Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review

Integrating renewable energy hybrid distributed generation (REHDG) into distribution network systems (DNSs) has become increasingly important because of various technical, economic, and environmental advantages accruing from it. However, the output power of REHDGs from photovoltaic (PV) and wind is highly variable because of its dependency on intermittent parameters such as solar irradiance, temperature, and wind speed. Such variability of generated power from large-scale REHDGs or load introduces small signal instabilities (oscillations). Meanwhile, different locations of integration and sizes of REHDGs in the DNS affect the system oscillation modes by either improving or depriving the small-signal stability (SSS) of the network. Consequently, a significant number of research has been conducted on the planning of optimal allocation of REHDGs in DNS. In this regard, this paper reviews the existing planning models, optimisation techniques, and resources' uncertainty modelling employed in REHDGs allocations in terms of their capability in obtaining optimal solutions and enhancing SSS of the system. Planning models with optimisation algorithms are evaluated for modelling renewable resource uncertainties and curtailing SSS variables. Research works on planning of optimal allocation of these generations attain minimum cost, but were unable to satisfy the SSS requirements of the system. The existing models for the planning and design of optimal timing, sizing, and placement of REHDGs will need to be improved to optimally allocate REHDGs and satisfy the SSS of the DNS after the integration.     

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.     

Grid integrated renewable DG systems: A review of power quality challenges and state-of-the-art mitigation techniques

Increased energy demands due to rapid industrialization, environmental concerns with fossil fuel–based generation, diminishing fossil energy resources, transmission network congestion, and technical performance deterioration are the motivations behind the integration of small renewable distributed generation (DG) units and turning the existing power systems into a restructured one. Optimizing the technical benefits offered by DG placement is a well-known challenge for distribution network operators (DNOs) for both fossil and renewable energy resource–based DGs, but renewable DG systems have several power quality (PQ) challenges associated additionally. Power quality is a very significant characteristic of renewable DG systems because today's loads are more sensitive to PQ disturbances and penetration of renewable energy as well as nonlinear loads is proliferating in distribution power networks. So the need for innovative power quality improvement (PQI) techniques becomes inevitable due to ongoing reformation in traditional distribution networks by the integration of renewable energy. This article presents a comprehensive analysis of power quality challenges with grid integration of renewable DG systems and current research status of associated mitigation techniques. Firstly, this paper puts emphasis on theoretically illustrating all the crucial power quality challenges associated with grid integration of renewable energy, and secondly, a thorough survey, of all PQI techniques introduced till date, is elaborated along with highlighting the opportunities for future research. Furthermore, all the crucial power quality issues, the impact of high penetration of renewable energy and mitigation techniques on power quality, are demonstrated also by simulating a grid integrated PV-based DG system in MATLAB/Simulink. This article is believed to be very beneficial for academics as well as industry professionals to understand existing PQ challenges, PQI techniques, and future research directions for renewable energy technologies.     

Optimal hybrid renewable energy systems for energy security: a comparative study

A hybrid power system may be used to reduce dependency on either conventional energy or renewable systems. This article deals with the sizing, generator running hours, sensitivity analysis, optimisation, and greenhouse gas emission analysis of hybrid renewable energy systems (HRES). Two locations have been selected where the feasibility of using different hybrid systems is studied for the same load demand. One site is the small remote community of Amini in the Lakshadweep Islands, located in southern India in the Arabian Sea, where solar and/or wind energy is always available throughout the year to provide energy security. Another place is the rural township of Hathras, in the northern Indian state of Uttar Pradesh, where agricultural biomass is found in abundance for the whole year. A comparative study has been made for the two locations for the same load demand by simulating HRES. To achieve the goal of simulation, the hybrid optimisation model for electric renewables (HOMER) software of the National Renewable Energy Laboratory, USA, is used. An optimisation model of a hybrid renewable system has been prepared which simplifies the task of evaluating the design of an off-grid/standalone system. After simulating all possible system equipment with their sizes, a list of many possible configurations may be evaluated and sorted by net present cost to compare the design options. An elaborate sensitivity analysis has been used for each input variable; the whole optimisation process is repeated to get simulated system configurations     

