Discrete harmony search based size optimization of Integrated Renewable Energy System for remote rural areas of Uttarakhand state in India

In the recent years, decentralized power generation using locally available renewable energy resources has been recognized as a cost effective alternative of uneconomical grid extension. The present paper deals with the size optimization of Integrated Renewable Energy System (IRES) for a cluster of villages of Uttarakhand state in India. The proposed IRES consists of locally available renewable energy resources of Micro Hydro Power (MHP), biogas, biomass, wind and solar energy in order to meet the electrical and cooking demands of the study area. A system operation strategy has been developed in the paper for size optimization of IRES. Also, the loss of power supply probability (LPSP) has been used as the reliability criteria in order to ensure the continuous supply of power without any failure problems. Further, in order to utilize renewable energy resources in different contributions, four different resource scenarios are considered for the study area. Finally, the total net present cost (NPC) of the considered scenarios has been optimized using discrete harmony search (DHS) algorithm. Among different scenarios, MHP-biogas-biomass-wind-solar-battery based IRES offers the lowest net present cost of INR 49.0309 million at the estimated LCOE of INR 5.47/kWh.     

A novel methodology for scrutiny of autonomous hybrid renewable energy system

The optimal design of a hybrid system with different configurations including renewable generation is presented in this paper. A novel multi‐objective function consisting of 6 different objectives of hybrid system is reported using GA, PSO, and TLBO to decide the optimal configurations of parameters. The technical (loss of power supply probability, renewable factor), economical (cost of energy, penalty and fuel consumption), and social (job creation, human development index, and particular matter) features are investigated as objectives simultaneously for optimal design of hybrid system. The different objective indices namely cost of energy, loss of power supply probability, particular matter, human development index, job creation, and renewable factor indices are considered. The newly invented particular matter factor for design consideration of hybrid system directly shows the human health impacts, while pollutant emission is measured in the hybrid system design. The optimum values of objective indices are decided on the basis of the minimum value of multi‐objective function. The distinct cases from I to VI of hybrid system are examined for optimal configuration including different combinations of PV, wind, biomass, diesel generator, and battery bank. The resulting analysis of each case reveals that the performance of TLBO is better than PSO, and PSO is better than GA in all respect through new multi‐objective function and found case I is more efficient solution.     

Minimizing the energy cost for microgrids integrated with renewable energy resources and conventional generation using controlled battery energy storage

This paper presents a methodology to minimize the total cost of buying power from different energy producers including renewable energy generations particularly within the context of a microgrid. The proposed idea is primarily based on the controlled operation of a battery energy storage system (BESS) in the presence of practical system constraints coupled with our proposed cost optimization algorithm. The complex optimization problem with constraints has been solved using the well-known concept of dynamic programming. The methodology has been assessed using actual power and price data from six different power generation sites and cost reduction has been calculated for a number of BESSs by varying their energy and power capacities. Twofold benefits of the proposed methodology lie in minimizing the total cost along with the constraint-based efficient operation of the BESS. Simulation results depict that the given power demand at a particular region can be fulfilled properly at all times using a BESS and multiple power generation.     

Sustainable energy system design with distributed renewable resources considering economic,environmental and uncertainty aspects

Electricity generation using renewable energy generation technologies is one of the most practical alternatives for network planners in order to achieve national and international Greenhouse Gas (GHG) emission reduction targets. Renewable Distributed Generation (DG) based Hybrid Energy System (HES) is a sustainable solution for serving electricity demand with reduced GHG emissions. A multi-objective optimisation technique for minimising cost, GHG emissions and generation uncertainty has been proposed in this paper to design HES for sustainable power generation and distribution system planning while considering economic and environmental issues and uncertainty in power availability of renewable resources. Life cycle assessment has been carried out to estimate the global warming potential of the embodied GHG emissions from the electricity generation technologies. The uncertainty in the availability of renewable resources is modelled using the method of moments. A design procedure for building sustainable HES has been presented and the sensitivity analysis is conducted for determining the optimal solution set.     

