A decision support system for planning biomass-based energy production

Environmental decision support systems (EDSS) are recognized as valuable tools for environmental planning and management. In this paper, a geographic information system (GIS)-based EDSS for the optimal planning of forest biomass use for energy production is presented. A user-friendly interface allows the creation of Scenarios and the running of the developed decision and environmental models. In particular, the optimization model regards decisions over a long-term period (e.g. years) and includes decision variables related to plant locations, conversion processes (pyrolisis, gasification, combustion), harvested biomass. Moreover, different energy products and different definitions of the harvesting and pre-treatment operations are taken into account. The correct management of the forest is considered through specific constraints, security factors, and procedures for parcel selection. The EDSS features and capabilities are described in detail, with specific reference to a case study. Discussion and further research are reported.     

Modeling of biomass-to-energy supply chain operations: Applications,challenges and research directions

Reducing dependency on fossil fuels and mitigating their environmental impacts are among the most promising aspects of utilizing renewable energy sources. The availability of various biomass resources has made it an appealing source of renewable energy. Given the variability of supply and sources of biomass, supply chains play an important role in the efficient provisioning of biomass resources for energy production. This paper provides a comprehensive review and classification of the excising literature in modeling of biomass supply chain operations while linking them to the wider strategic challenges and issues with the design, planning and management of biomass supply chains. On that basis, we will present an analysis of the existing gaps and the potential future directions for research in modeling of biomass supply chain operations.     

Proposal for a combined methodology for renewable energy planning. Application to a Spanish region

The article here presented aims to contribute to renewable energies development at regional level, proposing a methodology for the establishment of strategies needed to reach, in the long term, an energy system more sustainable and mainly based upon autochthonous resources.Current energy planning models are investigated, analysing its convenience to design a sustainable energy system, and a new methodology, that combines three different approaches, is proposed. Such new “hybrid” methodology resumes advantages of territorial strategic planning methods, based upon SWOT analysis, along with characteristics extracted both from Multicriteria decision analysis techniques and expert opinion “Delphi” methods.Nowadays, decisions concerning energy system cannot be consider under one specific criterion. Different implications, energetic, environmental or socioeconomic, derived from changes on energy development make it unavoidable to use tools and techniques that could take into account such multiplicity. It has been also intended to take advantage of the know-how acquired along the territorial strategic planning process carried out in the region to analyse, from year 1997 to 2000. This approach has allowed to integrate, under a unique methodology, tools from energy planning with those one used, and successfully tested, for the elaboration of the strategic plan for Jaén Province.The proposed methodology has been applied to Jaén Province in order to design a renewable energy plan for the region, setting strategic action lines and fixing strategic goals to be met on year 2010 by the provincial energy system. The objective regarding electricity production from renewable resources, on year 2010, is fixed above 1630 GWh, which represents a 43% of the total foreseeable electricity consumption. Overall contribution of renewable sources in provincial energy system is finally set to 28.3%, in terms of final energy.     

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.     

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.     

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.     

Sustainable electricity generation fuel mix analysis using an integration of multicriteria decision-making and system dynamic approach

To achieve a national energy access target of 90% urban and 51% rural by 2035, combat climate change, and diversify the energy sector in the country, the Zambian government is planning to integrate other renewable energy resources (RESs) such as wind, solar, biomass, and geothermal into the existing hydro generation–based power system. However, to achieve such targets, it is essential for the government to identify suitable combination of the RESs (electricity generation fuel mix) that can provide the greatest sustainability benefit to the country. In this paper, a multicriteria decision-making framework based on analytic hierarchy process and system dynamics techniques is proposed to evaluate and identify the best electricity generation fuel mix for Zambia. The renewable energy generation technologies considered include wind, solar photovoltaic, biomass, and hydropower. The criteria used are categorized as technical, economic, environmental, social, and political. The proposed approach was applied to rank the electricity generation fuel mix based on nine sustainability aspects: land use, CO₂ emissions, job creation, policy promotion affordability, subsidy cost, air pollution reduction, RES electricity production, RES cumulative capacity, and RES initial capital cost. The results indicate that based on availability of RESs and sustainability aspects, in overall, the best future electricity generation mix option for Zambia is scenario with higher hydropower (40%) penetration, wind (30%), solar (20%), and lower biomass (10%) penetration in the overall electricity generation fuel mix, which is mainly due to environmental issues and availability of primary energy resources. The results further indicate that solar ranks first in most of the scenarios even after the penetration weights of RES are adjusted in the sensitivity analysis. The wind was ranked second in most of the scenarios followed by hydropower and last was biomass. These developed electricity generation fuel mix pathways would enable the country meeting the future electricity generation needs target at minimized environmental and social impacts by 2035. Therefore, this study is essential to assist in policy and decision making including planning at strategic level for sustainable energy diversification.     