Hybrid renewable energy‐based distribution system for seasonal load variations

In recent scenario, there is abundant availability of renewable energy resources to satisfy the significant increase in residential, industrial, and commercial demand. This paper presents a novel framework to determine the preeminent size of renewable distributed generators (RDGs) by optimizing the system components such as area required for solar‐photovoltaic modules, swept area occupied by wind turbine blades, and area used by fuel cell. A microgrid with hybrid RDG (h‐RDG) is integrated in distribution system to minimize the distribution loss, substation energy requirement, and improve the voltage level of the load. The power loss minimization is formulated as a nonlinear problem and optimized by the proposed Hybrid Nelder Mead‐Particle Swarm Optimization algorithm. The microgrid location is identified by voltage stability index to improve the stability of system. Further, the system is analyzed for energy flow in different seasonal loading conditions with mixture of residential, industrial, and commercial load. The effective performance of the proposed technique is applied to standard 12‐bus, 69‐bus, and a practical Tamil Nadu (TN) 84‐bus radial distribution system (RDS) for different hybrid combinations of h‐RDG in microgrid. The result proves that the proposed method provides a simple and efficient tool for optimal and flexible use of h‐RDG in microgrid under different climatic changes by simultaneously reducing distribution energy loss and improving voltage profile.     

An updated review of energy storage systems: Classification and applications in distributed generation power systems incorporating renewable energy resources

The demand of electric energy is increasing globally, and the fact remains that the major share of this energy is still being produced from the traditional generation technologies. However, the recent trends, for obvious reasons of environmental concerns, are indicating a paradigm shift towards distributed generation (DG) incorporating renewable energy resources (RERs). But there are associated challenges with high penetration of RERs as these resources are unpredictable and stochastic in nature, and as a result, it becomes difficult to provide immediate response to demand variations. This is where energy storage systems (ESSs) come to the rescue, and they not only can compensate the stochastic nature and sudden deficiencies of RERs but can also enhance the grid stability, reliability, and efficiency by providing services in power quality, bridging power, and energy management. This paper provides an extensive review of different ESSs, which have been in use and also the ones that are currently in developing stage, describing their working principles and giving a comparative analysis of important features and technical as well as economic characteristics. The wide range of storage technologies, with each ESS being different in terms of the scale of power, response time, energy/power density, discharge duration, and cost coupled with the complex characteristics matrices, makes it difficult to select a particular ESS for a specific application. The comparative analysis presented in this paper helps in this regard and provides a clear picture of the suitability of ESSs for different power system applications, categorized appropriately. The paper also brings out the associated challenges and suggests the future research directions.     

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.     

An energy system for the integration of renewable energy with energy storage in a frigid plateau region

面向高原高寒地区对稳定供热和供电的迫切需求,本文提出了一种新型的可再生能源与储能集成供能系统。该系统包括风力发电、光伏发电、水力发电、槽式太阳能集热器、储热系统、储电装置以及集成控制系统,实现了多种可再生能源高效利用;制定了一种考虑热电设备性能的实时能量管理策略,并建立了以年成本为主要优化目标的容量配置方法;利用该系统与优化方法对高原高寒地带民用住宅群的供能系统进行了优化设计,通过案例对比分析,验证了该集成供能系统容量配置方法和能量管理策略的可行性。研究结果为高原高寒地区供能系统的选择提供了有益的参考。     

