Optimised model for community-based hybrid energy system

Hybrid energy system is an excellent solution for electrification of remote rural areas where the grid extension is difficult and not economical. Such system incorporates a combination of one or several renewable energy sources such as solar photovoltaic, wind energy, micro-hydro and may be conventional generators for backup. This paper discusses different system components of hybrid energy system and develops a general model to find an optimal combination of energy components for a typical rural community minimizing the life cycle cost.The developed model will help in sizing hybrid energy system hardware and in selecting the operating options. Micro-hydro-wind systems are found to be the optimal combination for the electrification of the rural villages in Western Ghats (Kerala) India, based on the case study. The optimal operation shows a unit cost of Rs. 6.5/kW h with the selected hybrid energy system with 100% renewable energy contribution eliminating the need for conventional diesel generator.     

Modelling of hybrid energy system—Part I: Problem formulation and model development

A well designed hybrid energy system can be cost effective, has a high reliability and can improve the quality of life in remote rural areas. The economic constraints can be met, if these systems are fundamentally well designed, use appropriate technology and make use effective dispatch control techniques. The first paper of this tri-series paper, presents the analysis and design of a mixed integer linear mathematical programming model (time series) to determine the optimal operation and cost optimization for a hybrid energy generation system consisting of a photovoltaic array, biomass (fuelwood), biogas, small/micro-hydro, a battery bank and a fossil fuel generator. The optimization is aimed at minimizing the cost function based on demand and potential constraints. Further, mathematical models of all other components of hybrid energy system are also developed. This is the generation mix of the remote rural of India; it may be applied to other rural areas also.     

Techno-economic analysis of a hybrid energy system for CCHP and hydrogen production based on solar energy

A typical problem in Northeast China is that a large amount of surplus electricity has arisen owing to the serious photovoltaic power curtailment phenomenon. To effectively utilize the excess photovoltaic power, a hybrid energy system is proposed that uses surplus electricity to produce hydrogen in this paper. It combines solar energy, hydrogen production system, and Combined Cooling Heating and Power (CCHP) system to realize cooling, heating, power, and hydrogen generation. The system supplies energy for three public buildings in Dalian City, Liaoning Province, China, and the system configuration with the lowest unit energy cost (0.0615$/kWh) was obtained via optimization. Two comparison strategies were used to evaluate the hybrid energy system in terms of unit energy cost, annual total cost, fossil energy consumption, and carbon dioxide emissions. Subsequently, the annual total energy supply, typical daily loads, and cost of the optimized system were analyzed. In conclusion, the system is feasible for small area public buildings, and provides a solution to solve the phenomenon of photovoltaic power curtailment.     

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     

Size optimization of a hybrid photovoltaic/fuel cell grid connected power system including hydrogen storage

This paper describes the size optimization of a hybrid photovoltaic/fuel cell grid linked power system including hydrogen storage. The overall objective is the optimal sizing of a hybrid power system to satisfy the load demand of a university laboratory with an unreliable grid, with low energy cost and minimal carbon emissions. The aim is to shift from grid linked diesel power system to a clean and sustainable energy system. The optimum design architecture was established by adopting the energy-balance methods of HOMER (hybrid optimization model for electric renewables). Analysis of hourly simulations was performed to decide the optimal size, cost and performance of the hybrid system, using 22-years monthly averaged solar radiation data collected for Ambrose Alli University, Ekpoma (Lat. 6°44.3ʹN, Long. 6°4.8ʹE). The results showed that a hybrid system comprising 54.7 kW photovoltaic array, 7 kW fuel cell system, 14 kW power inverter and 3 kW electrolyzer with 8 kg hydrogen storage tank can sustainably augment the erratic grid with a very high renewable fraction of 96.7% at $0.0418/kWh. When compared with the conventional usage of grid/diesel generator system; energy cost saving of more than 88% and a return on investment of 41.3% with present worth of $308,965 can be derived in less than 3 years. The application of the optimally sized hybrid system would possibly help mitigate the rural-to-urban drift and resolve the electricity problems hindering the economic growth in Nigeria. Moreover, the hybrid system can alleviate CO₂ emissions from other power generation sources to make the environment cleaner and more eco-friendly.     

