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Abstract In this paper the Selective Modal Analysis (SMA) method is used for reproducing the eigenvalues involved in subsynchronous control interactions (SSCI) between DFIG-based wind farms and series compensated transmission lines. The SMA method provides a reduced system matrix containing a desired part of the eigenstructure of a system without computing the eigenvalues and eigenvectors of the full system. The key concept for obtaining such reduced matrix resides in an appropriate identification of a subset of state variables and eigenvalues of the system. The intrinsic problems in identifying the corresponding subset for analyzing the SSCI phenomenon are explored and illustrated using a simplified radial system. In addition, a systematic approach for obtaining a subset with minimum dimension is proposed. The methodology consists in a two-phase iterative procedure that reduces the computational load and promotes the convergence of the SMA method to the desired eigenstructure. The proposed algorithm is validated on a relative large power system derived from a practical network.

Abstract In this paper the Selective Modal Analysis (SMA) method is used for reproducing the eigenvalues involved in subsynchronous control interactions (SSCI) between DFIG-based wind farms and series compensated transmission lines. The SMA method provides a reduced system matrix containing a desired part of the eigenstructure of a system without computing the eigenvalues and eigenvectors of the full system. The key concept for obtaining such reduced matrix resides in an appropriate identification of a subset of state variables and eigenvalues of the system. The intrinsic problems in identifying the corresponding subset for analyzing the SSCI phenomenon are explored and illustrated using a simplified radial system. In addition, a systematic approach for obtaining a subset with minimum dimension is proposed. The methodology consists in a two-phase iterative procedure that reduces the computational load and promotes the convergence of the SMA method to the desired eigenstructure. The proposed algorithm is validated on a relative large power system derived from a practical network.

Abstract In the Swiss canton of Geneva, an energy efficiency portfolio has been operated since 2009. In contrast, such programs have been in place for more than 40 years in the US. There are numerous lessons to be learnt from their experience. We have therefore conducted a comparative analysis including Geneva and 11 leading states in the US, with the objective to identify explanatory factors for the success of energy efficiency programs. First, we compared total investment in energy efficiency programs between 2006 and 2015 and public policies related to energy efficiency in each state. Second, we analyzed the levelized cost of saved energy (LCSE) of the programs from the perspective of program administrators. Our cost-effectiveness analysis showed that the program investment scale has been strongly influenced by i) the existence of public mandates, which require program administrators to set ambitious targets and maximize their investment in cost-effective energy efficiency measures, ii) financial instruments that ensure program expenditure to be recovered, and iii) complementary funding from other programs. Moreover, learning and accumulated experience of the program administrators allow to reduce the LCSE. We conclude that the combination of financial instruments with public mandates can ensure a high level of effectiveness.

Abstract In the Swiss canton of Geneva, an energy efficiency portfolio has been operated since 2009. In contrast, such programs have been in place for more than 40 years in the US. There are numerous lessons to be learnt from their experience. We have therefore conducted a comparative analysis including Geneva and 11 leading states in the US, with the objective to identify explanatory factors for the success of energy efficiency programs. First, we compared total investment in energy efficiency programs between 2006 and 2015 and public policies related to energy efficiency in each state. Second, we analyzed the levelized cost of saved energy (LCSE) of the programs from the perspective of program administrators. Our cost-effectiveness analysis showed that the program investment scale has been strongly influenced by i) the existence of public mandates, which require program administrators to set ambitious targets and maximize their investment in cost-effective energy efficiency measures, ii) financial instruments that ensure program expenditure to be recovered, and iii) complementary funding from other programs. Moreover, learning and accumulated experience of the program administrators allow to reduce the LCSE. We conclude that the combination of financial instruments with public mandates can ensure a high level of effectiveness.

Escalating energy costs are an increasing concern for South Asian farmers growing rice and wheat in rotation. Millions of people in the IGP (Indo-Gangetic Plains) depend on this cropping system for food and income security. CT (conservation tillage) practices, including mechanical BP (bed planting), PTOS (power-tiller operated seeding), and ST (strip tillage), are advocated by donors and development organizations as profitable, high yielding, and energy-efficient alternatives to TT (traditional tillage). However, most studies on the EUE (energy input use efficiency) of CT originate from researcher-controlled and on-station experiments. Comparatively little information is available on the EUE of CT practices as farmers apply them in their own fields, and under their own management decisions. This research responds to this gap, and analyzes EUE of each of these three CT options, compared to TT, by surveying 328 rice-wheat farmers in north-western Bangladesh. Concentrating on wheat production, we employed a non-parametric benchmarking technique involving slack-based measures of technical efficiency, along with a fractional regression model to identify and compute the wasteful use of energy. PTOS achieved the highest EUE score (0.92), followed closely by BP and ST (both 0.91), whereas TT (0.68) was significantly (p <0.001) different and lower than the CT practices.

Escalating energy costs are an increasing concern for South Asian farmers growing rice and wheat in rotation. Millions of people in the IGP (Indo-Gangetic Plains) depend on this cropping system for food and income security. CT (conservation tillage) practices, including mechanical BP (bed planting), PTOS (power-tiller operated seeding), and ST (strip tillage), are advocated by donors and development organizations as profitable, high yielding, and energy-efficient alternatives to TT (traditional tillage). However, most studies on the EUE (energy input use efficiency) of CT originate from researcher-controlled and on-station experiments. Comparatively little information is available on the EUE of CT practices as farmers apply them in their own fields, and under their own management decisions. This research responds to this gap, and analyzes EUE of each of these three CT options, compared to TT, by surveying 328 rice-wheat farmers in north-western Bangladesh. Concentrating on wheat production, we employed a non-parametric benchmarking technique involving slack-based measures of technical efficiency, along with a fractional regression model to identify and compute the wasteful use of energy. PTOS achieved the highest EUE score (0.92), followed closely by BP and ST (both 0.91), whereas TT (0.68) was significantly (p <0.001) different and lower than the CT practices.