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

Generation expansion planning (GEP) is a power plant mix problem that identifies what, where, when, and how new generating facilities should be installed and when old units be retired over a specific planning horizon. GEP ensures that the quantity of electricity generated matches the electricity demand throughout the planning horizon. This kind of planning is of importance because most production and service delivery is dependent on availability of electricity. Over the years, the traditional GEP approaches have evolved to produce more realistic models and new solution algorithms. For example, with the agitation for green environment, the inclusion of renewable energy plants and energy storage in the traditional GEP model is gradually gaining attention. In this regards, a handful of research has been conducted to identify the optimal expansion plans based on various energy‐related perspectives. The appraisal and classification of studies under these topics are necessary to provide insights for further works in GEP studies. This article therefore presents a comprehensive up‐to‐date review of GEP studies. Result from the survey shows that the integration of demand side management, energy storage systems (ESSs), and short‐term operational characteristics of power plants in GEP models can significantly improve flexibility of power system networks and cause a change in energy production and the optimal capacity mix. Furthermore, this article was able to identify that to effectively integrate ESS into the generation expansion plan, a high temporal resolution dimension is essential. It also provides a policy discussion with regard to the implementation of GEP. This survey provides a broad background to explore new research areas in order to improve the presently available GEP models.     

A multi‐objective evolutionary optimization of fuzzy controller for energy conservation in air conditioning systems

This paper presents the use of evolutionary optimization approach to design and tune smart fuzzy controllers for heating, ventilation, and air conditioning systems or HVAC. The objective is to optimize energy consumption while accounting for user comfort requirements. The problem of energy conservation in air conditioning systems becomes a multi‐objective optimization constrained problem, which enlarges the solution search space. To solve this problem, a multi‐objective evolutionary optimization technique based on genetic algorithm (GA) is proposed. A physical experimental setup is constructed for data collection and formulation of mathematical model. A fuzzy controller is initially designed through expert knowledge, and GA is then used to tune the rules and membership functions of the fuzzy controller in order to optimize multiple objectives. Simulations and real experiments are compared to determine the effectiveness of the proposed strategy. As compared to the controller present in the real experimental air conditioner, approximately 15% energy is successfully saved with no increase in average individual dissatisfaction or discomfort index. Also, a decrease in peak individual dissatisfaction or discomfort index from 91% to 62% is observed. Copyright © 2013 John Wiley & Sons, Ltd.     

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。     

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.     

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.     

可再生能源多能互补的分布式能源系统两级超结构模型

针对现有分布式能源系统设计受区域、资源和政策差异性的影响,建立了一套考虑可再生能源多能互补的超结构模型框架和通用求解方法.通过对系统流程结构和单元设备物理特性的逻辑描述,确定模型输入输出参数.引入强制进化随机游走算法,实现不同用能负荷需求、可再生能源形式和区域条件的求解计算.将提出的优化模型应用于具体算例,根据资源、设...     

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.     

Research and deployment priorities for renewable technologies: Quantifying the importance of various renewable technologies for low cost,high renewable electricity systems in an Australian case study

This study aims to identify research priorities to enable low cost, high renewable power systems. An evolutionary program optimises the mix of technologies in 100% renewable energy portfolios (RE) in the Australian National Electricity Market. Various technologies are reduced in availability to determine their relative importance for achieving low costs. The single most important factor is found to be the integration of large quantities of wind; therefore wind integration is identified as a research priority. In contrast, photovoltaics are found to “saturate” the system at less than 10% of total energy (in the absence of storage or demand management, installation of further photovoltaics does not contribute significant further value). This indicates that policies to promote utility-scale photovoltaics should be considered in partnership with complementary measures (such as demand side participation and storage). Biofuelled gas turbines are found to be important; a complete absence of bioenergy increases costs by AU$20–30/MWh, and even having only 0.1 TWh per year of bioenergy available reduces average costs by AU$3–4/MWh. Limits on the non-synchronous penetration (NSP) are found to be relatively expensive, suggesting a significant research priority around finding alternative approaches to providing synchronous services, such as inertia. Geothermal and concentrating solar thermal technologies do not appear essential as long as sufficient wind and peaking bioenergy is available.     

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.