基于VMD的混合储能容量优化配置

针对光伏发电输出功率的波动性以及混合储能容量优化,以光储联合的发电系统为研究对象,提出一种基于变分模态分解(VMD)的混合储能容量优化配置策略.该策略采用VMD对光伏输出功率进行处理,利用欧氏距离方法将相关模态和非相关模态进行区分,利用滑动平均法提取非相关模态中的持续分量信号,将其与相关模态进行重构作为满足国家标准的并...     

Generation unit sizing and cost analysis for stand-alone wind,photovoltaic, and hybrid wind/PV systems

This paper presents the results of investigations on the application of wind, photovoltaic (PV), and hybrid wind/PV power generating systems for utilization as stand-alone systems. A simple numerical algorithm has been developed for generation unit sizing. It has been used to determine the optimum generation capacity and storage needed for a stand-alone, wind, PV, and hybrid wind/PV system for an experimental site in a remote area in Montana with a typical residential load. Generation and storage units for each system are properly sized in order to meet the annual load and minimize the total annual cost to the customer. In addition, an economic analysis has been performed for the above three scenarios and is used to justify the use of renewable energy versus constructing a line extension from the nearest existing power line to supply the load with conventional power. Annual average hourly values for load, wind speed, and insolation have been used     

基于最大投资回报率的风光联合并网情况下输电网规划

江苏省电力设计院, 江苏 南京 211102     

独立光伏发电混合储能系统容量优化研究

准确建立系统中各环节数学模型,综合考虑不同储能元件（超级电容器和蓄电池）的储能特性,以混合储能系统成本最低为优化目标,以独立光伏发电系统各项运行技术指标为约束条件,提出了一种基于单纯形法的容量优化配置方法,并进行了编程实现和算例验证。     

Techno-economic feasibility of photovoltaic,wind, diesel and hybrid electrification systems for off-grid rural electrification in Colombia

Electrification to rural and remote areas with limited or no access to grid connection is one of the most challenging issues in developing countries like Colombia. Due to the recent concerns about the global climatic change and diminishing fuel prices, searching for reliable, environmental friendly and renewable energy sources to satisfy the rising electrical energy demand has become vital. This study aims at analyzing the application of photovoltaic (PV) panels, wind turbines and diesel generators in a stand-alone hybrid power generation system for rural electrification in three off-grid villages in Colombia with different climatic characteristics. The areas have been selected according to the “Colombia’s development plan 2011–2030 for non-conventional sources of energy”. First, different combinations of wind turbine, PV, and diesel generator are modeled and optimized to determine the most energy-efficient and cost-effective configuration for each location. HOMER software has been used to perform a techno-economic feasibility of the proposed hybrid systems, taking into account net present cost, initial capital cost, and cost of energy as economic indicators.     

Optimization of hybrid solar energy sources/wind turbine systems integrated to utility grids as microgrid (MG) under pool/bilateral/hybrid electricity market using PSO

This study presents an optimized design of microgrid (MG) in distribution systems with multiple distributed generation (DG) units under different market policies such as pool/hybrid electricity market.Proposed microgrid includes various energy sources such as photovoltaic array and wind turbine with energy storage devices such as battery bank.In this study, microgrid is considered as independent power producer company (IPP) in power system. Price of selling/buying power in on-peak or off-peak for MG, DG and upstream power system (DISCO) under pool/bilateral/hybrid electricity market are different. In this study, particle swarm optimization (PSO) algorithm has been implemented for the optimization of the microgrid cost. The costs include capital cost, replacement cost, operation and maintenance costs and production cost for microgrid and DGs. Then, an objective function to maximize total net present worth (NPW) is presented. PSO approach is employed to obtain the minimum cost of microgrid, during interconnected operation by optimizing the production of local DGs and power exchanges with the main distribution grid. The optimization algorithm is applied to a typical LV network operating under different market policies.     

