Sizing of integrated renewable energy system based on load profiles and reliability index for the state of Uttarakhand in India

In recent years the decentralized rural electrification is becoming cost effective and convenient for areas where grid extension is very difficult. The present paper deals with the electrification of dense forest areas of Uttarakhand state in India by Integrated Renewable Energy Optimization Model (IREOM). The IREOM consists of locally available renewable energy resources such as Micro-Hydropower (MHP), biomass, biogas, wind and solar photovoltaic (SPV) systems have been used to meet electrical energy and cooking energy needs of a cluster of villages. The paper includes the selection of different system components, sizing and development of a general model to find out optimal combination of energy subsystems for the selected study area in order to minimize the cost of energy (COE) generation for a required reliability values. The sizing of different renewable energy system components has been carried out so that they are suitable for four different seasonal load profiles. The two reliability values are considered for the selection of optimum solution of year round application. The model developed for this purpose, has been found to be quite useful in optimizing the renewable energy system sizes that are available in market. The proposed model totally depends on the renewable energy systems and eliminates the use of conventional energy systems.     

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

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

Combining simulation techniques and design expertise in a renewable energy system design package, RESSAD

Computer simulation is an increasingly popular tool for determining the most suitable renewable energy system type, design and control for an isolated community or homestead. However for the user without any expertise in system design, the complicated process of system component and control selection using computer simulation takes on a trial and error approach. Our renewable energy system design package, RESSAD, has been developed to simulate a wide range of renewable power supply systems, and to go beyond system simulation, by combining design expertise with the simulation model. The knowledge of the system designer is incorporated into the package through a range of analysis tools that assist in the selection process, without removing or restricting individual choices. The system selection process is analysed from the early stages of renewable resource assessment to the final evaluation of the results from a simulation of the chosen system. The approach of the RESSAD package in this selection process is described and its use is illustrated by two case studies in Western Australia.     

Hydrogen as an energy carrier in stand-alone applications based on PV and PV–micro-hydro systems

The paper compares two different models of a hypothetical stand-alone energy system based only on renewable sources (solar irradiance and micro-hydro power) integrated with a system for the production of hydrogen (electrolyzer, compressed gas storage and proton exchange membrane fuel cell or PEMFC). The models of both systems have been designed to supply the electricity needs of a residential user in a remote area (a valley of the Alps in Italy) during a complete year of operation, without integration of traditional fossil fuel energy devices. A simulation model has been developed to analyze the energy performance of these systems. The technical feasibility and the behavior of the systems will be evaluated through the analysis of some data (e.g. the production and consumption of electricity along the year by the different components; the heat management; the production, storage and utilization of hydrogen).     

A novel hybrid isolated generating system based on PV fed inverter-assisted wind-driven induction Generators

Isolated renewable energy systems based on hybrid wind-solar sources are considered as feasible and reliable options instead of wind-diesel systems. An isolated hybrid scheme employing a simple three-phase square-wave inverter to integrate a photovoltaic array with a wind-driven induction generator has been proposed for the first time. A dynamic mathematical model of the hybrid scheme with variables expressed in d-q synchronous reference frame has been developed. The model is implemented in the power system blockset platform and a comparison has been made between transients simulated and transients obtained in an experimental prototype. Close agreement between experimental and the simulated waveforms has been observed, which validates the model.     

