Optimal operation of a wind-electrolytic hydrogen storage system in the electricity/hydrogen markets

Wind power, the most promising renewable energy source in the world, plays an important role in the electricity markets. Wind power curtailment cannot be avoided in some countries due to its output has a special feature of randomness and volatility. Since the excess wind power being converted into hydrogen and sold to the hydrogen market will be the future trend. This study proposes a wind-electrolytic hydrogen storage system to participate in the electricity/hydrogen markets for selling electricity and hydrogen, which can help to improve the benefits of wind power in the electricity markets and addree the wind power curtailment effectively. With considering the uncertainties of wind power outputs and electricity prices, the optimal operation strategy is proposed with the objective of maximizing profits. The scenario-based stochastic method is adopted to describe the uncertainties, and the financial risk is evaluated using conditional value-at-risk. The operational problem of the proposed system is formulated into a mixed-integer linear programming model. Finally, the feasibility of the proposed operational strategy is validated by a case study. The results show that the expected revenue increases with the increase of the hydrogen selling price, indicating that investors can obtain profits by converting electricity into hydrogen. The optimal expected revenue increases by 33.42% when hydrogen price increases from 1.2 DKK/kWh to 1.8 DKK/kWh and the risk factor is equal to 0. Based on the analysis of the results, the importance of hydrogen can be proven.     

An optimal energy management strategy with subsection bi-objective optimization dynamic programming for photovoltaic/battery/hydrogen hybrid energy system

Nowadays, the scheme of a stand-alone microgrid utilizing renewable energy is regarded as an effective approach to guarantee the power supply of an off-grid system. However, the intermittent nature of renewables brings new challenges to the determination of the optimal operation point for a hybrid energy system (HES). To address this issue, this paper proposes a subsection bi-objective optimization dynamic programming strategy for the HES consisting of photovoltaic, fuel cell, electrolyzer, hydrogen storage system, and battery bank. Within the proposed strategy, reasonable rule-based judgment is introduced to reduce the complexity of system control. Moreover, dynamic programming is selected to obtain the global optimal power distribution scheme. Meanwhile, a multi-objective genetic algorithm strategy is designed for comparative analysis. The results in two typical cases indicate the proposed strategy can improve photovoltaic utilization by 0.95% and 0.0003%, and fuel economy by nearly 50%.     

On the design and optimization of distributed energy resources for sustainable grid-integrated microgrid in Ethiopia

This paper presents a study that focuses on alleviating the impacts of grid outages in Ethiopia. To deal with grid outages, most industrial customers utilize backup diesel generators (DG) which are environmentally unfriendly and economically not viable. Grid-integration of hybrid renewable energy systems (HRES) might be a possible solution to enhance grid reliability and reduce environmental and economic impacts of utilizing DG. In this study, an optimization of grid integrated HRES is carried out for different dispatch and control strategies. The optimal power supply option is determined by performing comparative analysis of the different configurations of grid integrated HRES. The result of the study shows that grid integrated HRES consisting of photovoltaic and wind turbine as renewable energy sources, and battery and hydrogen as hybrid energy storage systems is found to be the optimal system to supply the load demand. From the hydrogen produced on-site, the FC generator and FCEVs consume 143 620 kg/yr of hydrogen which is equivalent to 394 955 kg/yr gasoline fuel consumption. This corresponds to saving 1 184 865 kg/yr of CO₂ emissions and 605 703 $/yr revenue. Besides, this system yields 547 035.4 $/yr revenue by injecting excess electricity to the grid. The study clearly shows the economic and environmental viability of this new technology for implementation.     

光储微网的储能优化配置与技术经济分析

在储能系统和光伏发电相结合的统筹规划中,电池储能投资成本、光伏装机容量、光伏并网价格以及热电联产(CHP)的采用对电池储能的容量配置和电池充放电策略具有显著影响。基于分时电价下的光伏储能系统,将电池储能的容量和功率的配置转化为根据电价时段划分的约束优化问题。以某工业园区为研究对象,建立光伏-储能系统功率流模型,优化计算得到经济效益最优化的电池容量和功率配置结果及电池充放电策略。基于内部收益率、光伏自我消纳率等指标,根据光伏上网价格和电网谷段电价的关系划分场景,通过光伏发电容量和电池价格的变化探究光伏-储能系统中电池储能的容量配置、经济效益的变化规律和热电联产对系统的影响。     

