The effect of long lead times for planning of energy efficiency and biorefinery technologies at a pulp mill

The pulp and paper industry has many promising opportunities in the biorefinery field. To reach this potential, investments are required in new, emerging technologies and systems solutions which cannot be quickly implemented. In this paper, an approach to model the necessarily long planning times for this kind of investments is presented. The methodology used is based on stochastic programming, and all investments are optimized under uncertain energy market conditions. The uncertain cost development of the emerging technologies is also considered. It is analyzed using scenario analysis where both the cost levels and the timing for market introduction are considered. The effect of long lead times is studied by assuming that no investments can be decided on now and implemented already today, and only investments planned for today can be implemented in, for example, five years. An example is presented to illustrate the usefulness of the proposed approach. The example includes the possibility of future investment in lignin separation, and shows how the investment planning of industrial energy efficiency investments can be guided by using the proposed systematic approach. The example also illustrates the value of keeping flexibility in the investment planning.     

Investments into forest biorefineries under different price and policy structures

Increasing scarcity of oil reserves and the high CO₂ emissions from using oil have contributed to the development of renewable biofuels. Pulp and paper mill integrated forest biorefineries offer one important means to increase biofuel production. This study analyzes the effects of policies to support biofuel production in the pulp and paper sector. We study the relative effectiveness of three biofuel supporting policy instruments, namely production subsidy, input subsidy and investment subsidy. We present a partial equilibrium pulp and paper market model with a biorefinery investment option. A numerical model is used to evaluate the impacts of policy instruments on wood prices, as well as input choices and investment strategies of pulp and paper industries. The data represent the Finnish pulp and paper sector. We evaluate the values and direct costs of the policy instruments in a situation of exogenous biofuel production targets. The direct costs of input and investment subsidies are higher than those of a production subsidy. With all the policy instruments, Finnish pulp and paper mills would invest in wood-gasifying technology, instead of black liquor based one. The number of biorefinery units is dependent on the subsidy type — investment and input subsidies are likely to result in more numerous but smaller biofuel production units than a production subsidy. With all the policy instruments the demand for wood increases in Finland leading to higher wood prices. This, in turn, could reflect negatively on the profitability of the pulp and paper industries. To a significant degree, the model and the results can be generalized to other countries and markets where integrated pulp and paper mills are operating.     

A real option-based simulation model to evaluate investments in pump storage plants

Investments in pump storage plants are expected to grow especially due to their ability to store an excess of supply from wind power plants. In order to evaluate these investments correctly the peculiarities of pump storage plants and the characteristics of liberalized power markets have to be considered. The main characteristics of power markets are the strong power price volatility and the occurrence of prices spikes. In this article a valuation model is developed capturing these aspects using power price simulation, optimization of unit commitment and capital market theory. This valuation model is able to value a future price-based unit commitment planning that corresponds to future scope of actions also called real options. The resulting real option value for the pump storage plant is compared with the traditional net present value approach. Because this approach is not able to evaluate scope of actions correctly it results in strongly smaller investment values and forces wrong investment decisions.     

Implementation of lignin-based biorefinery into a Canadian softwood kraft pulp mill: Optimal resources integration and economic viability assessment

Implementation of a lignin-based biorefinery into one of the existing kraft pulp mills calls for increased consumption of resources such as steam (by up to 21.5%), water (by up to 3%), carbon dioxide (by up to 16.2%), and sulphuric acid (by up to 11.3%). To compensate for these extra demands on resources, an advanced process integration method was used to identify steam, water, and chemicals savings options and resource recovery opportunities within the kraft process. Given the importance of the lignin-based biorefinery, an economic viability assessment was carried out toward four scenarios, namely: a reference case relating to a stand-alone kraft pulp mill without a pulp production increase but with/without advanced process integration (scenarios #1 and #2) as well as to an integrated biorefinery with a pulp production increase by 5, 10 and 15% (scenarios #3 and #4).     

The forest biorefinery and its implementation in the pulp and paper industry: Energy overview

Incorporating a biorefinery unit to an operating Kraft pulping process has significant technological, economic and social advantages over the construction of a grassroot biorefinery. Also, the conversion of a Kraft mill from total pulp making to complete biorefinery can be done in a stepwise fashion and so give a company that envisages such transformation the opportunity to master the new technologies, evaluate options and develop an appropriate business plan. In all cases however, the road to conversion presents serious challenges. As components of the wood such as lignin or hemicelluloses are withdrawn from the Kraft pulp line, the heat production capacity from the recovery boiler where they are currently burnt is diminished. At the same time the operation of the added biorefinery unit increases the steam demand. In order to avoid fossil fuel dependency, the total site must be highly integrated and optimized. The application of an intensive and innovative energy optimization methodology to actual case studies has shown that the green, low GHG emissions biorefinery is feasible. The economics can be attractive for a site combining specialty wood pulp and bio-product, biomass gasification, power cogeneration and heat upgrading by optimally positioned and designed absorption heat cycles. The methodology has been applied to biorefining technologies for lignin and hemicelluloses extraction and valorisation, both technologies being coupled with gasification of wood residue.     