Prospects of renewable energy - a feasibility study in the Australian context

Given the recent increasing public focus on climate change issues, there is a need for robust, sustainable and climate friendly power transmission and distribution systems that are intelligent, reliable, and green. Current power systems create environmental impacts as well as contributing to global warming due to their utilization of fossil fuels, especially coal, as carbon dioxide is emitted into the atmosphere. In contrast to fossil fuels, renewable energy is starting to be used as the panacea for solving climate change or global warming problems. This paper describes a feasibility study undertaken to investigate the potentialities of renewable energy including the prospective locations in Australia for renewable energy generation, in particular solar and wind energy. Initially, a hybrid model has been developed to investigate the prospects of wind energy for typical Australian region considering production cost, cost of energy, emission production and contribution from renewable energy using the Hybrid Optimization Model for Electric Renewable (HOMER), a computer model developed by the USA’s National Renewable Energy Laboratory (NREL). This model also explores suitable places around Australia for wind energy generation using statistical analysis. Subsequently, the usefulness of solar energy in the Australian context and suitable locations for solar energy generation are also investigated using a similar hybrid model. Finally, the model has been developed to investigate the prospects of renewable energy in particular wind and solar energy including specific locations in Australia that would be suitable for both wind and solar energy generation. From simulation analysis it is clearly observed that Australia has enormous potentialities for substantially increased use of renewable energy; a large penetration of renewable energy sources into the national power system would reduce CO₂ emissions significantly, contributing to the reduction of global warming.     

Planning of community-scale renewable energy management systems in a mixed stochastic and fuzzy environment

In this study, an interval-parameter superiority–inferiority-based two-stage programming model has been developed for supporting community-scale renewable energy management (ISITSP-CREM). This method is based on an integration of the existing interval linear programming (ILP), two-stage programming (TSP) and superiority–inferiority-based fuzzy-stochastic programming (SI-FSP). It allows uncertainties presented as both probability/possibilistic distributions and interval values to be incorporated within a general optimization framework, facilitating the reflection of multiple uncertainties and complexities during the process of renewable energy management systems planning. ISITSP-CREM can also be used for effectively addressing dynamic interrelationships between renewable energy availabilities, economic penalties and electricity-generation deficiencies within a community scale. Thus, complexities in renewable energy management systems can be systematically reflected, highly enhancing applicability of the modeling process. The developed method has then been applied to a case of long-term renewable energy management planning for three communities. Useful solutions for the planning of renewable energy management systems have been generated. Interval solutions associated with different energy availabilities and economic penalties have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired energy resource/service allocation plans with a minimized system cost (or economic penalties), a maximized system reliability level and a maximized energy security. Tradeoffs between system costs and energy security can also be tackled. Higher costs will increase potential energy generation amount, while a desire for lower system costs will run into a risk of energy deficiency. They are helpful for supporting: (a) adjustment or justification of allocation patterns of renewable energy resources and services, (b) formulation of local policies regarding energy utilization, economic development and energy structure under various energy availabilities and policy interventions, and (c) analysis of interactions among economic cost, system reliability and energy-supply shortage.     

Effect of wind energy system performance on optimal renewable energy model-an analysis

The Optimal Renewable Energy Model (OREM) has been developed to determine the optimum level of renewable energy sources utilisation in India for the year 2020–21. The model aims at minimising costefficiency ratio and determines the optimum allocation of different renewable energy sources for various end-uses. The extent of social acceptance level, potential limit, demand and reliability will decide the renewable energy distribution pattern and are hence used as constraints in the model. In this paper, the performance and reliability of wind energy system and its effects on OREM model has been analysed. The demonstration windfarm (4 MW) which is situated in Muppandal, a village in the southern part of India, has been selected for the study. The windfarm has 20 wind turbine machines of 200 KW capacity. The average technical availability, real availability and capacity factor have been analysed from 1991 to 1995 and they are found to be 94.1%, 76.4% and 25.5% respectively. The reliability factor of wind energy system is found to be 0.5 at 10,000 hours. The OREM model is analysed considering the above said factors for wind energy system, solar energy system and biomass energy systems. The model selects wind energy for pumping end-use to an extent of 0.3153×10¹⁵ KJ.     

Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach

Recently, the increasing energy demand has caused dramatic consumption of fossil fuels and unavoidable raising energy prices. Moreover, environmental effect of fossil fuel led to the need of using renewable energy (RE) to meet the rising energy demand. Unpredictability and the high cost of the renewable energy technologies are the main challenges of renewable energy usage. In this context, the integration of renewable energy sources to meet the energy demand of a given area is a promising scenario to overcome the RE challenges. In this study, a novel approach is proposed for optimal design of hybrid renewable energy systems (HRES) including various generators and storage devices. The ε-constraint method has been applied to minimize simultaneously the total cost of the system, unmet load, and fuel emission. A particle swarm optimization (PSO)-simulation based approach has been used to tackle the multi-objective optimization problem. The proposed approach has been tested on a case study of an HRES system that includes wind turbine, photovoltaic (PV) panels, diesel generator, batteries, fuel cell (FC), electrolyzer and hydrogen tank. Finally, a sensitivity analysis study is performed to study the sensibility of different parameters to the developed model.     

Two energy system analysis models: A comparison of methodologies and results

This paper presents a comparative study of two energy system analysis models both designed for the purpose of analysing electricity systems with a substantial share of fluctuating renewable energy. The first model (EnergyPLAN) has been designed for national and regional analyses. It has been used in the design of strategies for integration of wind power and other fluctuating renewable energy sources into the future energy supply. The model has been used for investigating new operation strategies and investments in flexibility in order to utilize wind power and avoid excess production. The other model (H₂RES) has been designed for simulating the integration of renewable sources and hydrogen into island energy systems. The H₂RES model can use wind, solar and hydro as renewable energy sources and diesel blocks as backup. The latest version of the H₂RES model has an integrated grid connection with the mainland. The H₂RES model was tested on the power system of Porto Santo Island, Madeira, Portugal, Corvo and Graciosa Islands, Azores Islands, Portugal and Sal Island, Cape Verde. This paper presents the results of using the two different models on the same case, the island of Mljet, Croatia. The paper compares methodologies and results with the purpose of identifying mutual benefits and improvements of both models.     

Modelization of hybrid systems with hydrogen and renewable energy oriented to electric propulsion in sailboats

This paper presents a conceptual model of a hybrid electric sailboat in which energy from electric grid is stored in batteries and energy from renewable energies (eolic, solar and hydro) is stored as hydrogen. The main objective of this model is to study the viability of electrifying traditional sailboats with internal combustion engines into hybrid systems with batteries and fuel cell. The most important advantage of this design is the possibility to reduce up to zero emissions of traditional sailboat. Conversion of renewable energy to hydrogen is performed through an electrolyzer and post conversion to energy is carried out by a fuel cell. The fuel cell with the batteries forms the hybrid system (batteries-fuel cell) for propulsion electrical energy supply. In order to model the boat dynamic and energy systems, modular mathematical models were developed under Matlab^®-Simulink^®, using a fixed-step solver for the simulation of global model. A simulated logic controller manages the global model. In this paper, many models have been used: some of them are based in literature models and others were developed from experimental data. A control strategy has also been developed to manage energy flows and then it has been embedded to Matlab^® language. The global model permits test the performance of the sailboat.     

A modeling approach for investigating climate change impacts on renewable energy utilization

In this study, an integrated community‐scale energy model (ICEM) was developed for supporting renewable energy management (REM) systems planning with the consideration of changing climatic conditions. Through quantitatively reflecting interactive relationships among various renewable energy resources under climate change, not only the impacts of climate change on each individual renewable energy but also the combined effects on power‐generation sector from renewable energy resources could be incorporated within a general modeling framework. Also, discrete probability levels associated with various climate change impacts on the REM system could be generated. Moreover, the ICEM could facilitate capacity–expansion planning for energy‐production facilities within a multi‐period and multi‐option context in order to reduce energy‐shortage risks under a number of climate change scenarios. The generated solutions can be used for examining various decision options that are associated with different probability levels when availabilities of renewable energy resources are affected by the changing climatic conditions. A series of probability levels of hydropower‐, wind‐ and solar‐energy availabilities can be integrated into the optimization process. The developed method has been applied to a case of long‐term REM planning for three communities. The generated solutions can provide desired energy resource/service allocation and capacity–expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs, renewable energy availabilities and energy‐shortage risks can also be tackled with the consideration of climate change, which would have both positive and negative impacts on the system cost, energy supply and greenhouse‐gas emission. Copyright © 2011 John Wiley & Sons, Ltd.     

