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

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.

The Optimal Spinning Reserve Considering Wind Power Prediction Deviation

2013 ◽  
Vol 860-863 ◽  
pp. 299-304
Author(s):  
Xiao Ming Jin ◽  
Dong Mei Zhao ◽  
Long Long Li ◽  
Dong Hui Zhang
Keyword(s):  
Power System ◽  
Wind Power ◽  
Power Prediction ◽  
Spinning Reserve ◽  
Load Duration ◽  
Power Characteristics ◽  
Wind Power Prediction ◽  
Equivalent Load ◽  
The Impact ◽  
Complete Optimization

With the capacity of wind power into power system increasing year by year, the impact of wind power characteristics (random and intermittent) on the system stable equilibrium is outstanding. To configure spinning reserve properly, this paper establishes a relatively complete optimization model of spinning reserve for power system with wind integrated. Using the similar samples to train prediction model, the precision of prediction is improved. The equivalent load duration curve (ELDC) considering load fluctuations and unit outage, is revised by analyzing the probability density of wind power prediction deviation. And the last, this paper gives an example to verify the theory.

The Reserve Capacity Model Based on the Idea of Scenario in Power System

2014 ◽  
Vol 1008-1009 ◽  
pp. 173-178
Author(s):  
Xiao Li Zheng ◽  
Ji Chun Liu ◽  
Jia Yi Li ◽  
Yun Xia Wu ◽  
Fang Zhang ◽  
...  
Keyword(s):  
Power System ◽  
Wind Power ◽  
Programming Model ◽  
Reserve Capacity ◽  
Power Prediction ◽  
Capacity Model ◽  
Uncertainty Model ◽  
Power Difference ◽  
The Cost ◽  
The Impact

According to the impact of the wind power prediction uncertainty on the power system reserve capacity, the idea of scenario is introduced to the stochastic programming model. The method of scenario is used to simulate the uncertainty model of the wind power generation, load and the conventional units. The scenario-reduction methodology is combined to reduce the large scenario set to a simpler one, then the probability statistics on these scenarios is given in order to obtain the probability density of the system power difference, and the expected energy not supplied (EENS) and expected wind waste risk (EWWR) are presented. The reserve capacity is determined by the two aspects, which are the reliability shown by EENS and EWWR, and the economy of reserve capacity cost. Finally, simulations on a ten-unit system are given to demonstrate the method is effective to reduce the cost of reserve and the abandoned wind power in the context of system reliability.

scholarly journals Risk-Limiting Real-Time Economic Dispatch in a Power System with Flexibility Resources

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3133 ◽  
Author(s):  
Hongji Lin ◽  
Chongyu Wang ◽  
Fushuan Wen ◽  
Chung-Li Tseng ◽  
Jiahua Hu ◽  
...  
Keyword(s):  
Power System ◽  
Real Time ◽  
Value At Risk ◽  
Renewable Energy Sources ◽  
Economic Dispatch ◽  
Conditional Value At Risk ◽  
Operational Flexibility ◽  
Practical Applications ◽  
Start Up ◽  
The Impact

The integration of numerous intermittent renewable energy sources (IRESs) poses challenges to the power supply-demand balance due to the inherent intermittent and uncertain power outputs of IRESs, which requires higher operational flexibility of the power system. The deployment of flexible ramping products (FRPs) provides a new alternative to accommodate the high penetration of IRESs. Given this background, a bi-level risk-limiting real-time unit commitment/real-time economic dispatch model considering FRPs provided by different flexibility resources is proposed. In the proposed model, the objective is to maximize the social surplus while minimizing the operational risk, quantified using the concept of conditional value-at-risk (CVaR). Energy and ramping capabilities of conventional generating units during the start-up or shut-down processes are considered, while meeting the constraints including unit start-up/shut-down trajectories and ramping up/down rates in consecutive time periods. The Karush–Kuhn–Tucker (KKT) optimality conditions are then used to convert the bi-level programming problem into a single-level one, which can be directly solved after linearization. The modified IEEE 14-bus power system is employed to demonstrate the proposed method, and the role of FRPs in enhancing the system flexibility and improving the accommodation capability for IRESs is illustrated in some operation scenarios of the sample system. The impact of the confidence level in CVaR on the system operational flexibility is also investigated through case studies. Finally, a case study is conducted on a regional power system in Guangdong Province, China to demonstrate the potential of the proposed method for practical applications.

EFFECTS OF MULTIPLE CRITERIA ON PORTFOLIO OPTIMIZATION

2014 ◽  
Vol 13 (01) ◽  
pp. 77-99 ◽  
Author(s):  
TUNCER ŞAKAR CEREN ◽  
MURAT KÖKSALAN
Keyword(s):  
At Risk ◽  
Portfolio Optimization ◽  
Decision Maker ◽  
Value At Risk ◽  
Efficient Frontier ◽  
Conditional Value At Risk ◽  
Computational Studies ◽  
Expected Return ◽  
Risk Criteria ◽  
Return Variance

We study the effects of considering different criteria simultaneously on portfolio optimization. Using a single-period optimization setting, we use various combinations of expected return, variance, liquidity and Conditional Value at Risk criteria. With stocks from Borsa Istanbul, we make computational studies to show the effects of these criteria on objective and decision spaces. We also consider cardinality and weight constraints and study their effects on the results. In general, we observe that considering alternative criteria results in enlarged regions in the efficient frontier that may be of interest to the decision maker. We discuss the results of our experiments and provide insights.

Interruptible Load Risk Analysis Based on Portfolio Theory

2013 ◽  
Vol 732-733 ◽  
pp. 1427-1431
Author(s):  
Jin Feng Wang ◽  
Rong Zhu ◽  
Yan Jiang
Keyword(s):  
Power Supply ◽  
Value At Risk ◽  
Portfolio Theory ◽  
Conditional Value At Risk ◽  
Load Management ◽  
Interruptible Load ◽  
Proposed Model ◽  
Stochastic Load ◽  
Risk And Benefit ◽  
Load Risk

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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