Break-even price of distributed generation under uncertainty

Optimal investment strategies in decentralized renewable power generation under uncertainty

“…Much of the present literature on investment in distributed generation (e.g. [2,3]) takes the utility and societal perspective and focuses on wider system benefits. This paper instead takes the perspective of a building owner who wants to maximize private profits, with a building that consumes electricity and has a renewable resource available.…”

“…constant in option value function around and at difference point B 2 constant in option value function around and at difference point F j (S) value of the investment opportunity before investing in plant j ($) G Di annual power generation that displaces the electricity load for unit i (MWh/y) G Ei annual power generation that are exported for unit i (MWh/y) K Di correction factor for the annual average price of displaced electricity for project i K Ei correction factor for the average price exports receive for project i NPV(S) net present value of the most profitable capacity ($) P Di,t (S) annual effective price of displaced electricity load for unit i ($/MWh) P Ei,t (S) annual effective export price for unit i ($/MWh) S electricity start price adjusted for short-term deviations ($/MWh) V j (S) value of unit j after investment and in perpetuity ($) Z j optimal investment interval for power generating unit j ($/MWh) g Di,h hourly substituted electricity load for unit i (MWh) g Ei,h hourly power generation for exports for project i (MWh) Displaced electricity is valued at a retail price (including grid tariffs and taxes), and exported electricity is valued at a price close to the wholesale price. The model we develop can also be applied to cases with different metering regulations such as net metering, where the retail price is received also for the generated power that does not coincide with the building load.…”

A fuzzy levelised energy cost method for renewable energy technology assessment

“…Fixed discount rates are commonly utilised in financial decision support systems within the energy discipline (Bakken et al, 2007;Messineo et al, 2012;van Dyken et al, 2010) despite these issues which may be due to the lack of forecasting information available. Previous research has also attempted to study the effect of a stochastic discount rate with a 'normal' distribution on the break-even price of a project (Ang et al, 1999). However, the discount rate remains static over the duration of the project lifecycle and utilises an estimated standard deviation.…”

“…The plant is estimated to operate at 90% availability which results in 7800MWhe/pa, although this could in the worst case scenario fall to 7000MWhe/pa or in the best case be 8000MWhe/pa. As in Ang et al (1999), a range of possible discount rates are applied over the operational lifecycle but with a fuzzy distribution as an alternative to the probabilistic one applied in their research. Finally, as used as the upper cost estimate in IEA/NEA (2010), the decommission costs of the plant are estimated to be 10% of the investment cost and are distributed over the last 10 years of the plants operational life.…”

“…Previous research has only limitedly mitigated this in the absence of data, by probabilistically deviating from a fixed mean value, typically with a 'normal' distribution (Ang et al, 1999;Mancini, 2010, 2011). Darling et al (2011) also utilised Monte-Carlo simulation to probabilistically produce a distribution of LEC outputs in their Solar Advisor Model (SAM).…”