光水混合发电系统优化策略研究

为了提高独立能源发电的可靠性与运行效率,结合光水发电系统的混合发电模式,搭建出光水混合发电系统的优化模型,并基于改进型粒子群优化算法(CPSO)对混合光水发电系统进行仿真计算,比较了混合发电与单一发电系统中传输功率及效益。结果表明,通过对光水混合发电系统中水电优化,解决了光伏发电不稳定问题,更好地利用了太阳能与水电资源优化互补的特性,实现了效益最大化。     

考虑需求侧响应的微网混合储能优化配置

在微网中配置混合储能并引入需求侧响应机制,有利于提高电网运行时的灵活性,降低分布式电源对电网带来的冲击。针对含风力发电机、光伏、储能的并网型微电网,引入需求侧响应机制,建立了以混合储能全寿命周期净现值、微网购电成本和需求侧响应成本为目标函数的微网混合储能优化配置模型,对混合储能容量进行优化配置,采用改进差分算法求解该模型。结合某地实际微网进行验证,结果表明,混合储能可有效改善分布式电源对微电网的影响,需求侧响应可显著降低混合储能成本,提高微网运行的经济效益,为类似微网混合储能优化配置提供了参考。     

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。     

Hybrid optimization algorithm for modeling and management of micro grid connected system

In this paper, a hybrid optimization algorithm is proposed for modeling and managing the micro grid (MG) system. The management of distributed energy sources with MG is a multi-objective problem which consists of wind turbine (WT), photovoltaic (PV) array, fuel cell (FC), micro turbine (MT) and diesel generator (DG). Because, perfect economic model of energy source of the MG units are needed to describe the operating cost of the output power generated, the objective of the hybrid model is to minimize the fuel cost of the MG sources such as FC, MT and DG. The problem formulation takes into consideration the optimal configuration of the MG at a minimum fuel cost, operation and maintenance costs as well as emissions reduction. Here, the hybrid algorithm is obtained as artificial bee colony (ABC) algorithm, which is used in two stages. The first stage of the ABC gets the optimal MG configuration at a minimum fuel cost for the required load demand. From the minimized fuel cost functions, the operation and maintenance cost as well as the emission is reduced using the second stage of the ABC. The proposed method is implemented in the Matlab/Simulink platform and its effectiveness is analyzed by comparing with existing techniques. The comparison demonstrates the superiority of the proposed approach and confirms its potential to solve the problem.     

An optimization scheduling method of electric vehicle virtual energy storage to track planned output based on multiobjective optimization

Electric vehicle virtual energy storage technology can effectively improve the utilization of renewable energy. Aiming at the impact of the uncertainty of electric vehicle on the power grid, an optimized dispatching method of hybrid energy storage systems based on multiobjective optimization in the scenario of tracking plan output is proposed in this paper. The predicted value of the photovoltaic power obtained by the particle swarm optimization (PSO)-back propagation (BP) neural network is used to formulate the planned output of photovoltaic power generation, and the principle component analysis algorithm is used to extract the main features affecting photovoltaic power generation to further improve the prediction accuracy of photovoltaic output power. From the perspective of the service life of electric vehicles, a two-stage optimal control method of hybrid energy storage systems based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to achieve energy distributions between electric vehicles and supercapacitors. Fully consider the benefits of electric vehicle users and the capacity of tracking plans, a multiobjective optimization model of hybrid energy storage systems to track planned output is established, and the nondominated sorted genetic algorithm-III is adopted to solve the model. The validity of the model is verified by a simulation test of actual operating data of a business park in China. The simulation results show that after the optimized control, the average absolute error of the deviation power reduces from 1.092 to 0.0528 MW, power fluctuating times of electric vehicles decreases from 151 to 80, and the daily income benefit increases from $404.468 to $483.116 in the cloudy day. The method proposed in this paper can effectively improve the controllability of renewable energy, and provide a theoretical basis for the application of electric vehicle virtual energy storage technology.     

Comprehensive review and performance evaluation of maximum power point tracking algorithms for photovoltaic system

A photovoltaic array is environmentally friendly and a source of unlimited energy generation. However, it is presently a costlier energy generation system than other non-renewable energy sources. The main reasons are seasonal variations and continuously changing weather conditions, which affect the amount of solar energy received by the solar panels. In addition, the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays. To address this problem, the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm (MPPT) and the operating point of the photovoltaic system can be forced to its optimum value. This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power. However, the tracking algorithms are not equally effective in all areas of application. Therefore, selecting the correct MPPT is very critical. This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems, with consideration of the following key parameters: photovoltaic array dependence, type of system (analog or digital), need for periodic tuning, convergence speed, complexity of the system, global maxima, implemented capacity, and sensed parameter(s). In addition, based on real meteorological data (irradiance and temperature at a site located in Addis Ababa, Ethiopia), a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied. Finally, the study clearly validates the considerable energy saving achieved by using these algorithms.     

