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This paper proposes a dynamic valuation framework to determine the opportunity value of battery capacity degradation in grid applications based on the internal degradation mechanism and utilization scenarios. The proposed framework follows a dynamic programming approach and includes a piecewise linear value function approximation solution that solves the optimization problem over a long planning horizon. The paper provides two case studies on price arbitrage and frequency regulation using real market and system data to demonstrate the broad applicability of the proposed framework. Results show that the battery lifetime value is critically dependent on both the external market environment and its internal state of health. On the grid service side, results show that second-life batteries can provide more than 50% of the value compared to new batteries, and frequency regulation provides two times more revenue than price arbitrage throughout the battery lifetime. [ABSTRACT FROM AUTHOR]

This paper addresses the transmission network expansion planning problem under uncertain demand and generation capacity. A two-stage adaptive robust optimization framework is adopted whereby the worst-case operating cost is accounted for under a given user-defined uncertainty set. This paper differs from previously reported robust solutions in two respects. First, the typically disregarded correlation of uncertainty sources is explicitly considered through an ellipsoidal uncertainty set relying on their variance-covariance matrix. In addition, we describe the analogy between the corresponding second-stage problem and a certain class of mathematical programs arising in structural reliability. This analogy gives rise to a relevant probabilistic interpretation of the second stage, thereby revealing an undisclosed feature of the worst-case setting characterizing robust optimization with ellipsoidal uncertainty sets. More importantly, a novel nested decomposition approach based on results from structural reliability is devised to solve the proposed robust counterpart, which is cast as an instance of mixed-integer trilevel programming. Numerical results from several case studies demonstrate that the effect of correlated uncertainty can be captured by the proposed robust approach. [ABSTRACT FROM AUTHOR]

Many countries use auctions to select agents to which transmission concessions are awarded. Where multiple concessions are auctioned each year, there are potential benefits, for transcos and grid users, in using auction protocols allowing risk-averse bidders to explicitly consider complementary packages of transmission facilities: combinatorial and simultaneous descending auctions. We investigate the use of these protocols for transmission auctions, with aid of mixed-integer linear optimization models developed for this task and realistic case studies, while focusing on the treatment of the exposure problem. [ABSTRACT FROM AUTHOR]

Long-term contracting is the traditional governance mechanism to deal with the transaction costs associated with the specificity of gas industry assets. Long-term contracts have been often used to allocate risks among players, and to that end, they often include take-or-pay provisions. These clauses specify that buyers take the volume risk, as they are obliged to pay for a minimum amount of gas consumption. In exchange, buyers pay a predefined price, supposedly lower than the risk-neutral expectation of short-term gas prices. In that view, if the buyer is able to resell that gas in the short term, the contract is an effective hedge against short-term volatility. Otherwise, the contract does not act as a hedge but it becomes a sunk cost. The corresponding power producers' behavior involves not only output decisions but also financial decisions. To analyze that situation, this paper develops a new quantitative methodology that allows comparing risk-neutral valuations of gas and power markets decisions. We test the model in a real-size system, and show the additional cost of the power system associated with a possible illiquidity of the short-term gas market. [ABSTRACT FROM PUBLISHER]