Impact of Demand-Response on the Efficiency and Prices in Real-Time Electricity Markets

International audienceWe study the effect of Demand-Response (DR) in dynamic real-time electricity markets. We use a two-stage market model that takes into account the dynamical aspects of gen-eration, demand, and DR. We study the real-time market prices in two scenarios: in the former, consumers anticipate or delay their flexible loads in reaction to market prices; in the latter, the flexible loads are controlled by an independent aggregator. For both scenarios, we show that, when users are price-takers, any competitive equilibrium is efficient: the players' selfish responses to prices coincide with a socially optimal policy. Moreover, the price process is the same in all scenarios. For the numerical evaluation of the properties of the equilibrium, we develop a solution technique based on the Alternating Direction Method of Multipliers (ADMM) and trajectorial forecasts. The forecasts are computed us-ing wind generation data from the UK. We challenge the assumption that all players have full information. If the as-sumption is verified, then, as expected, the social welfare increases with the amount of DR available, since DR relaxes the ramping constraints of generation. However, if the day-ahead market cannot observe how elastic loads are affected by DR, a large quantity of DR can be detrimental and leads to a decrease in the welfare. Furthermore, the DR operator has an incentive to under-dimension the quantity of avail-able DR. Finally, we compare DR with an actual energy storage system. We find that storage has a faster response-time and thus performs better when only a limited amount is installed. However, storage suffers from charge-discharge in-efficiency: with DR, prices do concentrate on marginal cost (for storage, they do not) and provide a better welfare

Adaptive access and rate control of CSMA for energy, rate and delay optimization

In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal decision is to transmit when the wireless channel state is better than a threshold. We also provide a queue management scheme where arrival rate is controlled based on the link state. Numerical results show characteristics of the proposed adaptation scheme and highlight the trade-off among energy consumption, smoothed data rate, and link delay.This study was supported in part by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under projects COMONSENS (CSD2008-00010, CONSOLIDER-INGENIO 2010 program) and COSIMA (TEC2010-19545-C04-03), in part by Iran Telecommunication Research Center under contract 6947/500, and in part by Iran National Science Foundation under grant number 87041174. This study was completed while M. Khodaian was at CEIT and TECNUN (University of Navarra)