Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models

Han, Xinyan; Zhang, Hua; Yu, Xiaobao; Wang, Lina

doi:10.1016/j.apenergy.2016.10.008

Cited by 83 publications

(35 citation statements)

References 23 publications

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“…The profitability of ESS is verified only in eight case studies. This assumption is confirmed by the literature analysis [24,25], which confirms that the subsidies play a key-role in the feasibility of PV-integrated battery systems. The economic opportunities in this scenario are verified only when are verified three conditions: (i) a battery size double than PV plant capacity; (ii) a lifetime of ESS equal to 8 years; and, (iii) a substantial increase of the share of self-consumption.…”

Section: Sensitivity Analysissupporting

confidence: 77%

The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy

2017

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A solar photovoltaic system produces electricity by converting energy from the sun. By the end of 2016, the global installed solar photovoltaic capacity reached 305 GW. Its growth is impressive in the last years; in fact, it was only equal to 41 GW in 2010. However, Europe has installed only 6.9 GW in 2016 (−1.7 GW in comparison to previous year) and this annual power installed is equal to 9% of global one in according to data released by Solar Power Europe. The profitability of PV systems in mature markets depends on the harmonization between demanded energy and produced one residential energy storage when combined with photovoltaic panels is able to increase the share of self-consumption. This work proposes a mathematical model, in which a Discounted Cash Flow analysis is conducted to evaluate the financial feasibility of photovoltaic-integrated lead acid battery systems in Italy. The indicator used is Net Present Value. Furthermore, a break-even point analysis, in terms of an increase of self-consumption, is conducted. The residential sector is investigated and energy storage system investment is incentivized by fiscal deduction and regional subsidies. The analysis provides several case studies, determined by combinations of the following variables: photovoltaic plant size, battery capacity, the increase of the share of self-consumption, and the useful lifetime of energy storage system. The same case studies are proposed also in four alternative scenarios, where is the modified the structure of subsidies. Results confirm that the profitability can be reached in presence of subsidies.

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Section: Sensitivity Analysissupporting

confidence: 77%

The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy

2017

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“…Therefore, many different optimization models have been proposed for determining the cost optimal investment decisions and operation of building supply systems: either as Linear Programs (LP) [31,32] with the advantage of good computational tractability but the disadvantage of not being able to account for economies of scale; or as a Mixed Integer Linear Program (MILP) model [33][34][35][36][37][38][39]. Furthermore, two-level approaches that determine at least a part of investment decisions with a meta-heuristic solver and operation with a simulation or optimization are popular [40][41][42][43][44][45]. The last approach can account for very detailed physical models but no global optimal solution is guaranteed.…”

Section: Building Optimizationmentioning

confidence: 99%

Bottom-up energy supply optimization of a national building stock

Kotzur¹,

Markewitz²,

Robinius³

et al. 2020

Energy and Buildings

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The installation and operation distributed energy resources (DER) and the electrification of the heat supply significantly changes the interaction of the residential building stock with the grid infrastructure. Evaluating the mass deployment of DER at the national level would require analyzing millions of individual buildings, entailing significant computational burden.To overcome this, this work proposes a novel bottom-up model that consists of an aggregation algorithm to create a spatially distributed set of typical residential buildings from census data. Each typical building is then optimized with a Mixed-Integer Linear Program to derive its cost optimal technology adoption and operation, determining its changing grid load in future scenarios.The model is validated for Germany, with 200 typical buildings considered to sufficiently represent the diversity of the residential building stock. In a future scenario for 2050, photovoltaic and heat pumps are predicted to be the most economically and ecologically robust supply solutions for the different building types. Nevertheless, their electricity generation and demand temporally do not match, resulting in a doubling of the peak electricity grid load in the rural areas during the winter. The urban areas can compensate this with efficient co-generation units, which are not cost-efficient in the rural areas.

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“…where NPV max is the maximum NPV of the PV or PV‐BES system; B L,j , B G,j , and B S,j are the benefits from reducing the grid electricity fee, selling electricity to the grid ,and PV subsidies for the j ‐th year, respectively; C I,total are the total initial investment costs; C R(B),j’ and C R(inv),j” are the replacement costs of the battery and inverter for the j’ ‐th and j” ‐th years, respectively; and C OM,j and C E,j are the operational and maintenance cost and the cost of purchasing electricity from the grid for the j ‐th year, respectively. Although the NPV for a PV‐BES system will change with the PV size for a fixed ratio of PV size to BES size, there is a maximal NPV ( NPV max ) at a certain PV size.…”

Section: Methodsmentioning

confidence: 99%

“…The notion of net present value (NPV) is widely used in many papers, since the time dimension of the benefit and cost flows extends the lifespan of the project. [18][19][20] It is suitable for the PV-BES system because the social costs and benefits are considered in the overall life cycle. The equations for calculation of the NPV are as follows:…”

Section: Cost-benefit Models For a Pv-bes Systemmentioning

confidence: 99%

Economic analysis of an industrial photovoltaic system coupling with battery storage

et al. 2019

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Summary The Energy and Evaluation Special Committee of the China Price Association proposed two types of bill for battery energy storage (BES) subsidies in 2017: the first was that energy storage should be subsidised based on the initial installation capacity of BES system, while the second was that it should be subsidised based on the energy discharged by the BES system during the operational period. The economic benefits of a distributed photovoltaic (PV) system or a distributed system with PV and BES in the overall life cycle are discussed in the context of an industrial zone in Shanghai. The results suggest that the net present value (NPV) of a PV‐BES system with an optimised configuration is higher than the NPV of a PV system alone. The NPV of a distributed PV system with four different BESs is found to decrease in the order Li‐ion > NaS > VFB > Pb‐C because of the characteristics of their batteries. The NPVs of PV‐BES systems increase in equal proportion to the increase in the BES subsidy based on installation capacity for these four BES systems, while they show an inequable growth rate of earnings for the same BES subsidy based on the energy discharged over the operational period. The second bill for BES subsidy is more beneficial to the BES industry than the first, as it encourages higher pay for more work.

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Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models

Cited by 83 publications

References 23 publications

The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy

The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy

Bottom-up energy supply optimization of a national building stock

Economic analysis of an industrial photovoltaic system coupling with battery storage

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