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1. Pricing Multi-Interval Dispatch under Uncertainty Part I: Dispatch-Following Incentives

   https://doi.org/10.1109/TPWRS.2021.3055730  

   Guo, Ye; Chen, Cong; Tong, Lang (January 2021, IEEE Transactions on Power Systems)

   null (Ed.)

   Pricing multi-interval economic dispatch of electric power under operational uncertainty is considered in this two- part paper. Part I investigates dispatch-following incentives of profit-maximizing generators and shows that, under mild conditions, no uniform-pricing scheme for the rolling-window economic dispatch provides dispatch-following incentives that avoid discriminative out-of-the-market uplifts. A nonuniform pricing mechanism, referred to as the temporal locational marginal pricing (TLMP), is proposed. As an extension of the standard locational marginal pricing (LMP), TLMP takes into account both generation and ramping-induced opportunity costs. It eliminates the need for the out-of-the-market uplifts and guarantees full dispatch-following incentives regardless of the accuracy of the demand forecasts used in the dispatch. It is also shown that, under TLMP, a price-taking market participant has incentives to bid truthfully with its marginal cost of generation. Part II of the paper extends the theoretical results developed in Part I to more general network settings. It investigates a broader set of performance measures, including the incentives of the truthful revelation of ramping limits, revenue adequacy of the operator, consumer payments, generator profits, and price volatility under the rolling-window dispatch model with demand forecast errors. 

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2. Generation Ramping Valuation in Day-Ahead Electricity Markets

   https://doi.org/10.1109/HICSS.2016.292  

   Parvania, Masood; Scaglione, Anna (January 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS))

   In this paper, we first introduce a variational formulation of the Unit Commitment (UC) problem, in which generation and ramping trajectories of the generating units are continuous time signals and the generating units cost depends on the three signals: the binary commitment status of the units as well as their continuous-time generation and ramping trajectories. We assume such bids are piecewise strictly convex time-varying linear functions of these three variables. Based on this problem derive a tractable approximation by constraining the commitment trajectories to switch in a discrete and finite set of points and representing the trajectories in the function space of piece-wise polynomial functions within the intervals, whose discrete coefficients are then the UC problem decision variables. Our judicious choice of the signal space allows us to represent cost and constraints as linear functions of such coefficients, thus, our UC models preserves the MILP formulation of the UC problem. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total dayahead and real-time operation cost, and the number of ramping scarcity events in the real-time operations. 

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3. Pricing Multi-Interval Dispatch under Uncertainty Part II: Generalization and Performance

   https://doi.org/10.1109/TPWRS.2020.3045162  

   Chen, Cong; Guo, Ye; Tong, Lang (December 2020, IEEE Transactions on Power Systems)

   null (Ed.)

   Pricing multi-interval economic dispatch of electric power under operational uncertainty is considered in this two-part paper. Part I investigates dispatch-following incentives for generators under the locational marginal pricing (LMP) and temporal locational marginal pricing (TLMP) policies. Extending the theoretical results developed in Part I, Part II evaluates a broader set of performance measures under a general network model. For networks with power flow constraints, TLMP is shown to have an energy-congestion-ramping price decomposition. Under the one-shot dispatch and pricing model, this decomposition leads to a nonnegative merchandising surplus equal to the sum of congestion and ramping surpluses. It is also shown that, comparing with LMP, TLMP imposes a penalty on generators with limited ramping capabilities, thus giving incentives for generators to reveal their ramping limits truthfully and improve their ramping capacities. Several benchmark pricing mechanisms are evaluated under the rolling-window dispatch and pricing models. The performance measures considered are the level of out-of-the-market uplifts, the revenue adequacy of the system operator, consumer payment, generator profit, level of discriminative payment, and price volatility. 

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4. Dynamic Electricity Pricing – Modeling Manufacturer Response and an Application to Cement Processing

   https://doi.org/10.5539/eer.v9n2p1  

   Eryilmaz, Derya; Apland, Jeffrey; Smith, Timothy M. (November 2019, Energy and Environment Research)

   Dynamic pricing, also known as real-time pricing, provides electricity users with an economic incentive to adjust electricity use based on changing market conditions. This paper studies the economic implications of real-time pricing mechanisms in a cement manufacturing plant. Production for a representative cement manufacturing plant is modeled using stochastic mathematical programming. The results show that a cement plant can a) reduce electricity costs by shifting electricity load of certain processes to times when electricity prices are lower, and b) profitably reduce electricity use during peak prices through more efficient scheduling of production under real-time pricing compared to fixed pricing. The results suggest that building scheduling flexibility into certain industrial manufacturing processes to reschedule electricity consumption when the electricity prices at their peak may be economical. The results also suggest that shifts in the production schedule of a cement manufacturer that result from real-time pricing may also influence environmental impacts. The modelling framework modeled real-time pricing as a source of risk in this study, which is also applicable to other energy intensive industries. As such, dynamic pricing strategies that include the non-market impacts of electricity generation should be further explored. 

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5. Pricing flexibility of shiftable demand in electricity markets

   https://doi.org/10.1145/3447555.3464847  

   Werner, Lucien; Wierman, Adam; Low, Steven H. (June 2021, ACM International Conference on Future Energy Systems)

   Enabling participation of demand-side flexibility in electricity markets is key to improving power system resilience and increasing the penetration of renewable generation. In this work we are motivated by the curtailment of near-zero-marginal-cost renewable resources during periods of oversupply, a particularly important cause of inefficient generation dispatch. Focusing on shiftable load in a multi-interval economic dispatch setting, we show that incompatible incentives arise for loads in the standard market formulation. While the system's overall efficiency increases from dispatching flexible demand, the overall welfare of loads can decrease as a result of higher spot prices. We propose a market design to address this incentive issue. Specifically, by imposing a small number of additional constraints on the economic dispatch problem, we obtain a mechanism that guarantees individual rationality for all market participants while simultaneously obtaining a more efficient dispatch. Our formulation leads to a natural definition of a uniform, time-varying flexibility price that is paid to loads to incentivize flexible bidding. We provide theoretical guarantees and empirically validate our model with simulations on real-world generation data from California Independent System Operator (CAISO). 

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