A recent addition to the anthropogenic sources of underwater noise is offshore wave energy converters. Underwater noise was recorded from the Wavestar wave energy converter located at Hastholm, Denmark (57°7.73´N, 8°37.23´E). The Wavestar is a full-scale test and demonstration converter of the absorber type. During recordings the converter was operating close to maximum power output (nominal capacity of 110 kW). During operation the independently operating absorbers float semi-submerged in the water and wave-generated up-and-down motion is converted into hydraulic pressure by means of pistons connected to the arms of the absorbers. The hydraulic pressure then in turn drives the generator. A 57 minute sequence of noise from the converter was recorded by a Loggerhead datalogger deployed in 7 m deep water 25 m from the converter. This sequence contained recordings of ambient noise, the converter in full operation and start and stop of the converter. Median broad band (10 Hz – 20 kHz) sound pressure level (Leq) was 123 dB re. 1 Pa, irrespective of status of the wave energy converter (stopped, running or starting/stopping). The most pronounced peak in the third-octave spectrum was in the 160 Hz band during start and stop of the converter, attributed to the hydraulic pump responsible for lifting and lowering the absorbers. Less pronounced, but still statistically significant differences were seen in the bands 125, 160, 200 and 250 Hz when operation and ambient were compared. No statistically significant noise above ambient could be detected above the 250 Hz band. The absolute increase in noise above ambient was very small. L50 third-octave levels in the four bands with the converter running were thus only 1-2 dB above ambient L50 levels.The noise recorded 25 m from the wave energy converter was barely detectable above ambient noise and only in the range 125-250 Hz. Harbour seals have good low frequency hearing and third-octave levels of the converter noise are well above their hearing threshold. Harbour seals are thus expected to be able to hear the converter noise, although the elevation in noise levels is so low (1-2 dB) that it is likely to be close to inaudible even at the close range where recordings were obtained. In contrast to seals, harbour porpoises have poor low frequency hearing and it seems unlikely that the converter noise would have been audible to porpoises. Wave energy converters come in different designs and work according to different principles. Other types of converters could be expected to be noisier, perhaps also to generate noise at other frequencies than those reported from the Wavestar. Therefore the conclusion that noise levels from the Wavestar are unlikely to affect seals and porpoises cannot be generalised. Nevertheless, the results clearly demonstrate that it is possible to harvest wave energy in a way which does not add substantially to the increasing levels of anthropogenic noise in the ocean.

A recent addition to the anthropogenic sources of underwater noise is offshore wave energy converters. Underwater noise was recorded from the Wavestar wave energy converter located at Hastholm, Denmark (57°7.73´N, 8°37.23´E). The Wavestar is a full-scale test and demonstration converter of the absorber type. During recordings the converter was operating close to maximum power output (nominal capacity of 110 kW). During operation the independently operating absorbers float semi-submerged in the water and wave-generated up-and-down motion is converted into hydraulic pressure by means of pistons connected to the arms of the absorbers. The hydraulic pressure then in turn drives the generator. A 57 minute sequence of noise from the converter was recorded by a Loggerhead datalogger deployed in 7 m deep water 25 m from the converter. This sequence contained recordings of ambient noise, the converter in full operation and start and stop of the converter. Median broad band (10 Hz – 20 kHz) sound pressure level (Leq) was 123 dB re. 1 Pa, irrespective of status of the wave energy converter (stopped, running or starting/stopping). The most pronounced peak in the third-octave spectrum was in the 160 Hz band during start and stop of the converter, attributed to the hydraulic pump responsible for lifting and lowering the absorbers. Less pronounced, but still statistically significant differences were seen in the bands 125, 160, 200 and 250 Hz when operation and ambient were compared. No statistically significant noise above ambient could be detected above the 250 Hz band. The absolute increase in noise above ambient was very small. L50 third-octave levels in the four bands with the converter running were thus only 1-2 dB above ambient L50 levels.The noise recorded 25 m from the wave energy converter was barely detectable above ambient noise and only in the range 125-250 Hz. Harbour seals have good low frequency hearing and third-octave levels of the converter noise are well above their hearing threshold. Harbour seals are thus expected to be able to hear the converter noise, although the elevation in noise levels is so low (1-2 dB) that it is likely to be close to inaudible even at the close range where recordings were obtained. In contrast to seals, harbour porpoises have poor low frequency hearing and it seems unlikely that the converter noise would have been audible to porpoises. Wave energy converters come in different designs and work according to different principles. Other types of converters could be expected to be noisier, perhaps also to generate noise at other frequencies than those reported from the Wavestar. Therefore the conclusion that noise levels from the Wavestar are unlikely to affect seals and porpoises cannot be generalised. Nevertheless, the results clearly demonstrate that it is possible to harvest wave energy in a way which does not add substantially to the increasing levels of anthropogenic noise in the ocean.

Coherence in Photosynthesis It is unclear how energy absorbed by pigments in antenna proteins is transferred to the central site of chemical catalysis during photosynthesis. Hildner et al. (p. 1448 ) observed coherence—prolonged persistence of a quantum mechanical phase relationship—at the single-molecule level in light-harvesting complexes from purple bacteria. The results bolster conclusions from past ensemble measurements that coherence plays a pivotal role in photosynthetic energy transfer. Hayes et al. (p. 1431 , published online 18 April) examined a series of small molecules comprised of bridged chromophores that also manifest prolonged coherence.