数法处理约束。计算和验证表明本文采用的算法收敛,能同时优化风力发电机类型和容量、光伏电池的容量和倾角以及蓄电池的容量,并且计算效率高。     

Optimization and control of autonomous renewable energy systems

Recently, there has been a growing interest in harnessing renewable energy resources particularly for electricity generation. One of the main concerns in the design of an electric power system that utilizes renewable energy sources, is the accurate selection of system components that can economically satisfy the load demand. This depends on the load that ought to be met, the capacity of renewable resources, the available space for wind machines and solar panels, and the capital and running costs of system components. Once size optimization is achieved, the autonomous system must be controlled in order to correcly match load requirements with instantaneous variation of input energy. In this paper, a new formulation for optimizing the design of an autonomous wind-solar-diesel-battery energy system is developed. This formultation employs linear programming techniques to minimize the average production cost of electricity while meeting the load requirements in a reliable manner. The computer program developed reads the necessary input data, formulates the optimization problem by computing the coefficients of the objective function and the constraints and provides the optimum wind, solar, diesel, and battery ratings. In order to study the effect of parameters predefined by the designer on the optimum design, several sensitivity analysis studies are performed, and the effects of the expected energy not served, the load level, the maximum available wind area, the maximum available solar area, and the diesel engines' lifetime are investigated. A controller the monitors the operation of the autonomous system is designed. The operation of this controller is based on three major policies; in the first, batteries operate before diesel engines and hence the storage system acts as a fuel saver, while in the second diesel engines are operated first so that the unmet energy is lower but the fuel cost is high. According to the third policy, the supply is made through diesel engines only. This is done for the purpose of making a performance comparison between the isolated diesel system and the hybrid renewable energy system. The proposed optimization and control techniques are tested on Lebanese data. Although three different control policies have been adopted in this work, the software is able to accommodate other policies.     

Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms

A methodology for optimal sizing of stand-alone PV/WG systems is presented. The purpose of the proposed methodology is to suggest, among a list of commercially available system devices, the optimal number and type of units ensuring that the 20-year round total system cost is minimized subject to the constraint that the load energy requirements are completely covered, resulting in zero load rejection. The 20-year round total system cost is equal to the sum of the respective components capital and maintenance costs. The cost (objective) function minimization is implemented using genetic algorithms, which, compared to conventional optimization methods such as dynamic programming and gradient techniques, have the ability to attain the global optimum with relative computational simplicity. The proposed method has been applied for the design of a power generation system which supplies a residential household. The simulation results verify that hybrid PV/WG systems feature lower system cost compared to the cases where either exclusively WG or exclusively PV sources are used.     

Development of the hard and soft constraints based optimisation model for unit sizing of the hybrid renewable energy system designed for microgrid applications

The hybrid energy systems (HESs) based electricity generation system has become a more attractive solution for rural electrification nowadays. Economically feasible and technically reliable HESs are solidly based on an optimisation stage. This article discusses about the optimal unit sizing model with the objective function to minimise the total cost of the HES. Three typical rural sites from southern part of India have been selected for the application of the developed optimisation methodology. Feasibility studies and sensitivity analysis on the optimal HES are discussed elaborately in this article. A comparison has been carried out with the Hybrid Optimization Model for Electric Renewable optimisation model for three sites. The optimal HES is found with less total net present rate and rate of energy compared with the existing method     

A heuristic approach for optimal sizing of ESS coupled with intermittent renewable sources systems

In this paper a techno-economic comparison of an energy storage system (ESS) sizing for three intermittent renewables, wind, wave and PV power, with regard to two electricity grid services is presented. The first service consists of output hourly smoothing, based on day-ahead power forecasts (S1). The second service supplies year-round guaranteed power (S2). This leads to an annual default time rate (DTR) for which the actual power supplied to the grid does not match the day-ahead power bid within a given tolerance. A heuristic optimization based on an Adaptive Storage Operation (ASO) scheduling is developed in this study. ASO enables the minimal 5%-DTR ESS capacity, power, energy and feed-in-tariffs to be inferred from the operating conditions, depending on tolerance. The simulations assess and compare the techno-economic viability and efficiency of every renewable sources coupled with ESS. PV power is more efficient with daylight hours restricted services and higher power levels can be guaranteed for S1. Wind and wave power are more suitable than PV for services dedicated to full-day power delivery, as in the case of S2. For hourly smoothing the forecast accuracy influence is studied and yields a high impact on techno-economic sizing.     