Techno-economic analysis of hydrogen energy for renewable energy power smoothing

With the increasing proportion of renewable energy (mainly wind power and photovoltaic) connected to the grid, the fluctuation of renewable energy power brings great challenges to the safe and reliable operation of power grid. As a clean, low-carbon secondary energy, hydrogen energy is applied in renewable energy (mainly wind power and photovoltaic) grid-connected power smoothing, which opens up a new way of coupling hydrogen storage energy with renewable energy. This paper focuses on the optimization of capacity of electrolyzers and fuel cells and the analysis of system economy in the process of power output smoothing of wind/photovoltaic coupled hydrogen energy grid-connected system. Based on the complementary characteristics of particle swarm optimization (PSO) and chemical reaction optimization algorithm (CROA), a particle swarm optimization-chemical reaction optimization algorithm (PSO-CROA) are proposed. Aiming at maximizing system profit, the capacity of electrolyzers and fuel cells are constrained by wind power fluctuation, and considering environmental benefits, government subsidies and time value of funds, the objective function and its constraints are established. According to the simulation analysis, by comparing the calculated results with PSO and CROA, it shows that PSO-CROA effectively evaluates the economy of the system, and optimizes the optimal capacity of the electrolyzers and fuel cells. The conclusion of this paper is of great significance for the application of hydrogen energy storage in the evaluation of power smoothness and economy of renewable energy grid connection and the calculation of economic allocation of hydrogen energy storage capacity.     

基于动态运行策略的太阳能分布式供能系统设计运行联合优化

提出将光伏剩余电量按照可变比例分配给储能电池及市政电网的动态运行策略,建立基于该策略的并网太阳能分布式供能系统设计运行联合优化模型,在不同分时电价下基于遗传算法对模型寻优,并将动态运行策略与对照运行策略（剩余电量优先并网或优先分配储能电池）下的系统运行结果进行比较分析。以陕西某乡村典型民居建筑为例进行分析,结果表明：1）分时电价的峰谷价差较大时,动态运行策略可有效降低太阳能分布式供能系统成本;2）分时电价的峰谷价差对于动态运行策略下储能电池的容量配置具有较大影响：峰谷价差越大,储能电池的配置容量越大;3）光伏度电补贴对3种运行策略下的系统成本影响程度为：动态运行策略>策略B（剩余电量优先分配储能电池）>策略A（剩余电量优先并网）。     

Optimal operational strategy for a future electricity and hydrogen supply system in a residential area

This study introduces a novel framework of an electricity and hydrogen supply system integrating with a photovoltaic power station for a residential area. The non-residential parts including the power grid and non-residential vehicles are added to ensure power balance and bring benefits, respectively. The optimal operational strategy of the proposed framework with considering uncertainties is proposed. The objective function minimizes the expected operational cost (EOC) by reducing the imported electricity from the power grid and increasing exported electricity/hydrogen to non-residential vehicles. Additionally, the demand response program (DRP) is applied in the residential load to achieve operational cost reduction. The uncertainties are modeled via various scenarios by using scenario-based stochastic optimization method. Notably, existing research for similar frameworks both lacks the consideration of uncertainties and DRP, and fails to distinguish the residential and non-residential vehicles with different charging behaviors. The results indicate that 1) The feasibility of the proposed framework is validated which can ensure the power balance of the residential area and reduce the operational cost. 2) The EOC is reduced when considering DRP.     

Economic optimization and sensitivity analysis of photovoltaic system in residential buildings

This paper deals with the problem of optimal size of grid-connected photovoltaic (PV) system for residential application. It is assumed the PV system can input or output liberally the electricity to the utility electricity grid. A simple linear programming model is developed. The objective is to minimize the annual energy cost of a given customer, including PV investment cost, maintenance cost, utility electricity cost, subtracting the revenue from selling the excess electricity. The model reports the optimal PV capacity that customers adopt with their electricity requirements. Using this model, an investigation is conducted of economically optimal PV investment under several conditions for a typical residential building. Additionally, the sensitivity of levelized cost and simple payback period to various economic and technical circumstances has been analyzed.     

Study on optimal configuration of the grid-connected wind–solar–battery hybrid power system

The capacity allocation of each energy unit in the grid-connected wind–solar–battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind–solar–battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind–solar–battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.     

