Hedging Electricity Portfolio for a Hydro-energy Producer via Stochastic Programming

Giacometti, Rosella; Vespucci, Maria Teresa; Bertocchi, Marida; Adesi, Giovanni Barone

doi:10.1007/978-1-4419-9586-5_8

Cited by 3 publications

(1 citation statement)

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“…The fitness value of a chromosome is calculated by the group balance, weight balance, portfolio return, and risk to assess the quality of every possible solution. Reference [17] considering the uncertainty of residual demand curve, proposes a stochastic MILP approach to maximize the total expected profit of a price-maker hydro generating company. Reference [18] considers gains from coordinated bidding strategies in multiple electricity markets, a comprehensive scenario-generation methodology which simulation the portfolio size is proposed, and formulate a coordinated planning problem for a hydropower producer using stochastic mixed-integer programming.…”

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confidence: 99%

Risk Analysis Method of Cascade Plants Operation in Medium Term Based on Multi-Scale Market and Settlement Rules

Cheng

et al. 2020

IEEE Access

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Due to the distribution of runoff is uneven and uncertain in time and space, there are huge differences between the electricity markets dominated by hydropower and thermal power. Therefore, how to evaluate the risk of cascade plants participating in electricity market is an urgent problem to be solved. Based on the rules of the market in southwest China which hydropower plays a leading role, this paper proposes a risk analysis method for cascade hydropower to participate in market which is coupled with monthly market and day-ahead market: Copula-Monet Carlo is used to generate the combined scenario of daily runoff and daily clearing price, and the LINGO solver is used to calculate the generation income of all scenarios, and the corresponding conditional value-at-risk value(CVaR) of portfolio is obtained according to the confidence level. The method takes into account the uncertainty of runoff and electricity price in the meantime, as well as the settlement order and deviation assessment of each market in the settlement rules, and can directly solve the income and risk value. The process is simple and the physical meaning is clear. Using the actual data of a grid cascade hydropower participating in the electricity market as an example, the simulation analysis of the results shows that the proposed method can easily solve the portfolio risk value, and can more reasonably evaluate the risk value compared with the considering runoff and day-ahead market clearing prices separately. INDEX TERMS Cascade hydropower plants, portfolio, settlement rules, the risk assessment. I. INTRODUCTION

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confidence: 99%