Marginal cost pricing of transmission losses signals locational advantages for investment in generation and demand and the need for investment in the transmission system (Green, 1997). Experiences from the Californian Energy Crisis showed that EMI without proportionate investments in transmission capacities led to network congestions and power. Locational Marginal Pricing (LMP), a primary feature of MRTU, is the calculation of electricity prices at thousands of pricing points, or nodes, within California’s electricity grid. It provides price signals that account for the additional costs of electricity caused by transmission congestion and line loss at various points on the electricity grid.
The locational marginal price (LMP) at some particular point in the grid measures the marginal cost of delivering an additional unit of electric energy (i.e., a marginal MWh) to that location. With no transmission line constraints or losses, the marginal price in every location (referred to as a “Locational Marginal Price” or LMP) will be same at every node. As shown in Fig. 8.8, all of the cheapest generation (G2) will be used first, with incremental generation coming from G1 at a marginal cost of $30/MWh. The LMP at node L (and everywhere else) is therefore $30/MWh.
LMP may stand for:
Abstract: Large-scale integration of renewable energy sources (RES) brings hugechallenges to the power system. A cost-effective reserve deployment anduncertainty pricing mechanism are critical to deal with the uncertainty andvariability of RES. To this end, this paper proposes a novel locationalmarginal pricing mechanism in day-ahead market for managing uncertainties fromRES. Firstly, an improved multi-ellipsoidal uncertainty set (IMEUS) consideringthe temporal correlation and conditional correlation of wind power forecast isformulated to better capture the uncertainty of wind power. The dimension ofeach ellipsoidal subset is optimized based on a comprehensive evaluation indexto reduce the invalid region without large loss of modeling accuracy, so as toreduce the conservatism. Then, an IMEUS-based robust unit commitment (RUC)model and a robust economic dispatch (RED) model are established for theday-ahead market clearing. Both the reserve cost and ramping constraints areconsidered in the overall dispatch process. Furthermore, based on theLangrangian function of the RED model, a new locational marginal pricingmechanism is developed. The uncertainty locational marginal price (ULMP) isintroduced to charge the RES for its uncertainties and reward the generatorswho provide reserve to mitigate uncertainties. The new pricing mechanism canprovide effective price signals to incentivize the uncertainty management inthe day-ahead market. Finally, the effectiveness of the proposed methods isverified via numerous simulations on the PJM 5-bus system and IEEE 118-bussystem.
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