Methodology for integrated modelling and impact assessment of city energy system scenarios

Cities are ought to play a key role in the energy transition to a low carbon society as they concentrate more than half of the world's population and are responsible for about 67% primary energy consumption and around 70% of the energy-related CO2 emissions. To achieve the agreed climate targets, efficient urban planning is a must. Tools and methods have risen to model different aspects of the energy performance of urban areas. Nevertheless, addressing the complexity of a city energy system is a great challenge and new integrated tools and methods are still needed. This paper presents a methodology for integrated city energy modelling and assessment, from the characterization of the city's current energy performance to the development and assessment of future scenarios. Energy characterization is based on the combination of bottom-up approaches with top-down data to establish the city's energy baseline. This baseline integrates bottom-up results from a GIS based model which is used to characterize the city's building stock energy performance, while available information on the vehicle stock is used to model the mobility sector. Scenarios are developed from this baseline and assessed through a multi-criteria impact assessment model. A simplified case study is carried out for the city of Valencia (Spain) to demonstrate the suggested methodology, and results are shown for three different scenarios: one focused on the building sector, one on transport, and one combining measures in both sectors. The transport-focused scenario demonstrates to be the most favourable in terms of energy savings and emissions reductions. The application of the proposed method is intended to support the development of strategies and plans for energy transition at city level. The main challenges for its application in cities are data availability at urban level, the uncertainty related to modelling the transport sector, and the unavailability of adapted I/O tables at city scale to assess socioeconomic impacts

Rethinking Economic Growth Theory From a Biophysical Perspective

biophysical economics differential analysis ecological economics economic growth energy growth decoupling heterodox economics social metabolismNeoclassical growth theory is the dominant perspective for explaining economic growth. At its core are four implicit assumptions: 1) economic output can become decoupled from energy consumption; 2) economic distribution is unrelated to growth; 3) large institutions are not important for growth; and 4) labor force structure is not important for growth. Drawing on a wide range of data from the economic history of the United States, this book tests the validity of these assumptions and finds no empirical support. Instead, connections are found between the growth in energy consumption and such disparate phenomena as economic redistribution, corporate employment concentration, and changing labor force structure. The integration of energy into an economic growth model has the potential to offer insight into the future effects of fossil fuel depletion on key macroeconomic indicators, which is already manifested in stalled or diminished growth and escalating debt in many national economies. This book argues for an alternative, biophysical perspective to the study of growth, and presents a set of ‘stylized facts’ that such an approach must successfully explain. Aspects of biophysical analysis are combined with differential monetary analysis to arrive at a unique empirical methodology for investigating the elements and dependencies of the economic growth process. Book page on Springer's site: http://link.springer.com/book/10.1007%2F978-3-319-12826-9 DOI 10.1007/978-3-319-12826-

Risks to Global Trade and Implications for South Africa's Economy and Policy

The past two decades have witnessed an unprecedented globalisation of trade in goods and services. This process has been driven, inter alia, by technology, ideology and the availability of relatively cheap energy. By extrapolating this trend, one may expect further integration of world markets and increasingly unhindered international trade

Agricultural machinery selection and scheduling of farm operations

The procedure of calculating annual machinery ownership costs from the discounted cash flows of the mortgaged capital cost, the repair and insurance charges and the resale income is extended to include the effect of loan rate and loan period on interest charges, the effect of capital allowances taking account of the actual balancing charges at the end of the period of ownership, and the effect of tax relief on the interest charges, repair costs and insurance premiums. The concept of marginal holding cost is applied to determine the optimum ownership period.The selection of tractor- plough combinations is based on the prediction of soil characteristics such as moisture content, strength, and workability, all of which influencing the assessment of plough draught and tractor power. A number of filters are used to select the appropriate and realistic tractor /implement combinations with different sizes of fully mounted plough depending on the draught, and the speed of each selected gear of the tractor. For each acceptable combina- tion of tractor and fully mounted plough determined, the costing routine is used to calculate the annual costs.The branch and bound algorithm is suitable for mixed integer solutions to the farm machinery selection problem. Machinery sets are selected simultaneously with the chosen cropping pattern on a given land area. Machinery sets are matched correctly to the tractor sizes. Four sizes of tractor are available (45 kW, 61 kW, 74 kW and 94 kW,. Field operations take place in discrete time periods during which available work days are predicted from soil type and weather records for the specific site. Cereal and root crops are distinguished by optimum sowing and harvesting date. Discrete time periods are defined in relation to these optimal dates and give rise to overlapping operations for different crops. The calculation of probability levels for available work days when operations are subject to different criteria is discussed. A single arbitrary value of 75% probability for available work days is adopted in the linear programming model for the main part of the study.Two stage processes are used to simulate available work days in each time period. The patterns generated converge on the relative frequency pattern laid down by the generating process. The range of experience is wider than that contained in the short series of 24 years historical data. The simulation model generates results suitable for stochastic dominance ranking.In a simulation experiment on a 250 ha arable farm cropping cereals and potatoes, alternative solutions are obtained by integer linear programming, the solutions being ranked according to gross revenue. Annual costs of operating farm machinery are derived from a separate costing algorithm based on the annual hours of use which are determined by the size of the task and not by the sequence of work days. After deducting the annual costs of machinery operation, the cumulative net revenue curves cross and second order stochastic dominance ranking is used to identify the optimum (maximum profit) solution.The current study demonstrates the viability of the analytical procedures but further work is now required to reduce the computing time involved for the complete machinery selection procedure. Meanwhile, a commercial software package is prepared on the calculation of annual machinery ownership costs

Plug-in hybrid and battery electric vehicles in South Africa: market forecasts

This paper uses diffusion modeling to forecast the sales of Plug-in Hybrid and Battery Electric Vehicles (PH/BEVs) in South Africa. First the potential benefits of PH/BEVs in South Africa are scrutinized. The global PH/BEV market is analyzed along with the goals and enticement policies of the countries that are best positioned for a widespread uptake of PH/BEVs. The supply and demand challenges facing the market for PH/BEVs in South Africa are evaluated with a review of current and proposed public policies. The total sales of PH/BEVs in South Africa are then forecast for the medium and long term using an adapted multiple technology generation Bass model with variable parameters for vehicle purchase price and running cost. Two scenarios are examined involving varying oil prices, electricity prices, government support and PH/BEV technological development