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Currently, there is a national push for a smarter electric grid, one that is more controllable and flexible. Only limited control and flexibility of electric assets is currently built into electric network optimization models. Optimal transmission switching is a low cost way to leverage grid controllability: to make better use of the existing system and meet growing demand with existing infrastructure. Such control and flexibility can be categorized as a “smart grid application” where there is a co-optimization of both generators or loads and transmission topology. In this paper we form the dual problem and examine the multi-period N-1 reliable unit commitment and transmission switching problem with integer variables fixed to their optimal values. Results including LMPs and marginal cost distributions are presented for the IEEE RTS 96 test problem. The applications of this analysis in improving the efficiency of ISO and RTO markets are discussed.

The prevalence of commercial activities whose profit and cost are correlated with weather risk makes weather derivatives valuable financial instruments that enable hedging of price or volumetric (quantity) risk in many industries. This paper proposes a multi-period equilibrium pricing model for weather derivative. In our stylized economy representative agents of weather-sensitive industries optimizes their hedging portfolios that drive the supply and demand for weather derivative which are dynamically determined based on a utility indifference pricing framework. At equilibrium the weather derivative market will be cleared and their market price can be obtained. Numerical examples illustrate the equilibrium prices and optimal choices for the weather derivative as function of the correlation between weather indices and demand for the underlying commodity. We also demonstrate the benefit of multiple trading opportunities which allows rebalancing of the hedging portfolio prior to the commodity delivery date, as compared to a single shot framework.

In this paper, we continue to analyze optimal dispatch of generation and transmission topology to meet load as a mixed integer program (MIP) with binary variables representing the state of the transmission element (line or transformer). Previous research showed a 25% savings by dispatching the IEEE 118-bus test case. This paper is an extension of that work. It presents how changing the topology affects nodal prices, load payment, generation revenues, cost, and rents, congestion rents, and flowgate prices. Results indicate that changing the topology to cut costs typically results in lower load payments and higher generation rents for this network. Computational issues are also discussed. Index Terms--Mixed integer programming, power generation dispatch, power system economics, power transmission control, power transmission economics.

Many wholesale electricity markets call on the independent system operator (ISO) to determine day-ahead schedules for generators based on a centralized unit commitment. Up until recently, the Lagrangian relaxation (LR) algorithm was the only practical means of solving an ISO-scale unit commitment problem, and it was the solution technique used by most ISOs. Johnson et al. [1] demonstrate, however, that equity, incentive, and efficiency issues will arise from use of LR solutions, because different commitments that are similar in terms of total system costs can result in different surpluses to individual units. Recent advances in computing capabilities and optimization algorithms now make solution of the mixed-integer programming (MIP) formulation by means of branch and bound (B&B) tractable, often with optimality gaps smaller than those of LR algorithms, which has led some ISOs to adopt B&B algorithms and others proposing to do so. With the move towards B&B, one obvious question is whether the use of MIP will eliminate or reduce the issues with LR raised by Johnson et al. Using actual market data from an ISO, we demonstrate that both LR and MIP solutions will suffer the same equity issues, unless the ISO unit commitment problems can be solved to complete optimality within the allotted timeframe--which is beyond current computational capabilities. Our results further demonstrate that the size of the payoff deviations are not monotone in the size of the optimality gap, meaning smaller optimality gaps from B&B will not necessarily mitigate the issues Johnson et al. raise. We show that the use of 'make-whole' payments, which ensure units recover any startup and no-load costs not recovered by inframarginal energy rents, can help to reduce surplus volatility and differences to some extent. Index Terms--Electricity market design, power systems economics, unit commitment.

From an economic perspective, a common criterion for assessing the merits of a transmission investment is its impacts on social welfare. The underlying assumption in using this criterion is that side payments may be used to distribute the social gains among all market players. In reality, however, since the impacts of an electricity transmission project on different players may vary, such side payments are rather difficult to implement. This paper focuses on different economic criteria that should be considered when planning electricity transmission investments. We propose an electricity transmission investment assessment methodology that is capable of evaluating the economic impacts on the various effected stakeholders and account for strategic responses that could enhance or impede the investment's objectives. We formulate transmission planning as an optimization problem under alternative conflicting objectives and investigate the policy implications of divergent expansion plans resulting from the planner's level of anticipation of strategic responses. We find that optimal transmission expansion plans may be very sensitive to supply and demand parameters. We also show that the transmission investments have significant distributional impact, creating acute conflicts of interests among market participants. We use a 32-bus representation of the main Chilean grid to illustrate our results. Index Terms--Market power, network expansion planning, power system economics, power transmission planning.