Operating Strategy for Local-Area Energy Systems Integration Considering Uncertainty of Supply-Side and Demand-Side under Conditional Value-At-Risk Assessment

Shi, Jiaqi; Wang, Yingrui; Fu, Ruibin; Zhang, Jianhua

doi:10.3390/su9091655

Cited by 8 publications

(9 citation statements)

References 23 publications

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“…(1) Single objective. The most common single objective is the minimization of the total operation cost [10,11,13,15,18,[23][24][25][26][27][28]30,31,34,46]. (2) Multiple objectives with weights [19,20,32,44].…”

Section: Objectivesmentioning

confidence: 99%

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Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Georgilakis

2020

Energies

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The massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment introduces challenges for the optimal operation of the smart distribution network. Local energy markets at power distribution level are highly investigated in recent years. The aim of local energy markets is to optimize the objectives of market participants, e.g., to minimize the network operation cost for the distribution network operator, to maximize the profit of the private distributed energy resources, and to minimize the electricity cost for the consumers. Several models and methods have been suggested for the design and optimal operation of local energy markets. This paper introduces an overview of the state-of-the-art computational intelligence methods applied to the optimal operation of local energy markets, classifying and analyzing current and future research directions in this area.

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Section: Objectivesmentioning

confidence: 99%

“…Out of 41 reviewed papers, only 14 papers consider the alternating current (AC) power flow constraints at their optimization models [12,13,15,17,[29][30][31]34,35,38,40,41,43,46].…”

Section: Power Flow Constraintsmentioning

confidence: 99%

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Georgilakis

2020

Energies

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“…(3) Installed capacity constraints. Equation (10) means that the installed capacities of each type of power plant should be limited to the upper bound IC ub k :…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Due to its capability of improving reliability of performance and customers' responsiveness, as well as encouraging greater efficiency decisions by customers and the utility provider, smart grids can avoid electricity waste, thus reducing energy consumption and achieving carbon mitigation [9]. Shi et al [10] proposed an energy systems integration (ESI) operational scheduling model as an important form of a new energy system, which included the electrical, thermal and gas networks.…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China

2017

Sustainability

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Abstract:In order to solve problems caused by climate change, countries around the world should work together to reduce GHG (greenhouse gas) emissions, especially CO 2 emissions. Power demand takes up the largest proportion of final energy demand in China, so the key to achieve its goal of energy-saving and emission reduction is to reduce the carbon emissions in the power sector. Taking Shenzhen as an example, this paper proposed a stochastic optimization model incorporating power demand uncertainty to plan the carbon mitigation path of power sector between 2015 and 2030. The results show that, in order to achieve the optimal path in Shenzhen's power sector, the carbon mitigation technologies of existing coal and gas-fired power plants will be 100% implemented. Two-thirds and remaining one-third of coal-fired power plant capacities are going to be decommissioned in 2023 and 2028, respectively. Gas-fired power, distributed photovoltaic power, waste-to-energy power and CCHP (Combined Cooling, Heating, and Power) are going to expand their capacities gradually.

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“…Although the VaR method has the advantage of reflecting the risk, its disadvantage is that the decision criterion is conservative due to excessive recognition of the risk, which often leads to loss of an investment opportunity for investors. In previous studies, the VaR method for various projects has been applied to evaluate the risk by reflecting the project [8][9][10][11]. For sustainable development, investors need to select good investment opportunities that are less risky and more profitable for their projects.…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk

Kim

2018

Sustainability

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This paper focuses on an investment decision-making process for sustainable development based on the profitability impact factors for overseas projects. Investors prefer to use the discounted cash-flow method. Although this method is simple and straightforward, its critical weakness is its inability to reflect the factor volatility associated with the project evaluation. To overcome this weakness, the Value-at-Risk method is used to apply the volatility of the profitability impact factors, thereby reflecting the risks and establishing decision-making criteria for risk-averse investors. Risk-averse investors can lose relatively acceptable investment opportunities to risk-neutral or risk-amenable investors due to strict investment decision-making criteria. To overcome this problem, critical factors are selected through a Monte Carlo simulation and a sensitivity analysis, and solutions to the critical-factor problems are then found by using the Theory of Inventive Problem Solving and a business version of the Project Definition Rating Index. This study examines the process of recovering investment opportunities with projects that are investment feasible and that have been rejected when applying the criterion of the Value-at-Risk method. To do this, a probabilistic alternative approach is taken. To validate this methodology, the proposed framework for an improved decision-making process is demonstrated using two actual overseas projects of a Korean steel-making company.

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Operating Strategy for Local-Area Energy Systems Integration Considering Uncertainty of Supply-Side and Demand-Side under Conditional Value-At-Risk Assessment

Cited by 8 publications

References 23 publications

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research

A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China

A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk

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