Assessment of hydrogen as a potential energy storage for urban areas’ PV-assisted energy systems - Case study

The world is experiencing unprecedented development in the clean energy sector in residential and industrial applications. This paper provides a case study assessing different scenarios of greenizing the electrical energy demand in El-Mostakbal city in Egypt. Three scenarios are studied with consideration of a photovoltaic (PV) system integrated with the grid-connected city with different integrated system configurations. The scenarios for the grid-connected city are scenario-I: only PV, scenario-II: PV with batteries for electricity storage along with grid electricity, and scenario-III: PV with hydrogen production, storage, and utilization for covering the electric demand along with grid electricity, these scenarios are assessed technoeconomically, and the results show an optimized case where the electricity demand of the city can be met with 64.3% produced from solar energy, at $71.7 M of the net present cost.     

Optimal operation of DC smart house system by controllable loads based on smart grid topology

From the perspective of global warming mitigation and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all-electric apartment houses or residence such as DC smart houses are increasing. However, due to the fluctuating power from renewable energy sources and loads, supply-demand balancing of power system becomes problematic. Smart grid is a solution to this problem. This paper presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuation. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuation, it is possible to reduce the electric power consumption and the cost of electricity. This system consists of photovoltaic generator, heat pump, battery, solar collector, and load. To verify the effectiveness of the proposed system, results are used in simulation presented.     

Modeling,control and simulation of a photovoltaic /hydrogen/ supercapacitor hybrid power generation system for grid-connected applications

Hybrid renewable energy systems (HRES) should be designed appropriately with an adequate combination of different renewable sources and various energy storage methods to overcome the problem of intermittency of renewable energy resources. Focusing on the inevitable impact on the grid caused by strong randomicity and apparent intermittency of photovoltaic (PV) generation system, modeling and control strategy of pure green and grid-friendly hybrid power generation system based on hydrogen energy storage and supercapacitor (SC) is proposed in this paper. Aiming at smoothing grid-connected power fluctuations of PV and meeting load demand, the alkaline electrolyzer (AE) and proton exchange membrane fuel cell (PEMFC) and SC are connected to DC bus of photovoltaic grid-connected generation system. Through coordinated control and power management of PV, AE, PEMFC and SC, hybrid power generation system friendliness and active grid-connection are realized. The validity and correctness of modeling and control strategies referred in this paper are verified through simulation results based on PSCAD/EMTDC software platform.     

Photovoltaic grid stabilization system using second life lithium battery

The operation of residential solar photovoltaic arrays are typically dependent on net energy metering (NEM) tariffs or feed in tariffs that allow the array owner to treat the electricity grid as an energy storage device. This study presents a model and simulation results of a photovoltaic array paired with a second life battery pack, a partially degraded lithium battery pack from an automotive application, for stabilizing the electricity grid interactions of residential photovoltaic systems and reducing the overall residential demand placed on the electricity grid. Two numerical simulations are performed on the operation of a second life battery pack. The first used an equivalent system model for the battery pack and measured solar production and residential loads to evaluate the system performance using one second time steps. The second model used hourly time steps and round trip efficiency for the battery, coupled with weather data and residential demand, to determine the system performance over the course of a year. The numerical investigation shows that the PV and battery system can substantially reduce the quantity of solar electricity that is exported to the distribution grid and decrease the impacts of sudden fluctuations in photovoltaic output due to cloud cover while providing significant reductions in the electricity demand placed on the grid. Copyright © 2015 John Wiley & Sons, Ltd.     

Hydrogen fuel as an important element of the energy storage needs for future smart cities

A considerable amount of non-dispatchable photovoltaic and wind power have always been planned in smart cities, however, the problem of massive energy storage has not yet been solved which limits the use of green energy on larger scale. At present the only battery energy storage is available, and it is effective only for storing modest quantities of energy for short periods of time. The other storage technology options are not often commercially available items; rather, they are just good concepts that need to be tested for viability. Currently, the only alternative options for turning an urban development into one that exclusively uses green energy is to use that energy to generate hydrogen through electrolyzers, then use this fuel to generate the required electricity in order to stabilize the grid. Even more appealing is the idea of using wind and photovoltaic energy to transform smart communities into a centre for producing hydrogen in addition to a city that solely uses renewable energy. The most likely solution, absent an urgent debate inside the science establishment, will be to import electricity from the burning of hydrocarbons while continuing to pay carbon offsets, which is incompatible with the goal of using only renewables. The smart city has not officially accepted this issue, just like the science establishment.     

