The use of hourly prices in distributed photovoltaic (PV) techno-economic analysis is rare, but may become necessary as time-of-day retail pricing becomes more common. A methodology is presented for selecting an hourly price curve suitable for long-term analysis, called the typical price year (TPY), which is based on the methodology for TMY weather data. Using a techno-economic analysis with annual revenues and net present value as indicators, a TPY curve for the Swedish market is validated and then compared to 18 price simplification methods to determine the error introduced by the use of non-hourly prices. Results show that the TPY method produces a curve which accurately represents long term pricing trends, but using a static annual mean introduces minor revenue errors of 1.3%. This suggests the TPY may not be necessary in the Swedish market, but further analysis of the method is suggested for other markets.

The market for solar photovoltaic systems is growing rapidly into a mature industry, while at the same time policies which have spurred the growth (e.g. feed-in tariffs or net metering) are beginning to fade away. These policies made techno-economic studies relatively simple for engineers, analysts, and owners, however investing in a deregulated market requires more advanced tools than the traditional engineering economics which dominate the literature. The objective of part one in this paper is to catalogue and critique the range of methods and models relevant to techno-economic analysis for PV systems in the context of distributed, grid-connected buildings. This is accomplished by; developing a system modeling framework for prosumer PV investment analysis, reviewing relevant energy, economics, and finance literature to identify mathematical models which can be applied, and cataloging the use of the reviewed techniques in the relevant literature. Also included is a qualitative discussion of the benefits and practicality of the review techniques, where Monte Carlo analysis is highlighted as an exemplary method. This review is useful as a reference for analysts, researchers, and engineers developing PV integration solutions for building energy systems in a post early adopter PV market.

Part One in this two part paper identified Monte Carlo analysis as an improved approach over traditional deterministic techno-economic methods for solar PV prosumers in deregulated markets. In this paper a novel Monte Carlo methodology is described and demonstrated through a case study for the Swedish residential sector, which includes a review of relevant market, climate, and policy conditions, their use in determining inputs, and the probabilistic results. The probability of profitability (PoP) is introduced as an indicator in conjunction with result distributions. The results show that under current policy conditions, Swedish PV investors with well positioned buildings have a 71% chance of making a 3% real return on investment, and virtually no chance of losing their original investment. Without subsidies the PoP drops to 8%. In none of the simulated cases was any of the original investment lost. The PoP is most sensitive to the capital subsidy and the uncertainty of market based, long-term support is less critical to the chances of a successful investment. Given the current market conditions, Swedish PV prosumers can expect a return on investment. The decision to install will also depend on the probability of achieving their desired profitability, which Monte Carlo analysis quantifies well.

The electrification of buildings is a promising pathway to the decarbonization of cities. This is a parametric study of the technical and economic performance of ground source heat pump (GSHP) systems with series connected solar PV/thermal (PVT) collectors. The focus is on multi-family houses (MFH) in the heating dominated climate of Sweden, where land restrictions for boreholes or noise restrictions on air heat exchangers limit the heat pump market. System efficiency and lifecycle cost results are generated using a holistic and detailed systems model in TRNSYS with 20 year simulations. The results show that PVT can reduce borehole length by 18% or spacing by 50% while maintaining an equivalent seasonal performance factor to systems without PVT. The cost for PVT + GSHP systems is higher than a traditionally designed PV + GSHP, however this does not take into account the value of the land area saved by PVT, which can be up to 89%. The reduction in land enabled by PVT has the potential to increase penetration of GSHP in MFH and promote solar energy diffusion in high latitude markets.