Estimation of aggregate reserve with point-of-load voltage control

Voltage dependent loads can collectively provide a certain amount of power reserve (by virtue of the ability to change their power consumption within the stipulated voltage tolerance) which could be exploited for grid frequency regulation through voltage control at the substation/feeder or at the point of load. The amount of such power reserve would vary with time of the day depending on the incidence of different types of voltage dependent loads and also the voltage profile across the feeders. It is important for the grid operators to know the aggregate power reserve from the voltage dependent loads during different times of the day in order to schedule other forms of reserves accordingly. This paper presents a methodology to estimate such power reserve from the measured power and voltage at the bulk supply points without knowing the actual distribution network topology and/or load profile of individual customers. The proposed method is applied to estimate the time variation of the aggregate reserve offered by the voltage dependent loads within the domestic sector in Great Britain (GB). Studies on a standard IEEE distribution network are presented to validate the estimated reserve margins under typical voltage profiles across the distribution feeders

Fast and Reliable Primary Frequency Reserves From Refrigerators with Decentralized Stochastic Control

Due to increasing shares of renewable energy sources, more frequency reserves are required to maintain power system stability. In this paper, we present a decentralized control scheme that allows a large aggregation of refrigerators to provide Primary Frequency Control (PFC) reserves to the grid based on local frequency measurements and without communication. The control is based on stochastic switching of refrigerators depending on the frequency deviation. We develop methods to account for typical lockout constraints of compressors and increased power consumption during the startup phase. In addition, we propose a procedure to dynamically reset the thermostat temperature limits in order to provide reliable PFC reserves, as well as a corrective temperature feedback loop to build robustness to biased frequency deviations. Furthermore, we introduce an additional randomization layer in the controller to account for thermostat resolution limitations, and finally, we modify the control design to account for refrigerator door openings. Extensive simulations with actual frequency signal data and with different aggregation sizes, load characteristics, and control parameters, demonstrate that the proposed controller outperforms a relevant state-of-the-art controller.Comment: 44 pages, 17 figures, 9 Tables, submitted to IEEE Transactions on Power System

Harnessing Flexible and Reliable Demand Response Under Customer Uncertainties

Demand response (DR) is a cost-effective and environmentally friendly approach for mitigating the uncertainties in renewable energy integration by taking advantage of the flexibility of customers' demands. However, existing DR programs suffer from either low participation due to strict commitment requirements or not being reliable in voluntary programs. In addition, the capacity planning for energy storage/reserves is traditionally done separately from the demand response program design, which incurs inefficiencies. Moreover, customers often face high uncertainties in their costs in providing demand response, which is not well studied in literature. This paper first models the problem of joint capacity planning and demand response program design by a stochastic optimization problem, which incorporates the uncertainties from renewable energy generation, customer power demands, as well as the customers' costs in providing DR. We propose online DR control policies based on the optimal structures of the offline solution. A distributed algorithm is then developed for implementing the control policies without efficiency loss. We further offer enhanced policy design by allowing flexibilities into the commitment level. We perform real world trace based numerical simulations. Results demonstrate that the proposed algorithms can achieve near optimal social costs, and significant social cost savings compared to baseline methods

Eliminating the Flaws in New England's Reserve Markets

New England’s wholesale electricity market has been in operation, since May 1, 1999. When the market began it was understood that the rules were not perfect (Cramton and Wilson 1998). However, it was decided that it was better to start the market with imperfect rules, rather than postpone the market for an indefinite period. After several months of operation, we now have a sense of the extent market imperfections have resulted in observed problems. Here we study the three reserve markets—ten-minute spinning reserve (TMSR), ten-minute non-spinning reserve (TMNSR), and thirty-minute operating reserve (TMOR); we also discuss the closely related operable capability (OpCap) market. The paper covers the first four months of operation from May 1 to August 31, 1999. It is based on the market rules and their implementation by the ISO, and the market data during this period, including bidding, operating, and settlement information. Since that data are confidential, we have presented only aggregate information in the tables and figures that follow. Although this paper will cover only the reserves markets, we have studied the data from the energy, AGC, and capacity markets as well. Since all of the NEPOOL markets are interrelated, one cannot hope to understand one market without having an understanding of the others.Auctions, Electricity Auctions, Multiple Item Auctions