Wind energy in Vietnam: Resource assessment,development status and future implications

The aim of this study is to estimate the technical potential of wind energy in Vietnam and discuss strategies for promoting the market penetration of wind energy in the country. For the wind resource assessment, a geographical information system (GIS)- assisted approach has been developed. It is found that Vietnam has a good potential for wind energy. About 31,000 km² of land area can be available for wind development in which 865 km² equivalents to a wind power of 3572 MW has a generation cost less than 6 US cents/kWh. The study also proves that wind energy could be a good solution for about 300,000 rural non-electrified households. While wind energy brings about ecological, economic and social benefits, it is only modestly exploited in Vietnam, where the main barrier is the lack of political impetus and a proper framework for promoting renewable energy. The priority task therefore is to set a target for renewable energy development and to find instruments to achieve such a target. The main instruments proposed here are setting feed-in tariff and providing investment incentives.     

Economical evaluation of electricity generation considering externalities

The economics of renewable energy are the largest barrier to renewable penetration. Nevertheless, the strong desire to reduce environmental emissions is considered a great support for renewable energy sources. In this paper, a full analysis for the cost of the kWh of electricity generated from different systems actually used in Egypt is presented. Also renewable energy systems are proposed and their costs are analyzed. The analysis considers the external cost of emissions from different generating systems. A proposed large scale PV plant of 3.3 MW, and a wind farm 11.25 MW grid connected at different sites are investigated. A life cycle cost analysis for each system was performed using the present value criterion. The comparison results showed that wind energy generation has the lowest cost, followed by a combined cycle–natural gas fired system. A photovoltaic system still uses comparatively expensive technology for electricity generation; even when external costs are considered the capital cost of photovoltaic needs to be reduced by about 60% in order to be economically competitive.     

Power sector development in India with CO2 emission targets: Effects of regional grid integration and the role of clean technologies

The power sector in India at present comprises of five separate regional electricity grids having practically no integrated operation in between them. This study analyses the utility planning, environmental and economical effects of integrated power sector development at the national level in which the regional electric grids are developed and operated as one integrated system. It also examines the effects of selected CO₂ emission reduction targets in the power sector and the role of renewable power generation technologies in India. The study shows that the integrated development and operation of the power system at the national level would reduce the total cost including fuel cost by 4912 million $, total capacity addition by 2784 MW, while the emission of CO₂, SO₂ and NO_x would be reduced by 231.6 (1.9%), 0.8 (0.9%), 0.4 (1.2%) million tons, respectively, during the planning horizon. Furthermore, the study shows that the expected unserved energy, one of the indices of generation system reliability, would decrease to 26 GWh under integrated national power system from 5158 GWh. As different levels of CO₂ emission reduction targets were imposed, there is a switching of generation from conventional coal plants to gas fired plants, clean coal technologies and nuclear based plants. As a result the capacity expansion cost has increased. It was found that wind power plant is most attractive and economical in the Indian perspective among the renewable options considered (Solar, wind and biomass). Copyright © 2003 John Wiley & Sons, Ltd.     

计及不确定性的多类型发电机组联合调度优化模型

为了促进可再生能源并网,解决可再生能源机组在内的多类型发电机组联合优化调度问题,引入全额收购可再生能源发电,由火电机组提供备用、允许适度弃风,由火电机组提供备用以及水火机组联合提供备用的可再生能源发电三种不同方案。首先构建了涵盖风、光伏、水力机组的可再生能源机组发电处理模型;再结合设定的三种方案组建了多类型发电机组节能调度优化模型;最后,基于基础数据,得出该节能调度优化模型的发电系统总煤耗、备用煤耗、系统发电成本、启停成本、弃风量及弃水量等关键指标的优化效果,对多类型发电机组联合调度优化具有一定的指导意义。     

