Interruptible Load Risk Analysis Based on Portfolio Theory

Due to the uncertain price and stochastic load, power supply companies will face the trade-off between profits and risks when exercising Interruptible Load Management (ILM). Customers of different type are looked as sub-markets with different risk and benefit. A model is established for Interruptible Load (IL) in the framework of portfolio theory, with the object of maximizing the expected profits and risks of conditional value at risk (CVaR). Genetic Algorithm (GA), is adopted to solve the model. Finally, a numerical example is served for demonstrating the market property of high profits accompanied by high risks and the feasibility of the proposed model, thus a reference is provided to a power supply company to manage risks.

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Developing an Algorithm for Urban Flood Management With the Aim of Reducing Damage and Costs Using the Concept of Conditional Value at Risk

10.21203/rs.3.rs-266864/v1 ◽

2021 ◽

Author(s):

Pedram Eshaghieh Firoozabadi ◽

sara nazif ◽

Seyed Abbas Hosseini ◽

Jafar Yazdi

Keyword(s):

At Risk ◽

Hybrid Model ◽

Best Management Practices ◽

Value At Risk ◽

Management Practices ◽

Flood Management ◽

Surface Flow ◽

Conditional Value At Risk ◽

Urban Flood ◽

Proposed Model

Abstract Flooding in urban area affects the lives of people and could cause huge damages. In this study, a model is proposed for urban flood management with the aim of reducing the total costs. For this purpose, a hybrid model has been developed using SWMM and a quasi-two-dimensional model based on the cellular automata (CA) capable of considering surface flow infiltration. Based on the hybrid model outputs, the best management practices (BMPs) scenarios are proposed. In the next step, a damage estimation model has been developed using depth-damage curves. The amount of damage has been estimated for the scenarios in different rainfall return periods to obtain the damage and cost- probability functions. The conditional value at risk (CVaR) are estimated based on these functions which is the basis of decision making about the scenarios. The proposed model is examined in an urban catchment located in Tehran, Iran. In this study, five scenarios have been designed on the basis of different BMPs. It has been found that the scenario of permeable pavements has the lowest risk. The proposed model enables the decision makers to choose the best scenario with the minimum cost taking into account the risk associated with each scenario.

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Optimal Purchasing Portfolio for Power Supplier with Options and Interruptible Load Based on Conditional Value-at-Risk

2009 WASE International Conference on Information Engineering ◽

10.1109/icie.2009.50 ◽

2009 ◽

Author(s):

Ruiqing Wang ◽

Xinfeng Xiao ◽

Weijun Dong

Keyword(s):

At Risk ◽

Value At Risk ◽

Conditional Value At Risk ◽

Interruptible Load

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Application of Portfolio Theory Based on CVaR in Determining Optimal Spinning Reserve with Consideration of Load and Wind Power Uncertainties

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.724-725.649 ◽

2013 ◽

Vol 724-725 ◽

pp. 649-654

Author(s):

Jun Li Wu ◽

Bu Han Zhang ◽

Zhen Yin Xiao ◽

Kui Wang

Keyword(s):

Power System ◽

Wind Power ◽

Value At Risk ◽

Efficient Frontier ◽

Portfolio Theory ◽

Conditional Value At Risk ◽

Power Prediction ◽

Spinning Reserve ◽

The Cost ◽

Installed Capacity

With the increased installed capacity of wind power in power system, determining optimal spinning reserve capacity is one of the most important problems in operation of electricity power system. CVaR (conditional value at risk) is introduced to calculate the risk of the cost associated with load shed and abandoning wind power with the consideration of load and wind power prediction uncertainties. Portfolio theory based on CVaR is used to build the Cost-CVaR model. Efficient frontier, which can support the system operators (SO) with the decision of optimal spinning reserve, can be obtained by solving the Cost-CVaR model. The analysis of RTS example can demonstrate the usefulness and efficiency of the model.

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Wholesale Price for Supply Chain Coordination via Conditional Value-at-Risk Minimization

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.20-23.88 ◽

2010 ◽

Vol 20-23 ◽

pp. 88-93 ◽

Cited By ~ 1

Author(s):

Chuan Xu Wang

Keyword(s):

At Risk ◽

Supply Chain ◽

Value At Risk ◽

Supply Chain Coordination ◽

Wholesale Price ◽

Conditional Value At Risk ◽

Optimal Order ◽

Individual Member ◽

Risk Minimization ◽

Proposed Model

The theory of the conditional value-at-risk (CVaR) in financial risk management is considered in this paper to develop a model of supply chain coordination with a wholesale pricing policy. The proposed model solves the drawbacks of objective function in current supply chain coordination model. A numerical example is given to demonstrate the effectiveness of the proposed model. The following helpful conclusions are drawn from the paper: with the increase of the degree of risk averting for supply chain individual member, the optimal order quantity of supply chain is decreasing, while the optimal profit is decreasing; If supplier’s risk averting degree increases, supplier has to increase wholesale price to achieve supply chain coordination; If retailer’s risk averting degree increases, supplier has to decrease wholesale price to achieve supply chain coordination.