Life-cycle analysis of renewable energy systems

An imlementation of life-cycle analysis (LCA) for energy systems is presented and applied to two renewable energy systems (wind turbines and building-integrated photovoltaic modules) and compared with coal plants.     

意大利的节能和可再生能源激励机制

新能源与可再生能源产业是具有环境效益的弱势产业,在市场化过程中面临着诸多的障碍和问题,政府支持是新能源与可再生能源市场培育的原动力。不论是发达国家还是发展中国家,新能源与可再生能源的发展离不开政府的支持,如投融资、税收、补贴、市场渗透等一系列的优惠政策。文章介绍了意大利在节能和可再生能源方面的激励政策。     

基于信息物理模型的可再生能源电网能量平衡控制

分布式电源从属于不同运营部门,相互之间缺乏有效的信息交换,难以进行集中控制。文章针对可再生能源电网中由于新能源占比较高,易出现出力波动或出力不足,难以保障供能可靠性等问题,提出一种基于信息物理融合的可再生能源电网分布式能量控制模型。首先,为进一步提高可再生能源电网能量平衡控制能力,建立了可再生能源电网信息物理模型;然后,考虑可再生能源波动性对系统的干扰,建立一种自适应滑模观测器对可再生能源电网的扰动进行估计;最后,提出一种基于可再生能源电网的分布式协同控制器,并基于李雅普诺夫稳定性理论验证了该控制器的收敛性。仿真结果表明,文章所提出的控制方法可以提高可再生能源电网的能源利用率,增强系统的鲁棒性。     

A unified REC market and composite RPO scheme for promotion of renewable energy in India

In India, uniform price was assigned to renewable energy certificate (REC) irrespective of renewable energy (RE) type, technology, and location. Moreover REC price bands are higher than existing preferential tariff. There are distinct renewable purchase obligations (RPOs) specified for various RE types, whereas there is lack of efficient tools to check RPO compliance. Because of these reasons, REC market stabilisation is getting delayed. This paper proposes a method using plant performance multiplier to convert non-solar and solar REC to single equivalent REC with competitive REC pricing, which can be traded on unified REC market. The method combines solar and non-solar RPOs into a single composite RPO, to make RPO compliance and its checking simple and efficient. A sample illustration of the proposed method is given. The benefits offered by the proposed method in REC pricing, REC trading and RPO compliance are discussed. A comparative economic analysis of present and proposed method is reported.     

基于聚类数据包络分析模型的可再生能源发电项目综合评判决策

在深入调研的基础上,针对可再生能源发电项目规划环节面临的开发排序问题及运行后的效率综合评估问题,建立了聚类分析和数据包络分析相结合的CA/DEA两阶段评价模型。基于文中所设计的综合评价指标体系,引入了模糊层次分析法对于环境协调度等定性指标进行了综合分析,并运用基于聚类分析的主导因素挖掘方法从众多指标中选出最具影响力的因素指标;采用非参数DEA最优化模型对发电项目综合效率进行评估,较好地解决了生产函数难以确定的问题。通过CA/DEA模型所确定的综合投入产出效率,实现了对发电项目优秀度的有效评价。最后通过实例分析,验证了该评估方法的有效性及实用性。     