A model for optimization of process integration investments under uncertainty

The long-term economic outcome of energy-related industrial investment projects is difficult to evaluate because of uncertain energy market conditions. In this article, a general, multistage, stochastic programming model for the optimization of investments in process integration and industrial energy technologies is proposed. The problem is formulated as a mixed-binary linear programming model where uncertainties are modelled using a scenario-based approach. The objective is to maximize the expected net present value of the investments which enables heat savings and decreased energy imports or increased energy exports at an industrial plant. The proposed modelling approach enables a long-term planning of industrial, energy-related investments through the simultaneous optimization of immediate and later decisions. The stochastic programming approach is also suitable for modelling what is possibly complex process integration constraints. The general model formulation presented here is a suitable basis for more specialized case studies dealing with optimization of investments in energy efficiency.     

Power system planning with high renewable energy penetration considering demand response

Electric system planning with high variable renewable energy (VRE) penetration levels has attracted great attention world-wide. Electricity production of VRE highly depends on the weather conditions and thus involves large variability, uncertainty, and low-capacity credit. This gives rise to significant challenges for power system planning. Currently, many solutions are proposed to address the issue of operational flexibility inadequacy, including flexibility retrofit of thermal units, inter-regional transmission, electricity energy storage, and demand response (DR). Evidently, the performance and the cost of various solutions are different. It is relevant to explore the optimal portfolio to satisfy the flexibility requirement for a renewable dominated system and the role of each flexibility source. In this study, the value of diverse DR flexibilities was examined and a stochastic investment planning model considering DR is proposed. Two types of DRs, namely interrupted DR and transferred DR, were modeled. Chronological load and renewable generation curves with 8760 hours within a whole year were reduced to 4 weekly scenarios to accelerate the optimization. Clustered unit commitment constraints for accommodating variability of renewables were incorporated. Case studies based on IEEE RTS-96 system are reported to demonstrate the effectiveness of the proposed method and the DR potential to avoid energy storage investment.     

Economy and CO2 emissions trade-off: A systematic approach for optimizing investments in process integration measures under uncertainty

In this paper we present a systematic approach for taking into account the resulting CO₂ emissions reductions from investments in process integration measures in industry when optimizing those investments under economic uncertainty. The fact that many of the uncertainties affecting investment decisions are related to future CO₂ emissions targets and policies implies that a method for optimizing not only economic criteria, but also greenhouse gas reductions, will provide better information to base the decisions on, and possibly also result in a more robust solution. In the proposed approach we apply a model for optimization of decisions on energy efficiency investments under uncertainty and regard the decision problem as a multiobjective programming problem. The method is applied to a case of energy efficiency investments at a chemical pulp mill. The case study is used to illustrate that the proposed method provides a good framework for decision-making about energy efficiency measures when considerations regarding greenhouse gas reductions influence the decisions. We show that by setting up the problem as a multiobjective programming model and at the same time incorporating uncertainties, the trade-off between economic and environmental criteria is clearly illustrated.     

An optimization methodology for identifying robust process integration investments under uncertainty

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures.     

考虑延迟期权的增量配电网源网协调规划方法

考虑增量配电网中的负荷电价变化等不确定性因素,将延迟期权理论融入到增量配电网源网规划模型之中,提出一种考虑延迟期权的增量配电网源网协调规划方法.首先在期望负荷增长率的基础上构建增量配电网分布式电源的选址定容模型,并通过序优化算法得到分布式电源规划可行方案的帕累托前沿;然后在此基础上通过蒙特卡洛模拟,得出增量配电网负荷及...     