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Cryptocurrency Portfolio Selection—A Multicriteria Approach

Mathematics ◽

10.3390/math9141677 ◽

2021 ◽

Vol 9 (14) ◽

pp. 1677

Author(s):

Zdravka Aljinović ◽

Branka Marasović ◽

Tea Šestanović

Keyword(s):

At Risk ◽

Standard Deviation ◽

Portfolio Selection ◽

Value At Risk ◽

Selection Process ◽

Efficient Frontier ◽

Conditional Value At Risk ◽

Optimal Portfolios ◽

Promethee Ii ◽

Proposed Model

This paper proposes the PROMETHEE II based multicriteria approach for cryptocurrency portfolio selection. Such an approach allows considering a number of variables important for cryptocurrencies rather than limiting them to the commonly employed return and risk. The proposed multiobjective decision making model gives the best cryptocurrency portfolio considering the daily return, standard deviation, value-at-risk, conditional value-at-risk, volume, market capitalization and attractiveness of nine cryptocurrencies from January 2017 to February 2020. The optimal portfolios are calculated at the first of each month by taking the previous 6 months of daily data for the calculations yielding with 32 optimal portfolios in 32 successive months. The out-of-sample performances of the proposed model are compared with five commonly used optimal portfolio models, i.e., naïve portfolio, two mean-variance models (in the middle and at the end of the efficient frontier), maximum Sharpe ratio and the middle of the mean-CVaR (conditional value-at-risk) efficient frontier, based on the average return, standard deviation and VaR (value-at-risk) of the returns in the next 30 days and the return in the next trading day for all portfolios on 32 dates. The proposed model wins against all other models according to all observed indicators, with the winnings spanning from 50% up to 94%, proving the benefits of employing more criteria and the appropriate multicriteria approach in the cryptocurrency portfolio selection process.

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A New Portfolio Rebalancing Model with Transaction Costs

Journal of Applied Mathematics ◽

10.1155/2014/942374 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 2

Author(s):

Meihua Wang ◽

Cheng Li ◽

Honggang Xue ◽

Fengmin Xu

Keyword(s):

At Risk ◽

Transaction Costs ◽

Cost Function ◽

Transaction Cost ◽

Value At Risk ◽

Financial Data ◽

Conditional Value At Risk ◽

Expected Return ◽

Portfolio Rebalancing ◽

Proposed Model

A portfolio rebalancing model with self-finance strategy and consideration of V-shaped transaction cost is presented in this paper. Our main contribution is that a new constraint is introduced to confirm that the rebalance necessity of the existing portfolio needs to be adjusted. The constraint is constructed by considering both the transaction amount and transaction cost without any additional supply to the investment amount. The V-shaped transaction cost function is used to calculate the transaction cost of the portfolio, and conditional value at risk (CVaR) is used to measure the risk of the portfolios. Computational tests on practical financial data show that the proposed model is effective and the rebalanced portfolio increases the expected return of the portfolio and reduces the CVaR risk of the portfolio.

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Research on Interruptible Load participating in electricity and reserve joint market

E3S Web of Conferences ◽

10.1051/e3sconf/202125701045 ◽

2021 ◽

Vol 257 ◽

pp. 01045

Author(s):

Haiyu Huang ◽

Chunming Wang ◽

Shaolian Xia ◽

Huaqiang Xiong ◽

Baofeng Jiang ◽

...

Keyword(s):

Social Welfare ◽

Power Supply ◽

Power Grid ◽

Peak Load ◽

Electric Energy ◽

Response Speed ◽

Interruptible Load ◽

Proposed Model ◽

Simulation Results ◽

Reserve Market

There is a shortage of power supply in multi provincial power grid during peak load period. The response speed of interruptible load is fast, and it has the same excellent regulation performance as the standby on the generation side, which can meet the needs of fast transfer. Aiming at the situation of interruptible load participating in the joint market under the bilateral mode, this paper designs the joint clearing process of electric energy and reserve market considering interruptible load, and establishes the joint clearing model considering interruptible load participating in electric energy and reserve market with the goal of maximizing social welfare. Simulation results verify the effectiveness of the proposed model.

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