An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment

Lin, Whei-Min; Yang, Chung-Yuen; Tu, Chia-Sheng; Tsai, Ming-Tang

doi:10.3390/en11061423

Cited by 8 publications

(6 citation statements)

References 32 publications

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“…Financial risk assessment techniques are being increasingly used in the field of power systems to manage renewable energy risks in generation planning and electricity markets [23]. The Markowitz mean‐variance theory [24], value at risk (VaR) [25] and Sortino ratio [22] are examples of financial risk measurement tools that have been tested in power systems. The conditional value at risk (CVaR) is another measure which has performed better than the VaR.…”

Section: Introductionmentioning

confidence: 99%

Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto‐optimal profits for the utility and prosumers

Mohan

Antonis

Jisma

et al. 2022

Energy Conversion and Econom

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The increasing penetration of renewable energy sources (RES) and electric vehicles (EVs) demands the building of a microgrid energy portfolio that is cost‐effective and robust against generation uncertainties (energy risk). Energy risk may trigger financial risk in the local energy market, depending on bid values, cost of generation and price of upstream grid power. In this study, a microgrid energy portfolio is built based on adjustments to both the financial and energy risks. These risks are managed in two ways: (1) by pre‐tuning and prioritizing the bid prices for wind and solar energy sources based on their relative levels of energy risk as quantified through a conditional value‐at‐risk (CVaR) approach; and (2) by co‐optimizing the conflicting profits of the utility and prosumers using non‐dominated sorting particle swarm optimization (NSPSO) to obtain a risk‐adjusted Pareto‐optimal energy mix. Thus, the utility predicts the net power balancing cost from the scheduling time horizon, thereby moderating the adverse effect that the uncertainties in renewable energy could have on the collective welfare. The proposed method is tested on a grid‐connected CIGRE low‐voltage (LV) benchmark microgrid with solar and wind sources, microturbines, and EVs. The results demonstrate that the obtained portfolio is realistic, welfare‐optimized and cost‐efficient.

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Section: Introductionmentioning

confidence: 99%

Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto‐optimal profits for the utility and prosumers

Mohan

Antonis

Jisma

et al. 2022

Energy Conversion and Econom

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“…Impact on the financial and technical aspects of running the power system under conditions of financial risk based on the behaviour of other players in the market was given in [20] where it was shown that the greatest financial profit of 10498.98 currency units for the case is achieved when the production of the solar power plants and the wind farms is managed under a single aggregator. Two scenarios for the microgrids with RES and electricity storage under the influence of risk are given in [21] where the author specifically considered the rate of change in solar radiation and wind speed between the two time periods, further examining the system's resistance to sudden changes. Operation of the virtual power plant consisted of wind power, solar power, battery and diesel power under the conditions of the financial risks affecting its daily profit were explored in [22].…”

Section: Introductionmentioning

confidence: 99%

A robust risk assessment method for energy planning scenarios on smart islands under the demand uncertainty

Mimica

Urtasun

Krajačić

2022

Energy

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“…Although optimization methods and control theories are applied in power systems to improve safety and stability [10,11], risks are still inevitable in the operation of the power grids. A generalized concept of risk is the product of the probability and consequences of the contingency.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment for the Power Grid Dispatching Process Considering the Impact of Cyber Systems

et al. 2019

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Power grid dispatching is a high-risk process, and its execution depends on an available cyber system. However, the effects of cyber systems have not caught enough attention in current research on risk assessments in dispatching processes, which may cause optimistic risk results. In order to solve this problem, this paper proposes a risk assessment model that considers the impact of a cyber system on power grid dispatching processes. Firstly, a cyber-physical switchgear state model that integrates the reliability states of both cyber system functions and switchgears is proposed, based on the transition of switchgear states in the dispatching process. Then, the potential effects of each operating step on power grid states are analyzed considering the failure model of cyber-physical system (CPS) components. The risk probabilities and consequences of the power grid states are calculated to quantify the risk index. Finally, the workings and effectiveness of this model are illustrated using the IEEE Reliability Test System-1979.

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An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment

Cited by 8 publications

References 32 publications

Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto‐optimal profits for the utility and prosumers

Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto‐optimal profits for the utility and prosumers

A robust risk assessment method for energy planning scenarios on smart islands under the demand uncertainty

Risk Assessment for the Power Grid Dispatching Process Considering the Impact of Cyber Systems

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