Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration

The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.     

Computer-aided design of PV/wind hybrid system

A complete set of match calculation methods for optimum sizing of PV/wind hybrid system is presented. In this method, the more accurate and practical mathematic models for characterizing PV module, wind generator and battery are adopted; combining with hourly measured meteorologic data and load data, the performance of a PV/wind hybrid system is determined on a hourly basis; by fixing the capacity of wind generators, the whole year’s LPSP (loss of power supply probability) values of PV/wind hybrid systems with different capacity of PV array and battery bank are calculated, then the trade-off curve between battery bank and PV array capacity is drawn for the given LPSP value; the optimum configuration which can meet the energy demand with the minimum cost can be found by drawing a tangent to the trade-off curve with the slope representing the relationship between cost of PV module and that of the battery. According to this match calculation method, a set of match calculation programs for optimum sizing of PV/wind hybrid systems have been developed. Applying these match calculation programs to an assumed PV/wind hybrid system to be installed at Waglan island of Hong Kong, the optimum configuration and its hourly, daily, monthly and yearly performances are given.     

基于双模糊控制的独立微网能量优化策略

为使微网运行效益最大化,提出一种含风—储系统的独立微网的能量优化策略,该策略采用双层模糊控制方式,针对微网峰谷特性,根据日前启停机计划确定风电机组与需求侧管理负荷的投切状态,对实时调度则使用模糊控制得到风电机组、储能与负荷的功率值。对于微网瞬时功率波动,采用模糊理论,通过蓄电池—需求侧负荷混合系统平抑功率波动。实例应用结果表明,该独立微网能量优化策略有效。     

Risk-constrained scheduling of a CHP-based microgrid including hydrogen energy storage using robust optimization approach

Recently, the integration of various energy resources, including renewable generation and combined heat and power (CHP) units in microgrids, has created the opportunity of off-grid operation with a suitable range of reliability. This paper presents an optimization model to schedule an islanded MG with various resources, including CHP, photovoltaic (PV), and boiler, as the primary energy provision sources besides electric battery storage, thermal storage and hydrogen energy system (HES). The HES has the power-to-hydrogen (P2H) and hydrogen-to-power (H2P) modes, which increases the flexibility of the scheduling. The uncertainty management is the most essential task in the CHP-based MGs scheduling problem, since the power and heat productions are interrelated and can result in economic losses without enough deliberations. Hence, this paper proposes the robust optimization approach (ROA) to cope with the uncertainties associated with the PV production and electric and heat load demands. The robust counterparts are applied to the deterministic problem to create a tractable adjustable robust framework. The problem is structured as a mixed-integer linear programming (MILP) handled by the General Algebraic Modeling System (GAMS) using CPLEX solver. The results verified the effectiveness of the proposed robust counterparts in managing the associated risk. The results illustrated a conscious scheduling strategy under robust conditions. However, the more preserved decisions are taken, the higher operational cost is realized. In this regard, the increment of robustness level from the lowest value (deterministic condition) to the highest value (conservatism condition) increased the operation cost by about 43.29%.     

Managing peak loads in energy grids: Comparative economic analysis

One of the key issues in modern energy technology is managing the imbalance between the generated power and the load, particularly during times of peak demand. The increasing use of renewable energy sources makes this problem even more acute. Various existing technologies, including stationary battery energy storage systems (BESS), can be employed to provide additional power during peak demand times. In the future, integration of on-board batteries of the growing fleet of electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) into the grid can provide power during peak demand hours (vehicle-to-grid, or V2G technology).This work provides cost estimates of managing peak energy demands using traditional technologies, such as maneuverable power plants, conventional hydroelectric, pumped storage plants and peaker generators, as well as BESS and V2G technologies. The derived estimates provide both per kWh and kW year of energy supplied to the grid. The analysis demonstrates that the use of battery storage is economically justified for short peak demand periods of <1 h. For longer durations, the most suitable technology remains the use of maneuverable steam gas power plants, gas turbine,reciprocating gas engine peaker generators, conventional hydroelectric, pumped storage plants.     

