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A geospatial comparison of distributed solar heat and power in Europe and the US.

ABSTRACT: The global trends for the rapid growth of distributed solar heat and power in the last decade will likely continue as the levelized cost of production for these technologies continues to decline. To be able to compare the economic potential of solar technologies one must first quantify the types and amount of solar resource that each technology can utilize; second, estimate the technological performance potential based on that resource; and third, compare the costs of each technology across regions. In this analysis, we have performed the first two steps in this process. We use physical and empirically validated models of a total of 8 representative solar system types: non-tracking photovoltaics, 2d-tracking photovoltaics, high concentration photovoltaics, flat-plate thermal, evacuated tube thermal, concentrating trough thermal, concentrating solar combined heat and power, and hybrid concentrating photovoltaic/thermal. These models are integrated into a simulation that uses typical meteorological year weather data to create a yearly time series of heat and electricity production for each system over 12,846 locations in Europe and 1,020 locations in the United States. Through this simulation, systems composed of various permutations of collector-types and technologies can be compared geospatially and temporally in terms of their typical production in each location. For example, we see that silicon solar cells show a significant advantage in yearly electricity production over thin-film cells in the colder climatic regions, but that advantage is lessened in regions that have high average irradiance. In general, the results lead to the conclusion that comparing solar technologies across technology classes simply on cost per peak watt, as is usually done, misses these often significant regional differences in annual performance. These results have implications for both solar power development and energy systems modeling of future pathways of the electricity system.

SUBMITTER: Norwood Z

PROVIDER: S-EPMC4256299 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:This paper examines the cost and benefits, both financial and environmental, of two leading forms of solar power generation, grid-tied photovoltaic cells and Dish Stirling Systems, using conventional carbon-based fuel as a benchmark. METHODS:First we define how these solar technologies will be implemented and why. Then we delineate a model city and its characteristics, which will be used to test the two methods of solar-powered electric distribution. Then we set the constraining assumptions for each technology, which serve as parameters for our calculations. Finally, we calculate the present value of the total cost of conventional energy needed to power our model city and use this as a benchmark when analyzing both solar models' benefits and costs. RESULTS:The preeminent form of distributed electricity generation, grid-tied photovoltaic cells under net-metering, allow individual homeowners a degree of electric self-sufficiency while often turning a profit. However, substantial subsidies are required to make the investment sensible. Meanwhile, large dish Stirling engine installations have a significantly higher potential rate of return, but face a number of pragmatic limitations. CONCLUSIONS:This paper concludes that both technologies are a sensible investment for consumers, but given that the dish Stirling consumer receives 6.37 dollars per watt while the home photovoltaic system consumer receives between 0.9 and 1.70 dollars per watt, the former appears to be a superior option. Despite the large investment, this paper deduces that it is far more feasible to get few strong investors to develop a solar farm of this magnitude, than to get 150,000 households to install photovoltaic arrays in their roofs. Potential implications of the solar farm construction include an environmental impact given the size of land require for this endeavour. However, the positive aspects, which include a large CO2 emission reduction aggregated over the lifespan of the farm, outweigh any minor concerns or potential externalities.

Project description:ObjectiveThe objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior solution can be found, and 3) develop a scalable algorithm that guarantees the convergence to a local minimum.Existing challengesDue to the nonconvexity of the problem, the search for a solution to OPF problems is not scalable, which makes the OPF highly limited for the system operation of large-scale real-world power grids-"the curse of dimensionality". The recent attempts at distributed computation aim for a scalable and efficient algorithm by reducing the computational cost per iteration in exchange of increased communication costs.MotivationA new network model allows for efficient computation without increasing communication costs. With the network model, recent advancements in distributed computation make it possible to develop an efficient and scalable algorithm suitable for large-scale OPF optimizations.MethodsWe propose a new network model in which all nodes are directly connected to the center node to keep the communication costs manageable. Based on the network model, we suggest a nodal distributed algorithm and direct communication to all nodes through the center node. We demonstrate that the suggested algorithm converges to a local minimum rather than a point, satisfying the first optimality condition.ResultsThe proposed algorithm identifies solutions to OPF problems in various IEEE model systems. The solutions are identical to those using a centrally optimized and heuristic approach. The computation time at each node does not depend on the system size, and Niter does not increase significantly with the system size.ConclusionOur proposed network model is a star network for maintaining the shortest node-to-node distances to allow a linear information exchange. The proposed algorithm guarantees the convergence to a local minimum rather than a maximum or a saddle point, and it maintains computational efficiency for a large-scale OPF, scalable algorithm.

Project description:The inherent intermittency of solar power due to diurnal and seasonal cycles has usually resulted in the need for alternative generation sources thereby increasing system operation costs. However, when solar power is spread over a large geographical area with significant time differences, the intermittency can be significantly reduced and also the electricity market balancing cost. The aim of this article is to address the fundamental scientific question on how the intermittency of solar power generation is affected by aggregation, which is of great interest in the wider power and energy community and would have profound impacts on the solar energy integration into the energy supply and Net-Zero Implementation. This article goes beyond the typical regional analysis by investigating solar power intermittency at 5 aggregation levels from a global perspective based on global 7 year hourly meteorological re-analysis data with a fine spatial resolution of [Formula: see text]. In the proposed assessment framework, a coefficient of variation (CV) is used to quantify solar power intermittency and hence characterize the potential benefits of wide area solar power aggregation. A duration curve is used to characterize the intermittency in terms of power availability and a probability density function is further employed to investigate the dispersion and scaling behavior of CV at different aggregation levels. The findings indicate that the CV of solar power generation of 'Inner Mongolia' in China drops from 129.65 to 105.65% in the level of 'Asia' (by 24% decrease), to 56.11% in 'Asia-North_America' (by 73.54% decrease) and to the smallest 43.50% in 'Global' (by 86.15% decrease), nearly 3.5 times of that in 'Asia'; (b) the availability of solar power generation increases from 52.17% in Germany, to 73.30% in 'Europe_EU_plus', to 77.82% in 'Europe', to 98.59% in 'Europe-North_America' (80.60% in 'Europe-Africa', 96.90% in 'Europe-Asia'), to 100% in 'Global'. Finally, conclusions and recommendations are provided to support a Net-Zero strategy.

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A geospatial comparison of distributed solar heat and power in Europe and the US.

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