Flexibility improvement evaluation of hydrogen storage based on electricity–hydrogen coupled energy model

To achieve carbon neutrality by 2060, decarbonization in the energy sector is crucial. Hydrogen is expected to be vital for achieving the aim of carbon neutrality for two reasons: use of power-to-hydrogen (P2H) can avoid carbon emissions from hydrogen production, which is traditionally performed using fossil fuels; Hydrogen from P2H can be stored for long durations in large scales and then delivered as industrial raw material or fed back to the power system depending on the demand. In this study, we focus on the analysis and evaluation of hydrogen value in terms of improvement in the flexibility of the energy system, particularly that derived from hydrogen storage. An electricity–hydrogen coupled energy model is proposed to realize the hourly-level operation simulation and capacity planning optimization aiming at the lowest cost of energy. Based on this model and considering Northwest China as the region of study, the potential of improvement in the flexibility of hydrogen storage is determined through optimization calculations in a series of study cases with various hydrogen demand levels. The results of the quantitative calculations prove that effective hydrogen storage can improve the system flexibility by promoting the energy demand balance over a long term, contributing toward reducing the investment cost of both generators and battery storage and thus the total energy cost. This advantage can be further improved when the hydrogen demand rises. However, a cost reduction by 20% is required for hydrogen-related technologies to initiate hydrogen storage as long-term energy storage for power systems. This study provides a suggestion and reference for the advancement and planning of hydrogen storage development in regions with rich sources of renewable energy.     

Biorefinery process water effluent treatments by salt coagulation

Acid pretreatment is one of the critical pretreatments for the biorefinery. However, little information is available on water effluent that results from this acidic pretreatment compared to alkaline pretreatment. In this study, the wastewaters from an integrated modern magnesium bisulphite pulp mill (acidic) were utilized as models for the acid pretreatment effluents of a modern biorefinery. The coagulation technique, using high valency electrolytes, was applied for the treatment of treated and untreated process water from the pulp mill. The effectiveness of some electrolytes and the selectivity of the coagulation process were compared by measuring the removal extent of critical contaminants such as organics, phosphorus and colour. The salt coagulation process was found to be selective for colour and total phosphorus removal from the wastewater, achieving more than 90% removal of contaminants.     

Energy optimization in a pulp and paper mill cogeneration facility

Alarmingly low pulp prices in early 2009 left pulp and paper mills across North America desperate for any way to improve thin profit margins. One solution that continues to gain popularity among the industry is improved energy management systems for cogeneration systems, which use steam for two purposes – to provide heat for the pulping process and to generate electricity for sale to regional providers. This paper presents an energy optimization algorithm for use in a pulp and paper mill cogeneration system. The algorithm is applicable to a number of popular mill configurations, power sale contracts, and fuel purchasing scenarios. The method is also extended to address weather-dependent cooling limitations encountered by a mill cogeneration facility, in which case an iterative solution is proposed in order to maintain convexity of the optimization problem. Results are presented in the form of three case studies.     

A Swedish integrated pulp and paper mill—Energy optimisation and local heat cooperation

Heat cooperation between industries and district heating companies is often economically and environmentally beneficial. In this paper, energy cooperation between an integrated Swedish pulp and paper mill and two nearby energy companies was analysed through economic optimisations. The synergies of cooperation were evaluated through optimisations with different system perspectives. Three changes of the energy system and combinations of them were analysed. The changes were process integration, extending biofuel boiler and turbine capacity and connection to a local heat market. The results show that the single most promising system change is extending biofuel and turbine capacity. Process integration within the pulp and paper mill would take place through installing evaporation units that yield less excess heat but must in this particular case be combined with extended biofuel combustion capacity in order to be beneficial. Connecting to the local heat market would be beneficial for the pulp and paper mill, while the studied energy company needs to extend its biofuel capacity in order to benefit from the local heat market. Furthermore, the potential of reducing CO₂ emissions through the energy cooperation is shown to be extensive; particularly if biofuel and turbine capacity is increased.     

The renewable energy targets of the Maghreb countries: Impact on electricity supply and conventional power markets

Morocco, Algeria and Tunisia, the three countries of the North African Maghreb region, are showing increased efforts to integrate renewable electricity into their power markets. Like many other countries, they have pronounced renewable energy targets, defining future shares of “green” electricity in their national generation mixes. The individual national targets are relatively varied, reflecting the different availability of renewable resources in each country, but also the different political ambitions for renewable electricity in the Maghreb states. Open questions remain regarding the targets’ economic impact on the power markets. Our article addresses this issue by applying a linear electricity market optimization model to the North African countries. Assuming a competitive, regional electricity market in the Maghreb, the model minimizes dispatch and investment costs and simulates the impact of the renewable energy targets on the conventional generation system until 2025. Special emphasis is put on investment decisions and overall system costs.     