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.     

Two-stage stochastic-based scheduling of multi-energy microgrids with electric and hydrogen vehicles charging stations,considering transactions through pool market and bilateral contracts

In order to mitigate greenhouse gas emissions and improve energy efficiency, sustainable energy systems such as multi-energy microgrids (MEMGs) with the high penetration of renewable energy resources (RES) and satisfying different energy needs of consumers have received significant attention in recent years. MEMGs, by relying on renewable resources and energy storage systems along with energy conversion systems, play an essential role in sustainability of energy supply. However, renewable energies are uncertain due to the intermittent nature of solar and wind energy sources. Thus, optimal operation of the MEMGs with the consideration of the uncertainties of RES is necessary to achieve sustainability. In this paper, risk constrained scheduling of a MEMG is carried out with the presence of the PV, wind, biomass, electric vehicles (EVs) and hydrogen vehicles (HVs) charging stations, combined heat and power (CHP), boiler, hydrogen electrolyzer (HE), cryptocurrency miners (CMs), electrical, thermal and hydrogen storage systems, responsive demands. From the trading and business model side, the proposed MEMG optimized operation relies on bilateral contracts between producers and consumers and pool electricity markets. A two-stage stochastic programming method is used for considering the uncertainties of electrical, thermal and hydrogen demands, EV and HV charging stations load, CM load, PV and wind power, and the price of electricity purchased from the pool market. The proposed mixed integer linear programming (MILP) model is solved using the CPLEX solver in GAMS which guarantees to achieve a globally optimal solution. The results show that due to the certain prices of bilateral contracts, the possibility of transaction by bilateral contracts decreases the risk metric CVaR by 50.42%. The simulation results demonstrate that risk of high operation costs while considering flexibility sources, such as storages and demand response (DR) programs, is decreased by 5.45% and 4.6%, respectively. As far as operation costs are concerned, results reveal that using renewable resources decreases operation costs by 34.47%. Moreover, the operation cost is reduced by 5.94% and 4.57% in the presence of storage units and DR programs, respectively. In the same way, storages and DR programs decrease cost of purchased electricity by 13.47% and 14.46%, respectively.     

Optimisation and techno-economic analysis of autonomous photovoltaic–wind hybrid energy systems in comparison to single photovoltaic and wind systems

A techno-economic analysis for autonomous small scale photovoltaic–wind hybrid energy systems is undertaken for optimisation purposes in the present paper. The answer to the question whether a hybrid photovoltaic–wind or a single photovoltaic or wind system is techno-economically better is also sought. Monthly analysis of 8 year long measured hourly weather data shows that solar and wind resources vary greatly from one month to the next. The monthly combinations of these resources lead to basically three types of months: solar-biased month, wind-biased month and even month. This, in turn, leads to energy systems in which the energy contributions from photovoltaic and wind generators vary greatly. The monthly and yearly system performances simulations for different types of months show that the system performances vary greatly for varying battery storage capacities and different fractions of photovoltaic and wind energy. As well as the system performance, the optimisation process of such hybrid systems should further consist of the system cost. Therefore, the system performance results are combined with system cost data. The total system cost and the unit cost of the produced electricity (for a 20 year system lifetime) are analysed with strict reference to the yearly system performance. It is shown that an optimum combination of the hybrid photovoltaic–wind energy system provides higher system performance than either of the single systems for the same system cost for every battery storage capacity analysed in the present study. It is also shown that the magnitude of the battery storage capacity has important bearings on the system performance of single photovoltaic and wind systems. The single photovoltaic system performs better than a single wind system for 2 day storage capacity, while the single wind system performs better for 1.25 day storage capacity for the same system cost.     

