A dynamic model for distributed energy resource expansion planning considering multi-resource support schemes

Fini, Alireza Sheikhi; Moghaddam, Mohsen Parsa; Sheikh‐El‐Eslami, Mohammad Kazem

doi:10.1016/j.ijepes.2014.03.030

Cited by 25 publications

(7 citation statements)

References 30 publications

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“…This value is considered as a random variable and the Gaussian distribution function represents its stochastic nature with standard deviation and expected value equal to 1% and 1.2%, respectively [7]. In this paper, the weekly demand is calculated by (1) [11].…”

Section: A Electricity Demandmentioning

confidence: 99%

“…IRR i (t) D rate (9) İi(t) = SCL 1 + e −(βs i ×PIt i (t)+γ i ) × (RCR i (t) + CAR i (t)) (10) RCR i (t) = P i (t) T i age (11) in which, IRR is the internal rate of return (%/yr), PIt is the profitability index of technology, Drate is adjusted discount rate (%/yr), İ is investment rate of technology (MW/yr), RCR is retired capacity rate of technology (MW/yr), P is installed capacity (MW), T age is the lifetime of each unit (yr), and CAR is capacity addition rate of technology to cover the maximum demand (MW/yr). The capacity addition rate of technology for supplying the maximum demand depends on the demand growth rate.…”

Section: Pit I (T) =mentioning

confidence: 99%

“…In [10], a system dynamic model was utilized to study the effect of different capacity mechanisms on market behavior. The effect of incentives on the development of distributed energy resources in an electricity market was studied by the market dynamic model in [11]. Various dynamic models were proposed to study different countries' electricity market behavior in Colombia [12], Sweden [13], and China [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Effect of Ratio-Based Incentive on Wind Capacity Development and Investment Risk of Wind Units: A System Dynamics Approach

Esmaeili

Anvari‐Moghaddam

2021

IEEE Access

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Different capacity incentives like feed-in-tariff have been considered to encourage companies to invest in wind power units. One of the main challenges of the electricity market policymakers is the determination of this fixed payment based on limited funding in a way that the investment cost of wind units is compensated and the associated investment risk is reduced. The main contribution of this paper is the introduction of a method to manage the amount of payment or incentives during a time horizon to reach the targeted wind capacity and reduce its investment risk. In this regard, the ratio-based incentive is introduced.To study the effects of such a policy, the long-term behavior of the electricity market is simulated by a dynamic model, which is a useful tool for policymakers to analyze the effects of their policies. Then, conditional value at risk and value at risk concepts are used to measure the risk of wind capacity investment. The results illustrate that the ratio-based incentive is more effective than the feed-in-tariff in the context of decreasing the risk of investment, reducing total CO2 production, electricity price reduction, and speed of providing higher amounts of wind capacity.

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Section: A Electricity Demandmentioning

confidence: 99%

Section: Pit I (T) =mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Effect of Ratio-Based Incentive on Wind Capacity Development and Investment Risk of Wind Units: A System Dynamics Approach

Esmaeili

Anvari‐Moghaddam

2021

IEEE Access

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“…So it is obvious that the power structure adjustment has nonlinear characteristics. The system dynamics (SD) method not only models the market's real behavior but also properly explains the relationship between the main variables of the system [15]. Considering the advantages of integrity and dynamics that system dynamics has in analyzing complex dynamic problems, this paper set up a complete system dynamics model by analyzing: the air pollution emitted during coal combustion, coal washing technology, installed capacity, unit transform, and new energy power generation, under the constraint of the new atmospheric pollutant emission policy, to seek a development pattern for the thermal coal supply chain.…”

Section: Introductionmentioning

confidence: 99%

“…Some scholars have set up an SD-based model to investigate the distributed energy resource expansion planning [15][16][17] and energy efficiency improvement [18], considering both energy states and production constraints. Other scholars use SD methodology to simulate the behavior of the renewable energy sectors such as nuclear [19] and photovoltaic energy [20].…”

Section: Introductionmentioning

confidence: 99%

Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China

Guo

Yuan

2014

Sustainability

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Spurred by the increasingly serious air pollution problem, the Chinese government has launched a series of policies to put forward specific measures of power structure adjustment and the control objectives of air pollution and coal consumption. Other policies pointed out that the coal resources regional blockades will be broken by improving transportation networks and constructing new logistics nodes. Thermal power takes the largest part of China's total installed power generation capacity, so these policies will undoubtedly impact thermal coal supply chain member enterprises. Based on the actual situation in China, this paper figures out how the member enterprises adjust their business decisions to satisfy the requirements of air pollution prevention and control policies by establishing system dynamic models of policy impact transfer. These dynamic analyses can help coal enterprises and thermal power enterprises do strategic environmental assessments and find directions of sustainable development. Furthermore, the policy simulated results of this paper provide the Chinese government with suggestions for policy-making to make sure that the energy conservation and emission reduction policies and sustainable energy policies can work more efficiently.

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A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

2019

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Summary Generation expansion planning (GEP) is a power plant mix problem that identifies what, where, when, and how new generating facilities should be installed and when old units be retired over a specific planning horizon. GEP ensures that the quantity of electricity generated matches the electricity demand throughout the planning horizon. This kind of planning is of importance because most production and service delivery is dependent on availability of electricity. Over the years, the traditional GEP approaches have evolved to produce more realistic models and new solution algorithms. For example, with the agitation for green environment, the inclusion of renewable energy plants and energy storage in the traditional GEP model is gradually gaining attention. In this regards, a handful of research has been conducted to identify the optimal expansion plans based on various energy‐related perspectives. The appraisal and classification of studies under these topics are necessary to provide insights for further works in GEP studies. This article therefore presents a comprehensive up‐to‐date review of GEP studies. Result from the survey shows that the integration of demand side management, energy storage systems (ESSs), and short‐term operational characteristics of power plants in GEP models can significantly improve flexibility of power system networks and cause a change in energy production and the optimal capacity mix. Furthermore, this article was able to identify that to effectively integrate ESS into the generation expansion plan, a high temporal resolution dimension is essential. It also provides a policy discussion with regard to the implementation of GEP. This survey provides a broad background to explore new research areas in order to improve the presently available GEP models.

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A dynamic model for distributed energy resource expansion planning considering multi-resource support schemes

Cited by 25 publications

References 30 publications

The Effect of Ratio-Based Incentive on Wind Capacity Development and Investment Risk of Wind Units: A System Dynamics Approach

The Effect of Ratio-Based Incentive on Wind Capacity Development and Investment Risk of Wind Units: A System Dynamics Approach

Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China

A comprehensive state‐of‐the‐art survey on power generation expansion planning with intermittent renewable energy source and energy storage

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