EnerGis: A geographical information based system for the evaluation of integrated energy conversion systems in urban areas

A geographical information system has been developed to model the energy requirements of an urban area. The purpose of the platform is to model with sufficient detail the energy services requirements of a given geographical area in order to allow the evaluation of the integration of advanced integrated energy conversion systems. This tool is used to study the emergence of more efficient cities that realize energy efficiency measures, integrate energy efficient conversion technologies and promote the use of endogenous renewable energy. The model is illustrated with case studies for the energetic planning of the Geneva district (Switzerland).     

Community-scale renewable energy systems planning under uncertainty—An interval chance-constrained programming approach

In this study, an inexact community-scale energy model (ICS-EM) has been developed for planning renewable energy management (REM) systems under uncertainty. This method is based on an integration of the existing interval linear programming (ILP), chance-constrained programming (CCP) and mixed integer linear programming (MILP) techniques. ICS-EM allows uncertainties presented as both probability distributions and interval values to be incorporated within a general optimization framework. It can also facilitate capacity-expansion planning for energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term renewable energy management planning for three communities. Useful solutions for the planning of energy management systems have been generated. Interval solutions associated with different risk levels of constraint violation have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks can also be tackled. Higher costs will increase system stability, while a desire for lower system costs will run into a risk of potential instability of the management system. They are helpful for supporting (a) adjustment or justification of allocation patterns of energy resources and services, (b) formulation of local policies regarding energy consumption, economic development and energy structure, and (c) analysis of interactions among economic cost, system reliability and energy-supply security.     

Feasibility assessment of introducing distributed energy resources in urban areas of China

In this study, based on the consideration of achieving a low-carbon city, a distributed energy system is promoted by integrating combined heat and power (CHP) plant, biomass energy and photovoltaic technology, for the urban areas in China. An analytical model has been developed for estimating an economically efficient installation and operation pattern for the distributed energy system. As an illustrative example, a numerical study is conducted of feasible distributed energy system for a model area in Shanghai, while considering five scenarios with different technology combinations. According to the simulation results, although enjoying reasonable environmental merits, it is hard to diffuse the distributed generation technologies, especially some renewable ones, in the model area from the economic point of view. Currently, the most feasible technology is the natural gas CHP system, which has a cost reduction ratio of only 0.7%. In addition, the sensitivity analyses illustrate that the introduction of electricity buy-back and the reduction of biogas price can promote the adoption of some renewable technologies to some extent.     

Economic and environmental aspects of the component sizing for a stand-alone building energy system: A case study

When designing a building energy system based on renewable energy sources, a major challenge is the suitable sizing of its components. In this paper, a simulation tool is presented for determining the optimal sizes of the main components of a stand-alone building energy system which integrates both thermal and electric renewable energy sources. Since the control of this multisource energy system is a non-trivial, multivariable control problem, particular emphasis is placed on the energy management system. A control structure based on model predictive control is proposed, whereas the underlying optimal control problem is formulated as a mixed-integer linear programming problem.The simulation tool developed is successfully applied on the specific case of an alpine lodge. A set of potential configurations, each being optimal with respect to both the net present costs and the global warming potential, is generated by analyzing the system for various component sizes. Out of this set, the decision makers can choose the most cost efficient configuration fulfilling their specifications.     