风光互补发电系统的优化设计(I) CAD设计方法

给出了一整套利用CAD进行风光互补发电系统优化设计的方法。为了精确确定系统每小时的运行状态,采用了更精确地表征组件特性及评估实际获得的风光资源的数学模型。为了寻找出以最小设备投资成本满足用户用电要求的系统配置,首先在风力发电机容量固定不变的前提下,计算了与该容量风力发电机匹配的不同容量的PV方阵和蓄电池所组成的风/光/蓄组合的全年功率供给亏欠率LPSP,根据总的设备投资成本最小化的原则筛选出一组与该容量风力发电机对应的满足用户给定系统供电可靠性即LPSP值的风/光/蓄组合;然后通过改变风力发电机的容量,优选出多个与不同容量风力发电机对应的既能满足用户用电要求同时总的设备购置成本又是最低的风/光/蓄组合,比较它们的成本最终唯一确定出以最小投资成本满足用户用电要求的优化的系统配置。     

Review of research on autonomous wind farms and solar parks and their feasibility for commercial loads in hot regions

In the wake of rising cost of oil and fears of its exhaustion coupled with increased pollution, the governments world-wide are deliberating and making huge strides to promote renewable energy sources such as solar–photovoltaic (solar–PV) and wind energy. Integration of diesel systems with hybrid wind–PV systems is pursued widely to reduce dependence on fossil-fuel produced energy and to reduce the release of carbon gases that cause global climate change. Literature indicates that commercial/residential buildings in the Kingdom of Saudi Arabia (KSA) consume an estimated 10–40% of the total electric energy generated. The study reviews research work carried out world-wide on wind farms and solar parks. The work also analyzes wind speed and solar radiation data of East-Coast (Dhahran), KSA, to assess the technical and economic potential of wind farm and solar PV park (hybrid wind–PV–diesel power systems) to meet the load requirements of a typical commercial building (with annual electrical energy demand of 620,000 kWh). The monthly average wind speeds range from 3.3 to 5.6 m/s. The monthly average daily solar global radiation ranges from 3.61 to 7.96 kWh/m². The hybrid systems simulated consist of different combinations of 100 kW wind machines, PV panels, supplemented by diesel generators. NREL (and HOMER Energy's) HOMER software has been used to perform the techno-economic study. The simulation results indicate that for a hybrid system comprising of 100 kW wind capacity (37 m hub-height) and 40 kW of PV capacity together with 175 kW diesel system, the renewable energy fraction (with 0% annual capacity shortage) is 36% (24% wind + 12% PV). The cost of generating energy (COE, $/kWh) from this hybrid wind–PV–diesel system has been found to be 0.154 $/kWh (assuming diesel fuel price of 0.1$/L). The study exhibits that for a given hybrid configuration, the number of operational hours of diesel generators decreases with increase in wind farm and PV capacity. Attention has also been focused on wind/PV penetration, un-met load, excess electricity generation, percentage fuel savings and reduction in carbon emissions (relative to diesel-only situation) of different hybrid systems, cost break-down of wind–PV–diesel systems, COE of different hybrid systems, etc.     

Optimal energy management system for stand-alone wind turbine/photovoltaic/hydrogen/battery hybrid system with supervisory control based on fuzzy logic

This paper presents a novel hourly energy management system (EMS) for a stand-alone hybrid renewable energy system (HRES). The HRES is composed of a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and two energy storage systems (ESS), which are a hydrogen subsystem and a battery. The WT and PV panels are made to work at maximum power point, whereas the battery and the hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as support and storage system. The EMS uses a fuzzy logic control to satisfy the energy demanded by the load and maintain the state-of-charge (SOC) of the battery and the hydrogen tank level between certain target margins, while trying to optimize the utilization cost and lifetime of the ESS. Commercial available components and an expected life of the HRES of 25 years were considered in this study. Simulation results show that the proposed control meets the objectives established for the EMS of the HRES, and achieves a total cost saving of 13% over other simpler EMS based on control states presented in this paper.     

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.     