Analysis of wind power generation operation management risk in China

The Chinese government has made an important effort to diversify the country's energy mix and exploit different sources of renewable energy. Although China's installed wind power capacity has undergone a dramatic expansion over the past six years, the electricity generated from wind power has not increased as expected. Meanwhile, operational risks, such as high generation cost, mismatch between capacity and generation, intermittent wind power generation, power grid construction lag, deficient policy, and operation mechanism, have become increasingly prominent. If not controlled, these risks will negatively affect wind power development in China. Therefore, this paper established a quantitative analysis model of wind power operation management risk from two aspects, feed-in tariff and grid electricity (electricity being connected to the grid), based on an analysis of wind power operation management risk in China. Moreover, this study quantitatively assessed the risk of the operational management of a wind farm in Inner Mongolia. Finally, corresponding risk control strategies for the healthy development of wind power generation in China were proposed.     

Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices

Compressed air energy storage (CAES) technologies can be used for load levelling in the electricity supply and are therefore often considered for future energy systems with a high share of fluctuating renewable energy sources, such as e.g. wind power. In such systems, CAES plants will often operate on electricity spot markets by storing energy when electricity prices are low and producing electricity when prices are high. In order to make a profit on such markets, CAES plant operators have to identify proper strategies to decide when to sell and when to buy electricity. This paper describes three independent computer-based methodologies which may be used for identifying the optimal operation strategy for a given CAES plant, on a given spot market and in a given year. The optimal strategy is identified as the one which provides the best business-economic net earnings for the plant. In practice, CAES plants will not be able to achieve such optimal operation, since the fluctuations of spot market prices in the coming hours and days are not known. Consequently, two simple practical strategies have been identified and compared to the results of the optimal strategy. This comparison shows that, in practice, a CAES plant can be expected to earn 80-90 per cent of the optimal earnings.     

Optimal configuration for photovoltaic storage system capacity in 5G base station microgrids

Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations. In this study, the idle space of the base station’s energy storage is used to stabilize the photovoltaic output, and a photovoltaic storage system microgrid of a 5G base station is constructed. Aiming at the capacity planning problem of photovoltaic storage systems, a two-layer optimal configuration method is proposed. The inner layer optimization considers the energy sharing among the base station microgrids, combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery, and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid. The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid, while considering peak clipping and valley filling, to optimize the photovoltaic storage system capacity. The CPLEX solver and a genetic algorithm were used to solve the two-layer models. Considering the construction of the 5G base station in a certain area as an example, the results showed that the proposed model can not only reduce the cost of the 5G base station operators, but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.     

A market‐oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage

In this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid‐tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time‐varying market‐price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market‐price data, depict the proficiency of the proposed methodology over standard linear programming methods.     

Optimizing hydrogen production capacity and day ahead market bidding for a wind farm in Texas

Producing green hydrogen from wind energy is one potential method to mitigate curtailment. This study develops a general approach to examine the economic benefit of adding hydrogen production capacity through water electrolysis along with the fuel cell and storage facilities in a wind farm in north Texas. The study also investigates different day ahead market bidding strategies in the existence of these technologies. The results show that adding hydrogen capacity to the wind farm is profitable when hydrogen price is greater than $3.58/kg, and that the optimal day ahead market bidding strategy changes as hydrogen price changes. The results also suggest that both the addition of a fuel cell to reconvert stored hydrogen to electricity and the addition of a battery to smooth the electricity input to the electrolyzer are suboptimal for the system in the case of this study. The profit of a particular bidding scenario is most sensitive to the selling price of hydrogen, and then the input parameters of the electrolyzer. This study also provides policy implications by investigating the impact of different policy schemes on the optimal hydrogen production level.     

A power allocation strategy of a hybrid energy storage system for a PV grid-connected system

针对光伏并网系统中光伏微电源出力的波动性和间歇性,将蓄电池和超级电容器构成的混合储能系统HESS（hybrid energy storage system）应用到光伏并网系统中可以实现光伏功率平滑、能量平衡以及提高并网电能质量。在同时考虑蓄电池的功率上限和超级电容的荷电状态（SOC）的情况下,对混合储能系统提出了基于超级电容SOC的功率分配策略;该策略以超级电容的SOC和功率分配单元的输出功率作为参考值,对混合储能系统充放电过程进行设计。超级电容和蓄电池以Bi-direction DC/DC变换器与500 V直流母线连接,其中超级电容通过双闭环控制策略对直流母线电压进行控制。仿真结果表明,所提功率分配策略能对混合储能系统功率合理分配,而且实现了单位功率因数并网,稳定了直流母线电压。