1 Abstract--In this paper the effective usage of Ripple Control Systems (RCS) is investigated from the point of view of daily load balancing. A computer simulation model is developed to be able to study the power consumption of RCS-controllable groups and their impact on the daily load curve. The design of an appropriate switching pattern is formulated as an optimization problem with the objective of the highest possible minimal daily load constrained by duration of service and derivative conditions. After the decomposition of the problem a fuzzy logic and genetic algorithm based optimization method is developed. The efficiency of the method is shown comparing different switching patterns by computer simulations. Index Terms -- Fuzzy Logic, Genetic Algorithms, Load management, Optimization methods I. INTRODUCTION By the end of the 20 th century, before privatization of the energy industry in Hungary the system of Ripple Control Systems (RCS) has been installed in order to be able to fill up load valleys by remotely switching on and off storage heaters from the dispatcher centers of the utility companies. A two- tariff system has been established, supplying energy mainly for the switchable hot water electric boilers and heaters considerably cheaper in off-peak time than for the non- switchable consumers. Recently the former utilities turned into Distribution System Operators (DSO) and changed their switching patterns so as to keep the deviation from their schedule as low as possible (still providing at least 8 hours switch-on time for the remotely switchable consumers). This interest contradicts the interest of the Hungarian Independent System Operator, which is still balancing the valley loads so that no one block of the nuclear power plant Paks has to lower its production during the night. The RCS is an important factor in the present production- trading-consumption structure: it can help to maintain balance and ensure the economical efficiency of the system. From this point of view it could be substituted only with very uneconomical solutions (e.g. export of surplus energy at any price). A.M. Dan (dan@vmt.bme.hu) and D. Raisz (raisz@vmt.bme.hu) are with the Department of Electric Power Systems, Budapest University of Technology and Economics, Budapest, Hungary (H-1111, Egry J. u. 18). However the present practice of RCS control does not make the most of its possibilities, though it could do so fairly easily and without hurting the interests of the consumers. In this paper various possible RCS switching patterns are analyzed and compared based on computer simulations. For the simulations it is necessary to know - the change of power demand due to switching on a group of RCS-controllable consumers - and also the power consumption without the switchable consumers (called "undistorted load curve") This issue is addressed in Section II. During the simulations the load time-functions of the RCS- groups is superposed on the undistorted load curve according to various RCS programs, and so the efficiency of those programs in the load-balancing can be analyzed. Important constraints to be respected are: • the change of the total load of the Hungarian system due to RCS switching is not allowed to exceed 90 MW within a 5-minute interval (written regulation), • every group has to be switched on at least 8 hours a day (as a guaranteed service ), • the double tariff system according to peak and off-peak times is not subject to change. These constraints along with the demand for a highest possible minimal load formulate an optimization problem for the switching pattern. The total length of the peak-off tariff time during one day is 15 hours: 13.00 to 17.00 and 20.00 to 07.00 in winter and 14.00 to 18.00 and 21.00 to 08.00 in summer. Considering that the switching patterns are determined in a 5 minute resolution, this yields a total of 180 possible switching instants. Further considering that there are several dozens of switchable groups yields a pattern to be optimized depending on several thousand variables; these variables are binary: either a group is on or off during a 5 minute period. In Section IV a deterministic switching pattern is analyzed. In Sections V and VI a soft-computing based optimization method is developed, which allow the fuzzy formulation of the above mentioned objective and constraints. II. DETERMINATION OF THE UNDISTORTED LOAD CURVE Some DSO-s have performed systematic measurements of their RCS-groups and obtained detailed information on the power consumption of each group. These results match with following theoretical assumption: the individually set switch- Ripple Control as a Possible Tool for Daily Load Balancing in an Open Electricity Market Environment David Raisz, Andras M. Dan, Senior Member, IEEE