The forest products industry at an energy/climate crossroads

Transformational energy and climate policies are being debated worldwide that could have significant impact upon the future of the forest products industry. Because woody biomass can produce alternative transportation fuels, low-carbon electricity, and numerous other “green” products in addition to traditional paper and lumber commodities, the future use of forest resources is highly uncertain. Using the National Energy Modeling System (NEMS), this paper assesses the future of the forest products industry under three possible U.S. policy scenarios: (1) a national renewable electricity standard, (2) a national policy of carbon constraints, and (3) incentives for industrial energy efficiency. In addition, we discuss how these policy scenarios might interface with the recently strengthened U.S. renewable fuels standards. The principal focus is on how forest products including residues might be utilized under different policy scenarios, and what such market shifts might mean for electricity and biomass prices, as well as energy consumption and carbon emissions. The results underscore the value of incentivizing energy efficiency in a portfolio of energy and climate policies in order to moderate electricity and biomass price escalation while strengthening energy security and reducing CO₂ emissions.     

Regional energy planning through SWOT analysis and strategic planning tools.: Impact on renewables development

Strategic planning processes, which are commonly used as a tool for region development and territorial structuring, can be harnessed by politicians and public administrations, at the local level, to redesign the regional energy system and encourage renewable energy development and environmental preservation. In this sense, the province of Jaén, a southern Spanish region whose economy is mainly based on olive agriculture, has carried out its strategic plan aiming at a major socioeconomic development. Under the leadership of the provincial government and the University of Jaén, main provincial institutions joined to propose the elaboration of a participatory strategic plan for the whole province. Here, the elaboration of the energy part of the plan, which was directly focused on the exploitation of renewable resources, mainly solar and biomass energy, and which highlights the effectiveness of techniques from business management applied to a sustainable energy model design is presented. Renewable Energy development during the first years of plan execution is presented, and the impact of additional issues is discussed. It is concluded that, although multicriteria decision-making technologies (MCDA) are extensively used in energy planning, a different approach can be utilized to incorporate techniques from strategic analysis. Furthermore, SWOT (strengths, weaknesses, opportunities and threats) analysis has proved to be an effective tool and has constituted a suitable baseline to diagnose current problems and to sketch future action lines.     

Hybrid renewable energy systems for power generation in stand-alone applications: A review

It has become imperative for the power and energy engineers to look out for the renewable energy sources such as sun, wind, geothermal, ocean and biomass as sustainable, cost-effective and environment friendly alternatives for conventional energy sources. However, the non-availability of these renewable energy resources all the time throughout the year has led to research in the area of hybrid renewable energy systems. In the past few years, a lot of research has taken place in the design, optimization, operation and control of the renewable hybrid energy systems. It is indeed evident that this area is still emerging and vast in scope. The main aim of this paper is to review the research on the unit sizing, optimization, energy management and modeling of the hybrid renewable energy system components. Developments in research on modeling of hybrid energy resources (PV systems), backup energy systems (Fuel Cell, Battery, Ultra-capacitor, Diesel Generator), power conditioning units (MPPT converters, Buck/Boost converters, Battery chargers) and techniques for energy flow management have been discussed in detail. In this paper, an attempt has been made to present a comprehensive review of the research in this area in the past one decade.     

Forest management strategies for producing wood for energy from conventional forestry systems

The report reviews the current developments in forest management planning and practices to integrate the production of biomass for energy along with more conventional forest management goals. However, these have direct or indirect benefits on site preparation, planting and regeneration, stand improvement, and forest protection, soil compaction and disturbance, leaching and removal of nutrients maybe associated with increases in biomass harvesting.

Efforts are under way to adapt management practices and silvicultural treatments to biomass production. These begin at the planning stage with the development of management tools and more accurate forest inventory data. They include silvicultural treatments such as shelterwood thinning in mixed wood stands and the interplanting of various tree species with the dual purpose of producing energy wood and conventional forest products.