Spanish energy roadmap to 2020: Socioeconomic implications of renewable targets

The European Union has established challenging targets for the share of renewable energies to be achieved by 2020; for Spain, 20% of the final energy consumption must be from renewable sources at such time. The aim of this paper is the analysis of the consequences for the electricity sector (in terms of excess cost of electricity, investment requirements, land occupation, CO₂ emissions and overcapacity of conventional power) of several possibilities to comply with the desired targets. Scenarios are created from different hypotheses for energy demand, biofuel share in final energy in transport, contribution of renewables for heating and cooling, renewable electricity generation (generation mix, deployment rate, learning curves, land availability) and conventional power generation (lifetime of current installations, committed deployment, fossil fuel costs and CO₂ emissions cost). A key input in the estimations presented is the technical potential and the cost of electricity from renewable sources, which have been estimated in previous, detailed studies by the present authors using a methodology based on a GIS (Geographical Information System) and high resolution meteorological data. Depending on the scenario, the attainment of the targets will lead to an increase in the cost of electricity from 19% to 37% with respect to 2007.     

储能对可再生能源并网发电的支撑作用

可再生能源发电并网对于电力系统的节能减排具有关键作用,选择合理的储能容量,并分析储能对可再生能源并网发电的支撑作用具有重要意义。从节能减排和供电可靠性角度建立具有储能装置的单母线电力系统和剩余电力系统的随机规划模型,并通过蒙特卡罗模拟算法对国外某地区的风力发电和储能联合运行系统进行模拟分析。结果表明,适度规模的储能容量不仅能有效解决可再生能源发电的功率波动问题、减小系统停电损失概率,而且能够降低系统的环境成本,但其减少程度与储能的全过程效率有关。     

Energy‐cost‐aware flow shop scheduling considering intermittent renewables,energy storage,and real‐time electricity pricing

The industrial sector is one of the major energy consumers that contribute to global climate change. Demand response programs and on‐site renewable energy provide great opportunities for the industrial sector to both go green and lower production costs. In this paper, a 2‐stage stochastic flow shop scheduling problem is proposed to minimize the total electricity purchase cost. The energy demand of the designed manufacturing system is met by on‐site renewables, energy storage, as well as the supply from the power grid. The volatile price, such as day‐ahead and real‐time pricing, applies to the portion supplied by the power grid. The first stage of the formulated model determines optimal job schedules and minimizes day‐ahead purchase commitment cost that considers forecasted renewable generation. The volatility of the real‐time electricity price and the variability of renewable generation are considered in the second stage of the model to compensate for errors of the forecasted renewable supply; the model will also minimize the total cost of real‐time electricity supplied by the real‐time pricing market and maximize the total profit of renewable fed into the grid. Case study results show that cost savings because of on‐site renewables are significant. Seasonal cost saving differences are also observed. The cost saving in summer is higher than that in winter with solar and wind supply in the system. Although the battery system also contributes to the cost saving, its effect is not as significant as the renewables.     

Research on optimal confguration of hybrid energy storage capacity for wind-solar generation system

储能系统可以有效解决微电网中分布式可再生能源特别是风光互补发电的间歇性、波动性以及“源”与“荷”错位的问题。不同储能技术在响应时间、容量规模、技术成熟度及成本等方面各有特点,两种或多种储能技术耦合将可以更有效地满足用电系统的技术性和经济性的要求。针对电力用户对分布式可再生能源的利用情况,本文提出一种由压缩空气储能、锂电池和超级电容器组成的混合储能系统,建立了三种储能的数学模型,针对其不同的特性,提出了基于二次移动平均滤波的储能系统功率分配方法和基于连续性运行的容量优化配置方法。基于某个实际的用户负荷进行了案例分析,得到了混合储能系统的功率和容量配置结果,并分析了其运行特性。研究表明,在分布式可再生能源微电网中,多种储能技术耦合既能充分发挥每种储能的优势,又可以通过相互配合弥补各自的劣势,这对于可再生能源的充分利用和满足用电负荷的严苛需求具有重要的作用和意义,在分布式能源利用领域具有较好的工程应用前景。     

