A Dynamic Input-Output Model with Renewable Resources

The paper studies a generalisation of the dynamic Leontief input-output model. The standard dynamic Leontief model will be extended with the balance equation of renewable resources. The renewable stocks will increase regenerating and decrease exploiting primary natural resources. In this study the controllability of this extended model is examined by taking the consumption as the control parameter. Assuming balanced growth for both consumption and production, we investigate the exhaustion of renewable resources in dependence on the balanced growth rate and on the rate of natural regeneration. In doing so, classic results from control theory and on eigenvalue problems in linear algebra are applied.

A Dynamic Input-Output Model with Renewable Resources

The paper studies a generalisation of the dynamic Leontief input-output model. The standard dynamic Leontief model will be extended with the balance equation of renewable resources. The renewable stocks will increase regenerating and decrease exploiting primary natural resources. In this study the controllability of this extended model is examined by taking the consumption as the control parameter. Assuming balanced growth for both consumption and production, we investigate the exhaustion of renewable resources in dependence on the balanced growth rate and on the rate of natural regeneration. In doing so, classic results from control theory and on eigenvalue problems in linear algebra are applied.

Optimizing the renewable generation mix in the Portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

Energy resources management in three distinct time horizons considering a large variation in wind power

The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players.

Bioproduction of succinic acid from renewable feedstocks by Actinobacillus succinogenes 130Z

Succinic acid (SA) is a highly versatile building block that is used in a wide range of industrial applications. The biological production of succinic acid has emerged in the last years as an efficient alternative to the chemical production based on fossil fuels. However, in order to fully replace the competing petro-based chemical process from which it has been produced so far, some challenges remain to be surpassed. In particular, one main obstacle would be to reduce its production costs, mostly associated to the use of refined sugars. The present work is focused on the development of a sustainable and cost-e↵ective microbial production process based on cheap and renewable resources, such as agroindustrial wastes. Hence, glycerol and carob pods were identified as promising feedstocks and used as inexpensive carbon sources for the bioproduction of succinic acid by Actinobacillus succinogenes 130Z, one of the best naturally producing strains. Even though glycerol is a highly available carbon source, as by-product of biodiesel production, its consumption by A. succinogenes is impaired due to a redox imbalance during cell growth. However, the use of an external electron acceptor such as dimethylsulfoxide (DMSO) may improve glycerol metabolism and succinic acid production by this strain. As such, DMSO was tested as a co-substrate for glycerol consumption and concentrations of DMSO between 1 and 4% (v/v) greatly promoted glycerol consumption and SA production by this biocatalyst. Aiming at obtaining higher succinic acid yield and production rate, batch and fed-batch experiments were performed under controlled cultivation conditions. Batch experiments resulted in a succinic acid yield on glycerol of 0.95 g SA/g GLY and a production rate of 2.13 g/L.h, with residual production of acetic and formic acids. In fed-batch experiment, the SA production rate reached 2.31 g/L.h, the highest value reported in the literature for A. succinogenes using glycerol as carbon source. DMSO dramatically improved the conversion of glycerol by A. succinogenes and may be used as a co-substrate, opening new perspectives for the use of glycerol by this biocatalyst. Carob pods, highly available in Portugal as a residue from the locust bean gum industry, contain a significant amount of fermentable sugars such as sucrose, glucose and fructose and were also used as substrate for succinic acid production. Sugar extraction from raw and roasted carobs was optimized varying solid/water ratio and extraction time, maximizing sugar recovery while minimizing the extraction of polyphenols. Kinetic studies of glucose, fructose and sucrose consumption by A. succinogenes as individual carbon sources till 30 g/L were first determined to assess possible metabolic diferences. Results showed no significant diferences related to sugar consumption and SA production between the diferent sugars. Carob pods water extracts were then used as carbon source during controlled batch cultivations. (...)

Project scheduling and cost minimization with multiple availability constrained resources under stochastic conditions

The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.

On the Effects of Mergers on Equilibrium Outcomes in a Common Property Renewable Asset Oligopoly

This paper examines a dynamic game of exploitation of a common pool of some renewable asset by agents that sell the result of their exploitation on an oligopolistic market. A Markov Perfect Nash Equilibrium of the game is used to analyze the effects of a merger of a subset of the agents. We study the impact of the merger on the equilibrium production strategies, on the steady states, and on the profitability of the merger for its members. We show that there exists an interval of the asset's stock such that any merger is profitable if the stock at the time the merger is formed falls within that interval. That includes mergers that are known to be unprofitable in the corresponding static equilibrium framework.