Sensitivity analysis of investments in the pulp and paper industry On investments in the chemical recovery cycle at a board mill

In the pulp and paper industry, energy costs represents a relatively large proportion of the value of production. When investing in new equipment, considerations concerning boundary conditions, such as electricity and oil prices, are therefore of great importance. A vital requirement is the identification of other key parameters influencing production costs as well as possible interaction between these parameters. In this paper, a sensitivity analysis is accomplished by using an optimization model that minimizes the system cost combined with a systematic approach involving a statistical method. The paper analyses the possibilities of investing in a new chemical recovery cycle, including a new recovery boiler and evaporation plant, at a Swedish board mill. The study includes a survey of future changes, together with forecasts of boundary conditions, such as changes in the price of electricity and oil. Interactions between different parameters are also examined. Copyright © 2002 John Wiley & Sons, Ltd.     

Intelligent optimization of renewable resource mixes incorporating the effect of fuel risk,fuel cost and CO2 emission

Power system planning is a capital intensive investment-decision problem. The majority of the conventional planning conducted since the last half a century has been based on the least cost approach, keeping in view the optimization of cost and reliability of power supply. Recently, renewable energy sources have found a niche in power system planning owing to concerns arising from fast depletion of fossil fuels, fuel price volatility as well as global climatic changes. Thus, power system planning is under-going a paradigm shift to incorporate such recent technologies. This paper assesses the impact of renewable sources using the portfolio theory to incorporate the effects of fuel price volatility as well as CO₂ emissions. An optimization framework using a robust multi-objective evolutionary algorithm, namely NSGA-II, is developed to obtain Pareto optimal solutions. The performance of the proposed approach is assessed and illustrated using the Indian power system considering real-time design practices. The case study for Indian power system validates the efficacy of the proposed methodology as developing countries are also increasing the investment in green energy to increase awareness about clean energy technologies.     

Designing effective and efficient incentive policies for renewable energy in generation expansion planning

We present a bilevel optimization approach to designing effective and efficient incentive policies for stimulating investment in renewable energy. The effectiveness of an incentive policy is its capability to achieve a goal that would not be achievable without it. Renewable portfolio standards are used in this paper as the policy goal. The efficiency of an incentive policy is measured by the amount of policy intervention, such as taxes collected or subsidies paid, to achieve the policy goal. We obtain the most effective and efficient incentive policies in the context of generation expansion planning, in which a centralized planner makes investment decisions for the energy system to serve projected demand of electricity. A case study is conducted on integrated coal transportation and electricity transmission networks representing the contiguous United States. The numerical analysis from the case study provides insights on the comparison of various incentive policies. The sensitivity of the incentive policies with respect to coal production cost, wind energy investment cost, and transmission capacity is also studied.     

Comparison of black liquor gasification with other pulping biorefinery concepts – Systems analysis of economic performance and CO2 emissions

Black liquor gasification (BLG) is being developed as an alternative technology for energy and chemical recovery in kraft pulp mills. This study compares BLG – with downstream production of DME (dimethyl ether) or electricity – with recovery boiler-based pulping biorefinery concepts for different types of mills. The comparison is based on profitability as well as CO₂ emissions, using different future energy market scenarios. The possibility for carbon capture and storage (CCS) is considered. The results show that, if commercialised, BLG with DME production could be profitable for both market pulp mills and integrated pulp and paper mills in all energy market scenarios considered. Recovery boiler-based biorefinery concepts including extraction of lignin or solid biomass gasification with DME production could also be profitable for market and integrated mills, respectively. If the mill is located close to an infrastructure for CO₂ collection and transportation, CCS significantly improves profitability in scenarios with a high CO₂ emissions charge, for both combustion- and gasification-based systems. Concepts that include CCS generally show a large potential for reduction of global CO₂ emissions. Few of the concepts without CCS achieve a significant reduction of CO₂ emissions, especially for integrated mills.     

Assessing the value of pulp mill biomass savings in a climate change conscious economy

Pulp mills use significant amounts of biofuels, both internal and purchased. Biofuels could contribute to reach greenhouse gas emission targets at competitive costs. Implementing process integration measures at a pulp mill in order to achieve pulp production with less use of energy (biofuels) has not only on-site consequences but also off-site consequences, such as substitution of fossil fuels elsewhere by the saved pulp mill biofuels, and less on-site electric power generation. In this paper a method, a linking model, is suggested to analyse pulp mill biofuel saving measures when carbon dioxide (CO₂) external costs are internalised. The linking model is based on equilibrium economics and links information from CO₂ constrained energy market future scenarios with process integration measures. Pulp mill economics and marginal energy market CO₂ response are identified. In an applied study, four process integration measures at a Swedish pulp mill were analysed using five energy market future scenarios emanating from a Nordic energy model. The investigated investment alternatives for biofuel savings all result in positive net annual savings, irrespectively of the scenario used. However, CO₂ emissions may increase or decrease depending on the future development of the Nordic energy market.