计及环境效益的虚拟电厂经济性优化调度

虚拟电厂（Virtual power plant, VPP）能有效减小新能源对电网的冲击,提高供电可靠性。本文在分析了VPP各分布式电源（Distributed generator, DG）发电成本的基础上,构建了计及环境效益的含风力发电、光伏发电、小水电和微型燃气轮机发电的VPP经济性优化调度模型,设计了基于小水电季节特性的VPP运行策略。以各时段内VPP实际出力跟踪计划出力、同时VPP发电成本和环境成本最小为目标,通过粒子群算法计算得到VPP各DG的出力。讨论了丰水期、平水期和枯水期VPP完成计划出力时微型燃气轮机出力系数,比较了丰水期、平水期和枯水期VPP发电成本和环境成本,并基于火力发电的环境成本计算了丰水期、平水期和枯水期VPP环境效益。实验结果验证了所建模型和运行策略的合理性,并表明VPP能有效平抑新能源出力偏差,降低DG发电总成本。     

Levelized cost of electricity (LCOE) of renewable energies and required subsidies in China

The development and utilization of renewable energy (RE), a strategic choice for energy structural adjustment, is an important measure of carbon emissions reduction in China. High cost is a main restriction element for large-scale development of RE, and accurate cost estimation of renewable power generation is urgently necessary. This is the first systemic study on the levelized cost of electricity (LCOE) of RE in China. Results indicate that feed-in-tariff (FIT) of RE should be improved and dynamically adjusted based on the LCOE to provide a better support of the development of RE. The current FIT in China can only cover the LCOE of wind (onshore) and solar photovoltaic energy (PV) at a discount rate of 5%. Subsidies to renewables-based electricity generation, except biomass energy, still need to be increased at higher discount rates. Main conclusions are drawn as follows: (1) Government policy should focus on solving the financing problem of RE projects because fixed capital investment exerts considerable influence over the LCOE; and (2) the problem of high cost could be solved by providing subsidies in the short term and more importantly, by reforming electricity price in the mid-and long-term to make the RE competitive.     

Optimal utilization of renewable energy-based IPPs for industrial load management

Share of power generation from renewable energy sources has been steadily increasing all over the world, mainly due to the concern about clean environment. Cost of renewable power generation has reduced considerably during the last two decades due to technological advancements and at present some of the renewable energy sources can generate power at costs comparable with that of fossil fuels. In this paper, application of renewable energy-based power generation is proposed, for load management. The formulation utilizes non-linear programming technique for minimizing the electricity cost and reducing the peak demand, by supplementing power by renewable energy sources, satisfying the system constraints. Case study of twenty-two large-scale industries showed that, significant reduction in peak demand (about 34%) and electricity cost (about 14%) can be achieved, by the optimal utilization of the renewable energy from independent power producers (IPPs).     

Economic viability and production capacity of wind generated renewable hydrogen

Generally, wind to power conversion is calculated by assuming the quality of wind as measured with a Weibull probability distribution at wind speed during power generation. We build on this method by modifying the Weibull distributions to reflect the actual range of wind speeds and wind energy density. This was combined with log law that modifies wind speed based on the height from the ground, to derive the wind power potential at windy sites. The study also provides the Levelized cost of renewable energy and hydrogen conversion capacity at the proposed sites. We have also electrolyzed the wind-generated electricity to measure the production capacity of renewable hydrogen. We found that all the sites considered are commercially viable for hydrogen production from wind-generated electricity. Wind generated electricity cost varies from $0.0844 to $0.0864 kW h, and the supply cost of renewable hydrogen is $5.30 to $ 5.80/kg-H₂. Based on the findings, we propose a policy on renewable hydrogen fueled vehicles so that the consumption of fossil fuels could be reduced. This paper shall serve as a complete feasibility study on renewable hydrogen production and utilization.     

Is the concept of ‘grid parity’ defined appropriately to evaluate the cost-competitiveness of renewable energy technologies?