Master Plan for Renewable Energy based Electricity Generation in The Gambia

The principal objective of this paper is to develop a methodology for the formulation of a master plan for renewable energy based electricity generation in The Gambia, Africa. Such a master plan aims to develop and promote renewable sources of energy as an alternative to conventional forms of energy for generating electricity in the country. A tailor-made methodology for the preparation of a 20-year renewable energy master plan focussed on electricity generation is proposed in order to be followed and verified throughout the present dissertation, as it is applied for The Gambia. The main input data for the proposed master plan are (i) energy demand analysis and forecast over 20 years and (ii) resource assessment for different renewable energy alternatives including their related power supply options. The energy demand forecast is based on a mix between Top-Down and Bottom-Up methodologies. The results are important data for future requirements of (primary) energy sources. The electricity forecast is separated in projections at sent-out level and at end-user level. On the supply side, Solar, Wind and Biomass, as sources of energy, are investigated in terms of technical potential and economic benefits for The Gambia. Other criteria i.e. environmental and social are not considered in the evaluation. Diverse supply options are proposed and technically designed based on the assessed renewable energy potential. This process includes the evaluation of the different available conversion technologies and finalizes with the dimensioning of power supply solutions, taking into consideration technologies which are applicable and appropriate under the special conditions of The Gambia. The balance of these two input data (demand and supply) gives a quantitative indication of the substitution potential of renewable energy generation alternatives in primarily fossil-fuel-based electricity generation systems, as well as fuel savings due to the deployment of renewable resources. Afterwards, the identified renewable energy supply options are ranked according to the outcomes of an economic analysis. Based on this ranking, and other considerations, a 20-year investment plan, broken down into five-year investment periods, is prepared and consists of individual renewable energy projects for electricity generation. These projects included basically on-grid renewable energy applications. Finally, a priority project from the master plan portfolio is selected for further deeper analysis. Since solar PV is the most relevant proposed technology, a PV power plant integrated to the fossil-fuel powered main electrical system in The Gambia is considered as priority project. This project is analysed by economic competitiveness under the current conditions in addition to sensitivity analysis with regard to oil and new-technology market conditions in the future.

Implications of the North Atlantic Oscillation for a UK–Norway renewable power system

UK wind-power capacity is increasing and new transmission links are proposed with Norway, where hydropower dominates the electricity mix. Weather affects both these renewable resources and the demand for electricity. The dominant large-scale pattern of Euro-Atlantic atmospheric variability is the North Atlantic Oscillation (NAO), associated with positive correlations in wind, temperature and precipitation over northern Europe. The NAO's effect on wind-power and demand in the UK and Norway is examined, focussing on March when Norwegian hydropower reserves are low and the combined power system might be most susceptible to atmospheric variations. The NCEP/NCAR meteorological reanalysis dataset (1948–2010) is used to drive simple models for demand and wind-power, and ‘demand-net-wind’ (DNW) is estimated for positive, neutral and negative NAO states. Cold, calm conditions in NAO− cause increased demand and decreased wind-power compared to other NAO states. Under a 2020 wind-power capacity scenario, the increase in DNW in NAO− relative to NAO neutral is equivalent to nearly 25% of the present-day average rate of March Norwegian hydropower usage. As the NAO varies on long timescales (months to decades), and there is potentially some skill in monthly predictions, we argue that it is important to understand its impact on European power systems.

Design and techno-economic evaluation of microbial oil production as a renewable resource for biodiesel and oleochemical production

Experimental results from the open literature have been employed for the design and techno-economic evaluation of four process flowsheets for the production of microbial oil or biodiesel. The fermentation of glucose-based media using the yeast strain Rhodosporidium toruloides has been considered. Biodiesel production was based on the exploitation of either direct transesterification (without extraction of lipids from microbial biomass) or indirect transesterifaction of extracted microbial oil. When glucose-based renewable resources are used as carbon source for an annual production capacity of 10,000 t microbial oil and zero cost of glucose (assuming development of integrated biorefineries in existing industries utilising waste or by-product streams) the estimated unitary cost of purified microbial oil is $3.4/kg. Biodiesel production via indirect transesterification of extracted microbial oil proved more cost-competitive process compared to the direct conversion of dried yeast cells. For a price of glucose of $400/t oil production cost and biodiesel production cost are estimated to be $5.5/kg oil and $5.9/kg biodiesel, correspondingly. Industrial implementation of microbial oil production from oleaginous yeast is strongly dependent on the feedstock used and on the fermentation stage where significantly higher productivities and final microbial oil concentrations should be achieved.

United Nations Conference on New and Renewable Sources of Energy: its relevance for CDCC Member States

Includes bibliography

Renewable energy sources in Latin America and the Caribbean: situation and policy proposals

Includes bibliography

Coping and adaptation against decreasing fish resources : case study of fishermen in Lake Inle, Myanmar

Fishermen depend on Lake Inle in Myanmar for their livelihood. However, the lake has been undergoing environmental degradation over the years. Adding to the long-term decrease in the catch because of this degradation, these fishermen faced extremely low water levels in 2010, which they had previously not experienced. Based on field surveys, this paper aims to reveal how fishermen adapted and coped with the changing environment as well as the sudden shock of the abnormally low water levels.

Heterogeneous catalysts for converting renewable feedstocks to fuels and chemicals

The combination of dwindling oil reserves and growing concerns over carbon dioxide emissions and associated climate change is driving the urgent development of routes to utilise renewable feedstocks as sustainable sources of fuel and chemicals. Catalysis has a rich history of facilitating energy-efficient selective molecular transformations and contributes to 90% of chemical manufacturing processes and to more than 20% of all industrial products. In a post-petroleum era, catalysis will be central to overcoming the engineering and scientific barriers to economically feasible routes to biofuels and chemicals. This chapter will highlight some of the recent developments in heterogeneous catalytic technology for the synthesis of fuels and chemicals from renewable resources, derived from plant and aquatic oil sources as well as lignocellulosic feedstocks. Particular attention will be paid to the challenges faced when developing new catalysts and importance of considering the design of pore architectures and effect of tuning surface polarity to improve catalyst compatibility with highly polar bio-based substrates.