Somayeh Moazeni

A Robust Optimization Approach for Planning the Transition to Plug-in Hybrid Electric Vehicles

This paper proposes a new technique to analyze the electricity and transport sectors within a single integrated framework to realize an environmentally and economically sustainable integration of plug-in hybrid electric vehicles (PHEVs) into the electric grid, considering the most relevant planning uncertainties. The method is based on a comprehensive robust optimization planning that considers the constraints of both the electricity grid and the transport sector. The proposed model is justified and described in some detail, applying it to the real case of Ontario, Canada, to determine Ontarios grid potential to support PHEVs for the planning horizon 2008-2025.

Mean-Conditional Value-at-Risk Optimal Energy Storage Operation in the Presence of Transaction Costs

This paper addresses the formulation and solution of an optimal energy storage management problem under risk consideration and transaction costs of trading energy with the power grid. The price evolves as a stochastic process, capable of correctly explaining the seasonality effects as well as the tail fatness and spikiness in its distribution. Transaction costs capture the price impact of the storage operation on the electricity spot price. A risk analysis of an optimal risk neutral deterministic policy as well as the simple myopic policy indicates that the realized operational cost may notably differ from the expected cost by a considerable probability. This difference suggests that we need to consider risk. Using the downside risk measure of conditional value-at-risk, an optimal risk averse conversion and transmission strategy, among the grid, the renewable power generation source, and an energy storage is proposed to fully satisfy the electricity demand and minimize the expected operational cost as well as the risk. Our numerical study using data from NYISO demonstrates the impacts of risk consideration and the transaction cost parameters on the optimal strategy structure, its expected cost, and its risk.

Optimal Portfolio Execution Strategies and Sensitivity to Price Impact Parameters

When liquidating a portfolio of large blocks of risky assets, an institutional investor wants to minimize the cost as well as the risk of execution. An optimal execution strategy minimizes a weighted combination of the expected value and the variance of the execution cost, where the weight is given by a nonnegative risk aversion parameter. The execution cost is determined from price impact functions. In particular, a linear price impact model is defined by the temporary impact matrix

Optimal Execution Under Jump Models For Uncertain Price Impact

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Resource allocation in OFDMA networks based on interior point methods: RESOURCE ALLOCATION IN OFDMA NETWORKS

and the permanent impact matrix

Fuzzy shortest path problem with finite fuzzy quantities

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Microgrids Frequency Control Considerations Within the Framework of the Optimal Generation Scheduling Problem

, which represent the expected price depression caused by trading assets at a unit rate. In this paper, we analyze the sensitivity of the optimal execution strategy to estimation errors in the impact matrices under a linear price impact model. We show that, instead of depending on

Smoothing and parametric rules for stochastic mean-CVaR optimal execution strategy

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An Interior Point Penalty Method for Utility Maximization Problems in OFDMA Networks

and

A note on the dynamic liquidity trading problem with a mean-variance objective

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