Three systems are available for recovering residues at time of final harvesting. The postharvest recovery of residues area is commonly used in Europe but is generally uneconomic in North America where the harvesting of small stems and integrated harvesting are favoured.

Future work is required to develop techniques for estimating the quantity of bioenergy resources available under different management strategies and to elucidate the long-term environmental impacts of producing wood for energy from conventional forestry systems.     

Overview of renewable energy sources in the Republic of the Sudan

Sudan is an agricultural country with fertile land, plenty of water resources, livestock, forestry resources and agricultural residues. An overview of the energy situation in Sudan is introduced with reference to the end uses and regional distribution. Energy sources are divided into two main types: conventional energy (biomass, petroleum products and electricity) and non-conventional energy (solar, wind, hydro, etc.). Sudan possesses a relatively high abundance of solar radiation, moderate wind speeds, hydro and biomass energy resources. Application of new and renewable sources of energy available in Sudan is now a major issue in strategic planning for alternatives to fossil fuels to provide part of local energy demand. Sudan is an important case study in the context of renewable energy. It has a long history of meeting its energy needs through renewables. Sudan’s renewables portfolio is broad and diverse, due in part to the country’s wide range of climates and landscapes. Like many of the African leaders in renewable energy utilisation, Sudan has a well-defined commitment to continue research, development and implementation of new technologies. Sustainable low-carbon energy scenarios for the new century emphasise the untapped potential of renewable resources. Rural areas of Sudan can benefit from this transition. The increased availability of reliable and efficient energy services stimulates new development alternatives. Renewable environmentally friendly energy must be encouraged, promoted, implemented and demonstrated, for use in the Republic of the Sudan.     

Drivers,barriers, and strategies for implementation of renewable energy technologies in rural areas in Bangladesh—An innovation system analysis

Bangladesh has good potential for harnessing renewable energy sources such as solar, biomass, wind, and mini-hydropower. The country has been experiencing a gradual shift towards exploring renewable energy resources as a driving force for rural development. A few public sector and non-government organizations have started to develop renewable energy technology (RET) projects in rural areas. The lessons learnt from different demonstrations of RET projects reveal that with careful forward planning renewable energy can provide far-reaching economic, environmental, and social benefits to people living in remote rural areas in Bangladesh. This paper identifies some of the barriers that need to be overcome for the successful development of renewable energy technology sector and betterment of rural livelihoods. It does so through a critical review of policy and institutional settings, as well as present status and lessons learnt from pilot demonstration of a number of RET projects undertaken by different organizations. The study highlights policy implications of the review with the aim of supporting decision makers in formulating renewable energy policies and future plans for Bangladesh.     

A superstructure model of an isolated power supply system using renewable energy: Development and application to Jeju Island,Korea

In this study, we aim to develop a superstructure-based optimization model using mixed integer linear programming (MILP) to determine the optimal combination and sizing for a hybrid renewable energy system to be used in an isolated area. The developed model has a three-layered energy structure to reflect the current reality in which energy production and consumption sites are generally separate. A variety of economic factors, including distance between facilities and an installation area, are considered for a more accurate estimation of the total annualized cost. Two types of optimization models, i.e., with and without a battery, are proposed to evaluate the economic and technical effects of a storage device to resolve operation issues caused by intermittent resources. An application case study on Jeju Island, Korea, confirms that the proposed model is suitable for decision making at the planning stage of a renewable energy system.     

Optimization of electrical distribution networks fed by conventional and renewable energy sources

This paper provides a methodology for the optimization of an existing electrical distribution network when upgraded by renewable energies. The contribution of renewable energy in electricity generation is decided upon through both network design optimization and proper load management whereby applications that can be satisfied by non‐electrical means are separated from the main load. The remaining load will then be satisfied by an optimal mix of renewable energy which will be injected to the existing grid. The proposed problem will be formulated using multiobjective linear programming in conjunction with fuzzy logic. It will be shown that optimization using fuzzy logic can provide decision makers with more flexibility that would assist them in the allocation of various energy resources to optimally meet the various end uses and solve the problem of renewable energy connection to existing distribution networks. Copyright © 1999 John Wiley & Sons, Ltd.     