Sizing and operating power-to-gas systems to absorb excess renewable electricity

Various configurations of power-to-gas system are investigated as a means for capturing excess wind power in the Emden region of Germany and transferring it to the natural gas grid or local biogas-CHP plant. Consideration is given to producing and injecting low concentration hydrogen admixtures, synthetic methane, or hydrogen/synthetic methane mixtures. Predictions based on time series data for wind generation and electricity demand indicate that excess renewable electricity levels will reach about 40 MW and 45 GW h per annum by 2020, and that it is desirable to achieve a progression in power-to-gas capacity in the preceding period. The findings are indicative for regions transitioning from medium to high renewable power penetrations. To capture an increasing proportion of the growing amount of excess renewable electricity, the following recommendations are made: implement a 4 MW hydrogen admixture plant and hydrogen buffer of 600 kg in 2018; then in 2020, implement a 17 MW hybrid system for injecting hydrogen and synthetic methane (with a hydrogen storage capacity of at least 400 kg) in conjunction with a bio-methane injection plant. The 17 MW plant will capture 68% of the available excess renewable electricity in 2020, by offering an availability to the electricity grid operator of >97% and contributing 19.1 GW h of ‘green’ gas to the gas grid.     

考虑需求响应和有功损耗的含可再生能源配网节点边际电价

文章提出了一种考虑需求响应和有功损耗的节点边际电价模型;考虑有功损耗的确定性和节点边际电价模型,提出了网损灵敏度因数。针对可再生能源接入配网对节点边际的影响进行了分析和建模,并建立了需求响应模型;建立了以有功损耗最小为目标的节点边际电价模型,并计及约束条件;针对概率场景,采用2m点估计法对模型进行求解。最后采用IEEE33节点模型对算例进行了仿真分析,验证了所建模型的有效性。     

Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach

Recently, the increasing energy demand has caused dramatic consumption of fossil fuels and unavoidable raising energy prices. Moreover, environmental effect of fossil fuel led to the need of using renewable energy (RE) to meet the rising energy demand. Unpredictability and the high cost of the renewable energy technologies are the main challenges of renewable energy usage. In this context, the integration of renewable energy sources to meet the energy demand of a given area is a promising scenario to overcome the RE challenges. In this study, a novel approach is proposed for optimal design of hybrid renewable energy systems (HRES) including various generators and storage devices. The ε-constraint method has been applied to minimize simultaneously the total cost of the system, unmet load, and fuel emission. A particle swarm optimization (PSO)-simulation based approach has been used to tackle the multi-objective optimization problem. The proposed approach has been tested on a case study of an HRES system that includes wind turbine, photovoltaic (PV) panels, diesel generator, batteries, fuel cell (FC), electrolyzer and hydrogen tank. Finally, a sensitivity analysis study is performed to study the sensibility of different parameters to the developed model.     

A hybrid model for the optimum integration of renewable technologies in power generation systems

The main purpose of this work is to assess the unavoidable increase in the cost of electricity of a generation system by the integration of the necessary renewable energy sources for power generation (RES-E) technologies in order for the European Union Member States to achieve their national RES energy target. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. Also, the procedure enables the estimation of the optimum feed-in-tariff to be offered to future RES-E systems. Also, the overall cost increase in the electricity sector for the promotion of RES-E technologies, for the period 2010–2020, is analyzed taking into account factors, such as, the fuel avoidance cost, the carbon dioxide emissions avoidance cost, the conventional power system increased operation cost, etc. The overall results indicate that in the case of RES-E investments with internal rate of return (IRR) of 10% the cost of integration is higher, compared to RES-E investments with no profit, (i.e., IRR at 0%) by 0.3–0.5 €c/kWh (in real prices), depending on the RES-E penetration level.     

欧盟可再生能源发展的新政策及对我国的启示

欧洲的可再生能源发展取得了很大的成就,并建立了有效的支持可再生能源发展的政策体系和框架,是世界可再生能源发展的领先者.文章介绍了欧盟在2007年1月提出的可再生能源发展的新的政策目标以及近期采取的新行动,并提出借鉴欧洲经验,支持我国可再生能源发展的行动建议.