A reliable methodology based on mine blast optimization algorithm for optimal sizing of hybrid PV-wind-FC system for remote area in Egypt

In this paper, a reliable methodology incorporated mine blast algorithm (MBA) is applied to solve the optimal sizing of a hybrid system consisting of photovoltaic modules, wind turbines and fuel cells (PV/WT/FC) to meet a certain load of remote area in Egypt. The main objective of the optimal sizing process is to achieve the minimum annual cost of the system with load coverage. The sizing process is performed optimally based on real measured data for solar radiation, ambient temperature and wind velocity recorded by the solar radiation and meteorological station located at national research institute of astronomy and geophysics, Helwan city, Egypt. Three other meta-heuristic optimization techniques, particle swarm optimization, cuckoo search and artificial bee colony are applied to solve the problem and the results are compared with those obtained by the proposed methodology. A power management strategy that regulates the power flow between each system component is also presented. The obtained results show that; applying the proposed methodology will save about 24.8% in the annual total cost of the proposed system compared with PSO, 8.956% compared with CS and 11.5576% compared with ABC. The proposed algorithm based on MBA is candidate for solving the presented optimization problem of optimal sizing the hybrid PV/WT/FC system.     

A hybrid optimization technique for proficient energy management in smart grid environment

Electrical energy is one of the key components for the development and sustainability of any nation. India is a developing country and blessed with a huge amount of renewable energy resources still there are various remote areas where the grid supply is rarely available. As electrical energy is the basic requirement, therefore it must be taken up on priority to exploit the available renewable energy resources integrated with storage devices like fuel cells and batteries for power generation and help the planners in providing the energy-efficient and alternative solution. This solution will not only meet electricity demand but also helps reduce greenhouse gas emissions as a result the efficient, sustainable and eco-friendly solution can be achieved which would contribute a lot to the smart grid environment. In this paper, a modified grey wolf optimizer approach is utilized to develop a hybrid microgrid based on available renewable energy resources considering modern power grid interactions. The proposed approach would be able to provide a robust and efficient microgrid that utilizes solar photovoltaic technology and wind energy conversion system. This approach integrates renewable resources with the meta-heuristic optimization algorithm for optimal dispatch of energy in grid-connected hybrid microgrid system. The proposed approach is mainly aimed to provide the optimal sizing of renewable energy-based microgrids based on the load profile according to time of use. To validate the proposed approach, a comparative study is also conducted through a case study and shows a significant savings of 30.88% and 49.99% of the rolling cost in comparison with fuzzy logic and mixed integer linear programming-based energy management system respectively.     

An artificial intelligence approach to optimization of an off-grid hybrid wind/hydrogen system

Off-grid electrification of remote areas using a hybrid renewable energy scheme is a requirement to achieve the goals of sustainable development. However, the optimization and sizing for the capacity of such systems are challenging. In this regard, this study targets an improved optimization algorithm with high efficiency for optimization and long-term capacity planning of an off-grid hybrid renewable energy scheme composed of wind, fuel cell, and hydrogen storage schemes. The suggested methods are three improved versions of the global dynamic harmony search to do pitch adjustment mechanism. The objective function of this study is to reduce the total net annual cost of the system and the loss of power supply probability to a minimum. The performance of this hybrid system is examined via a simulation study, which had been performed on a remote area located in eastern Iran over a long period. The results of the three improved proposed algorithms are compared with the original global dynamic harmony search algorithm. Also, sensitivity analysis is proposed to showcase the influence of uncertainties on the system and input parameters on the algorithm. The simulation results indicate that three improved versions of the global dynamic harmony search algorithm ?nd more promising results than the original algorithm, and confirm the superior accuracy, convergence speed, and robustness of the global dynamic harmony search-II. Also, reliability level and iteration values have a considerable impact on the total net annual cost of the optimal hybrid energy system based on wind and hydrogen energy.