Impact assessment of electric vehicle charging/discharging strategies on the operation management of grid accessible and remote microgrids

This article deals with impact analysis of different electric vehicle (EV) charging/discharging strategies (CDS) on the operation and pollutant treatment cost of both grid accessible and remote microgrid (MG) modes. In this regard, EV demand is developed under four different scenarios, namely, uncoordinated charging model (UCM), load leveling model (LLM), maximum renewable model (MRM), and charging discharging model (CDM). A comprehensive study is performed to see the effect of these different EV charging/discharging behaviors in optimizing MG's operation. A 2m scheme of Hong's point estimate method (PEM) is applied to examine the effect of uncertainties linked with the forecasted errors in load demand, solar energy, wind energy, and grid price respectively on MG operation problem. Finally, a sensitivity analysis is performed to investigate the effect of variations in battery parameters on economics of remote MG. The study results indicate that controlled charging of EVs can substantially improve operation of MG.     

Optimal sizing study of hybrid wind/PV/diesel power generation unit

In this paper, a methodology of sizing optimization of a stand-alone hybrid wind/PV/diesel energy system is presented. This approach makes use of a deterministic algorithm to suggest, among a list of commercially available system devices, the optimal number and type of units ensuring that the total cost of the system is minimized while guaranteeing the availability of the energy. The collection of 6 months of data of wind speed, solar radiation and ambient temperature recorded for every hour of the day were used. The mathematical modeling of the main elements of the hybrid wind/PV/diesel system is exposed showing the more relevant sizing variables. A deterministic algorithm is used to minimize the total cost of the system while guaranteeing the satisfaction of the load demand. A comparison between the total cost of the hybrid wind/PV/diesel energy system with batteries and the hybrid wind/PV/diesel energy system without batteries is presented.The reached results demonstrate the practical utility of the used sizing methodology and show the influence of the battery storage on the total cost of the hybrid system.     

Risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles using downside risk constraints method

Today, the utilizations of hydrogen storage systems (HSS), renewable generation units (PV and wind generation) and distributed energy units are increased in the intelligent parking lots (IPL) in order to charge the electric vehicles (EVs) with clean energy sources. In this work, the uncertainties of upstream grid price, the demand of IPL, wind speed, solar irradiation and temperature are modeled via scenario approach based on stochastic programing. Furthermore, the downside risk constraints method (DRCM) is applied to consider risk related to uncertainties to get risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles. The proposed risk-based formulation is modeled using mixed-integer linear programming (MIP) which is implemented under GAMS software and solved via CPLEX solver. Two cases namely risk-averse and risk-neutral strategies are studied and compared to show the effects of DRCM implementation. The obtained results demonstrate the expected performance cost (EPC) of IPL is slowly raised while risk-in-cost (RIC) is significantly reduced due to model of risk related to uncertainties.     

基于NCPSO的微网群优化调度策略研究

传统的粒子群优化（PSO）算法因在微网优化中不易达到全局最优而导致微网运行成本过高,该文采用小生境混沌粒子群优化（NCPSO）算法对混合微网群的运行策略进行协同优化,以实现区域微网经济性最优、环境治理成本最低、风光等可再生能源利用率高等目的。根据所提出的调度策略,建立的优化调度模型包括动态电价下的负荷模型、经济收益模型以及成本模型等,使用NCPSO算法得到多微网在一个周期内的最佳运行状态,实现微网群系统综合能源的互动调控、空间互补。通过分析微网群的功率交互动态、可控能源的发电以及储能电池的荷电状态等,验证微网群的电力负荷响应动态电价,表明了NCPSO算法优化微网群运行的优越性、有效性。     

Promoting applications of hybrid (wind+photovoltaic+diesel+battery) power systems in hot regions