The concept of ‘grid parity’ has emerged as a key indicator of the competitiveness of renewable electricity generation technologies. In this study, we firstly summarize the definition of the current levelized cost of electricity (LCOE) based methodology for the concept and address its limitation in not taking into account the systematic changes in an electric power system. Secondly, we introduce a bottom-up energy system model based methodology to overcome the limitation. Lastly, we apply the methodology to a case study, the grid parity analysis of solar photovoltaic and onshore wind technologies in the Korean electric power system, to highlight the differences between the results obtained using both methodologies. The results of the study show three implications. First, even if the LCOE of onshore wind is already lower than that of natural gas technologies and the average price of grid electricity, the LCOE is required to be much lower to achieve cost-competitiveness in the electric power system. Second, different technologies might be required to have different LCOE levels to be cost-competitive in the same power system. Third, a policy or plan for the deployment of renewable energy technologies must be harmonized with other policies and plans within the same system.     

日本是否会放弃核能——日本能源政策走向分析

能源作为日本震后经济社会发展的中长期政策大纲《日本再生基本战略》的主要支柱之一,日本能源政策的走向尤为值得关注.从短期看,日本将加大核能监管,继续扩大核电制造出口,完全弃核是不可能的;从长期看,日本会逐步降低核能在能源结构中的比例.由于核电的关停,造成日本电力供应不足,进而导致对火力发电政策的支持力度增强,未来对化石能源的依赖局面仍将持续.同时,由于核能政策的调整,一方面使得节能及提高能源使用效率成为新的支柱,另一方面可再生能源将成为重要的发展方向.近10年来,日本可再生能源占能源结构的比例一直没什么变化,约为10％,这与日本政府支持核能战略的政策导向不无关系.日本当前发展可再生能源的主要障碍是缺乏政府的长期政策扶持,其次是开发难度大、发电成本高、系统稳定性低.日本目前需要解决的课题包括全量购买制度等相关政策的导入,大幅度降低成本和解决稳定性关键技术,有效解决可再生能源利用的地域化差异等.总的来看,日本新的能源政策基本是围绕减少对核电的依赖和应对全球气候变暖来制定的.     

Online and batch methods for solar radiation forecast under asymmetric cost functions

In electric power grids, generation must equal load at all times. Since wind and solar power are intermittent, system operators must predict renewable generation and allocate operating reserves to mitigate imbalances. If they overestimate the renewable generation during scheduling, insufficient generation will be available during operation, which can be very costly. However, if they underestimate the renewable generation, usually they will only face the cost of keeping some generation capacity online and idle. Therefore overestimation of renewable generation resources usually presents a more serious problem than underestimation. Many researchers train their solar radiation forecast algorithms using symmetric criteria like RMSE or MAE, and then a bias is applied to the forecast later to reflect the asymmetric cost faced by the system operator – a technique we call indirectly biased forecasting. We investigate solar radiation forecasts using asymmetric cost functions (convex piecewise linear (CPWL) and LinEx) and optimize directly in the forecast training stage. We use linear programming and a gradient descent algorithm to find a directly biased solution and compare it with the best indirectly biased solution. We also modify the LMS algorithm according to the cost functions to create an online forecast method. Simulation results show substantial cost savings using these methods.     

The assessment of renewable energy planning on CO2 abatement in South Korea

Sources of renewable energies (for example landfill gas, wind, solar energy) are environmentally friendly and electric power generation in South Korea has concentrated on new and renewable energy technologies. The purpose of this paper is to study the economic and environmental influence of renewable energies on existing electricity generation market of South Korea with energy-economic model called ‘Long-range Energy Alternative Planning system’ and the associated ‘Technology and Environmental Database’. Business as usual scenario was based on energy supply planning with existing power plant. And then, the alternative scenarios were considered, namely the base case with existing electricity facilities, the installation plan of different renewable energy facilities, technological improvement and process dispatch rule according to merit order change. In each alternative scenario analysis, alternation trend of existing electricity generation facilities is analyzed and the cost of installed renewable energy plants and CO₂ reduction potential was assessed quantitatively.