Spatial Effects of Wind Generation and Its Implication for Wind Farm Investment Decisions in New Zealand

Abstract

Spill-over effects on electricity nodal prices associated with increased wind generation have not been examined in the literature. To examine these effects, we use spatial econometric models to estimate the direct and indirect effects of wind generation on nodal wholesale electricity prices. Spatial econometric models allow us to provide quantitative estimates of spill-over magnitudes and statistical tests for significance. Results show negative and significant effects are associated with increases in wind penetration, and the effect is stronger during peak hours and weaker during off-peak hours. Simulation results demonstrate net savings of NZ$8 million per MW of additional wind capacity installed at the CNI2 wind site. The findings provide valuable information on the evaluation of wind farm development in terms of site location, wholesale prices, and financial feasibility. Our approach also contributes to forecasting location specific wholesale electricity prices, and provides a better understanding of the implications of locating wind sites.

Levelized cost estimates of solar photovoltaic electricity in the United Kingdom until 2035

“…The merit order effect was calculated, for example, for Denmark, Germany, and Spain; 10 the Czech Republic; 11 and New Zealand. 12 Regardless of the approach taken and the renewable energy analyzed, however, the authors found a negative effect of higher renewable energy penetration on the wholesale market price of electricity. An exception is the solar PV technology in the Czech Republic, which is found to have a positive effect on wholesale electricity prices.…”

“…On the other hand, expansion of solar electricity generation in a market based on merit order (economic) dispatch can reduce the price of electricity in the wholesale market because the marginal cost of solar electricity generation is zero (merit order effect, examined for various European countries by, e.g., Welisch et al., 10 Luňáčková et al., 11 and Wen et al. 12 ). This reduction in wholesale electricity prices in the absence or reduction of economic support for solar projects can eventually transfer to electricity retail prices, helping to achieve the promise of clean and affordable electricity.…”

Partitioning for “Common but Differentiated” Precise Air Pollution Governance: A Combined Machine Learning and Spatial Econometric Approach

“…There are human factors in the setting of SWM, so that the results will be affected by different weight matrix settings [79]. To avoid the bias caused by SWM, we use the K-neighbor SWM and distance-neighbor SWM to conduct the robustness check.…”

The impact of COVID-19 containment measures on changes in electricity demand

“…We also expect the electricity price to fall since the electricity generated by low marginal cost technology can meet the low electricity demand based on the merit-order effect. That is, the cheapest form is dispatched first, and the most expensive conventional generation is dispatched last [11] . New Zealand responded to COVID-19 with a strong “go hard, go early” approach.…”