Reliability based socio economic optimal renewable energy model for India

Renewable energy sources such as solar, wind and biomass have to play a vital role in the developing countries like India in order to meet the growing energy demand. In the last five years, some renewable energy sources had emerged as technically and economically viable alternatives in the energy sector, as a result, more ambitious plans for their dissemination were being launched. In this situation, development of an energy model exclusively for renewables will help in the allocation of appropriate renewable energy systems for different end-uses in the future. An attempt has been made to develop a reliability based socio economic optimal renewable energy model for India in the year 2020–2021. The effect of social acceptance variation in OREM model was analysed. The lighting end-use would be met by solar PV and biogas system to an extent of 0.5198×10¹⁵ kJ and 0.75×10¹⁵ kJ, respectively. Similarly, the renewable energy utilisation is found for other end-uses.     

Modelling and optimization of the smart hybrid renewable energy for communities (SHREC)

The future energy system in community level should be more ‘smart’ to secure reliability, enhance market service, minimize environmental impact, reduce costs and improve the use of renewable energy source (RES). Therefore, this paper proposes an energy integration system – smart hybrid renewable energy for communities (SHREC). It considers both thermal (heating and cooling) and electricity market in a large community level and highlight the interactions between them through utilizing RES, combined heat and power (CHP) and energy storages. A planning model based on CHP modelling is developed for the SHREC system. A linear programming (LP) algorithm is developed to optimize the SHREC system in a weekly period and the results are compared with an existing energy optimization software. We also demonstrate the model in a sample SHREC system during three typical weeks with cold, warm and mid-season weather in the year 2011. The results indicate that the developed modelling and optimization method is more efficient and flexible for the smart hybrid renewable energy systems.     

A probabilistic model for 1st stage dimensioning of renewable hydrogen transport micro-economies

The implementation of a hydrogen transport economy based on renewable energy sources is seen by many as the ultimate sustainable transport solution. However, dimensioning of hydrogen production systems is complex: renewable energy sources are stochastic in nature, requiring the collection of empirical datasets relating to weather patterns on a daily, seasonal and annual basis; and hydrogen production is characterised by sensitivity to operating conditions and diversity in the performance of the component parts.A probabilistic model is developed for dimensioning of hydrogen production systems that removes the reliance on the collection of empirical datasets and the requirement for detailed performance characterisation of component parts. The model utilises well known correlations and distribution modelling techniques to predict energy output from either a photovoltaic array or wind turbine and hence the number of fuel cell electric vehicles (FCEVs) that could be supported on an annual basis.The model was implemented in MatLab and simulation results were compared with existing empirical based studies. Through simulation, limitations of the model were investigated and discussed. It was shown that the model was able to predict the number of FCEVs supported to within 10% (solar pathway) and 22% (wind pathway) for those studies investigated. These results are in alignment with the intention of the model as a first stage tool for the dimensioning of renewable hydrogen energy transport micro-economies.     

加快我国可再生能源数据信息平台建设

有效的可再生能源数据信息平台是进行新能源发展战略制定、规划、决策的基础.相比可再生能源的迅速发展,我国可再生能源信息收集和统计工作相对滞后,并缺乏一个集中的信息发布和共享服务平台.我国迫切需要建立和完善可再生能源信息收集平台,构建基于系统科学的数据信息分析系统.美国能源信息署(EIA)、美国可再生能源实验室(REL)、丹麦可再生能源实验室(Risoe)、国际能源署(IEA)、亚太经合组织(APEC)在能源和可再生能源数据信息平台建设方面积累了丰富的经验,代表了国际先进水平,可为我国可再生能源数据信息平台的建设提供重要的参考与借鉴.它们的经验包括人财物组织、数据收集方式、数据管理、数据监测、数据分析等方面.为加快我国可再生能源数据信息平台建设、建议有关部门应做好以下几项工作:加大对国家可再生能源数据信息平台建设的支持力度:加强国际交流合作,充分利用各国和有关国际组织的研究成果;严格数据定义,统一数据标准;建立高质量的数据收集体系;建立数据核查与评价机制;建立可再生能源数据信息平台标准手册制度;实现数据信息平台建设和运营管理的“天缝”衔接.