Development of an interval multi‐stage stochastic programming model for regional energy systems planning and GHG emission control under uncertainty

A regional energy system consists of diverse forms of energy. Energy‐related issues such as utilization of renewable energy and reduction of greenhouse gas (GHG) emission are confronting decision makers. Meanwhile, various uncertainties and dynamics of the energy system are posing difficulties for the energy system planning, especially for those under multiple stages. In this study, an interval multi‐stage stochastic programming regional energy systems planning model (IMSP‐REM) was developed to support regional energy systems management and GHG control under uncertainty. The IMSP‐REM is a hybrid methodology of inexact optimization and multi‐stage stochastic programming. Not only can it handle uncertainties presented as intervals and probability density functions but also reflect dynamics of system conditions over multiple planning stages. The developed IMSP‐REM was applied to a hypothetical regional energy system. The results indicate that the IMSP‐REM can effectively reflect issues of GHG reduction and renewable energy utilization within an energy system planning framework. In addition, the model has advantages in incorporating multiple uncertainties and dynamics within energy management systems. Copyright © 2011 John Wiley & Sons, Ltd.     

Effective biomass integration into existing combustion plant

Fossil fuels such as coal still dominate in current energy production plants. However, due to their large carbon footprint caused by combustion, rising prices and the unclear an increased interest in renewable and alternative fuels is observable. By 2020, renewable energy should account for 20% of the EU’s final energy consumption in order to reduce the negative impacts of the utilization of fossil fuels. Biomass-based fuels contribute to this effort.The optimization approach introduced in this article supports sustainable and financially feasible biomass integration into the existing large energy producing system with combined heat and power (CHP) production. The objective is to identify optimal conditions (optimal amount of burned fuels with respect to energy demands and energy flows through key components) with regard to maximum annual financial profit.The general mathematical model of a CHP plant utilizing more types of fuels is introduced and an optimization problem is formulated. The approach application is demonstrated on a case study involving existing CHP plant co-firing coal and biomass. The optimization problem is implemented and solved in GAMS (General Algebraic Modeling System). A sensitivity analysis of crucial parameters is performed and the results are presented and discussed.     

Supply chain optimization of residual forestry biomass for bioenergy production: The case study of Portugal

Within a large set of renewable energies being explored to tackle energy sourcing problems, bioenergy can represent an attractive solution if effectively managed. The supply chain design supported by mathematical programming can be used as a decision support tool to the successful bioenergy production systems establishment. This strategic decision problem is addressed in this paper where we intent to study the design of the residual forestry biomass to bioelectricity production in the Portuguese context. In order to contribute to attain better solutions a mixed integer linear programming (MILP) model is developed and applied in order to optimize the design and planning of the bioenergy supply chain. While minimizing the total supply chain cost the production energy facilities capacity and location are defined. The model also includes the optimal selection of biomass amounts and sources, the transportation modes selection, and links that must be established for biomass transportation and products delivers to markets. Results illustrate the positive contribution of the mathematical programming approach to achieve viable economic solutions. Sensitivity analysis on the most uncertain parameters was performed: biomass availability, transportation costs, fixed operating costs and investment costs.     

System analysis for effective use of palm oil waste as energy resources

Biomass refers to renewable energy sources and comes from biological materials such as trees, plants, manure as well as municipal solid wastes. Effective utilization of biomass as an energy resource requires the use of an optimization model to take into account biomass availability, transportation distances, and the scales and locations of power facilities within a region. In this study, we develop a new analytical tool that integrates cost, energy savings, greenhouse gas considerations, scenario analysis, and a Geographic Information System (GIS) to provide a comprehensive analysis of alternative systems for optimizing biomass energy production. The goal is to find a system that optimizes the use of biomass waste by analyzing the cost, net avoided CO₂ emission, and net energy savings with the objective of profit maximization. In this paper, we describe an application of the modeling tool described above to one of the fastest growing agriculture industries in Asia, the palm oil industry, for the case of Malaysia. Five scenarios utilizing palm oil waste as energy resources are discussed. The scenario of installing of new Combined Heat and Power (CHP) plants in the region yielded a number of benefits in terms of net energy savings, net avoided CO₂ emission, and profits. The results also demonstrate the benefits of utilizing excess heat for biomass pre-treatment. The choice of a suitable CHP plant scale, management strategies for biomass seasonal availability, and market price of biomass are also important factors for effective use of the biomass in a region.