Depleting oil and gas reserves, combined with growing concerns of atmospheric pollution/degradation, have made the search for energy from renewable sources of energy, such as solar and wind, inevitable. Literature indicates that commercial/residential buildings in Saudi Arabia consume an estimated 10–40% of the total electric energy generated. In the present study, hourly mean wind-speed and solar radiation data for the period 1986–1997 recorded at the solar radiation and meteorological monitoring station, Dhahran (26°32′ N, 50°13′ E), Saudi Arabia, have been analyzed to investigate the potential of utilizing hybrid (wind+solar) energy conversion systems to meet the load requirements of a typical commercial building (with annual electrical energy demand of 620 000 kWh). The monthly average wind speeds for Dhahran range from 4.1 to 6.4 m/s. The monthly average daily values of solar radiation for Dhahran range from 3.6 kWh/m² to 7.96 kWh/m². The hybrid systems considered in the present analysis consist of different combinations of commercial 10 kW wind energy conversion systems (WECS), photovoltaic (PV) panels supplemented with battery storage unit and diesel back-up. The study shows that with 30 10-kW WECS together with 150 m² PV, and 3 days of battery storage, the diesel back-up system has to provide 17% of the load demand. However, in the absence of battery storage, about 38% of the load needs to be provided by the diesel system.     

Performance analysis of hybrid photovoltaic/diesel energy system under Malaysian conditions

Standalone diesel generating system utilized in remote areas has long been practiced in Malaysia. Due to highly fluctuating diesel price, such a system is seemed to be uneconomical, especially in the long run if the supply of electricity for rural areas solely depends on such diesel generating system. This paper would analyze the potential use of hybrid photovoltaic (PV)/diesel energy system in remote locations. National Renewable Energy Laboratory’s (NREL) HOMER software was used to perform the techno-economic feasibility of hybrid PV/diesel energy system. The investigation demonstrated the impact of PV penetration and battery storage on energy production, cost of energy and number of operational hours of diesel generators for the given hybrid configurations. Emphasis has also been placed on percentage fuel savings and reduction in carbon emissions of different hybrid systems. At the end of this paper, suitability of utilizing hybrid PV/diesel energy system over standalone diesel system would be discussed mainly based on different solar irradiances and diesel prices.     

Hybridized off-grid fuel cell/wind/solar PV /battery for energy generation in a small household: A multi-criteria perspective

In this paper, the robust capability of HOMER and Criteria-COPRAS is deployed to explore the prospect of selecting a renewable energy system. The energy system consisting of wind turbines, solar photovoltaic (PV), fuel cell (FC), electrolyzer, hydrogen storage, and battery energy storage is intended to power a residential load in Lagos Nigeria. Based on the economic metric, the results show that the optimal system is a PV-Battery whose total net present cost (TNPC) and initial investment cost are $9060 and $3,818, respectively. However, if the energy systems are ranked based on multiple criteria (economic, technical and environmental aspects), the most preferred of the feasible energy systems is a hybrid PV-FC-wind-battery (TNPC-$10,324, initial cost: $7670). The study results indicate that, for viability in the adoption of hydrogen energy storage as part of the hybrid energy system, the selection metric should be based on more than one criterion.     

Off-grid hybrid renewable energy system with hydrogen storage for South African rural community health clinic

Most inhabitants of rural communities in Africa lack access to clean and reliable electricity. This has deprived the rural dwellers access to modern healthcare delivery. In this paper, an off-grid renewable energy system consisting of solar PV and wind turbine with hydrogen storage scheme has been explored to meet the electrical energy demands of a health clinic. The health clinic proposed is a group II with 10 beds located in a typical village in South Africa. First, the wind and solar energy resources of the village were analysed. Thereafter, the microgrid architecture that would meet the energy demand of the clinic (18.67 kWh/day) was determined. Some of the key results reveal that the average annual wind speed at 60 m anemometer height and solar irradiation of the village are 7.9 m/s and 4.779 kWh/m²/day, respectively. The required architecture for the clinic composes of 40 kW solar PV system, 3 numbers of 10 kW wind turbines, 8.6 kW fuel cell, 25 kW electrolyser and 40 kg hydrogen tank capacity. The capital cost of the microgrid was found to be $177,600 with a net present cost of $206,323. The levelised cost of energy of the system was determined to be 2.34 $/kWh. The project has a breakeven grid extension distance of 8.81 km. Since this distance is less than the nearest grid extension distance of 21.35 km, it is established that the proposed renewable energy microgrid with a hydrogen storage system is a viable option for the rural community health clinic.