A Self-Adapting Approach for Forecast-Less Scheduling of Electrical Energy Storage Systems in a Liberalized Energy Market

Abstract

Abstract:In this paper, an original scheduling approach for optimal dispatch of electrical Energy Storage Systems (ESS) in modern distribution networks is proposed. The control system is based on fuzzy rules and does not use forecasts since it repairs the past history according to the real time data on the electrical energy cost, renewable energy production and load. When the system detects a worsening of performances, the fuzzy logic rule-based control system self-adapts its membership functions using an economic indicator. The common use, in the relevant literature, of forecasted values in such systems can lead to large errors and economic losses. Moreover the speed of calculation guaranteed by the fuzzy control system allows the execution of new calculations even with high frequency. After the Introduction section, where the state of the art on the topic is outlined, the problem formulation is presented and an interesting application of the considered approach to the control on a medium size battery with real world data is proposed.

The Real-Time Optimisation of DNO Owned Storage Devices on the LV Network for Peak Reduction

“…Uncertainty with the MPC models has also been studied within [19][20][21] and for minimizing operational costs using electric vehicles [22]. It has also been shown that storage control incorporating uncertainty in the electricity market is possible using a receding horizon and no forecasts [23]; the work successfully reduces the impact of prediction errors using a heuristic-based approach. As forecasting on the LV network is difficult, the control of storage will be dependent on the accuracy of the forecast [12,24].…”

Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving

“…Scheduling systems developed by Sanseverino et al [61] and Grillo et al [62] depend on price signals over the use of TOU tariffs, day-ahead energy market data, an hour ahead market data, and spot prices optimize the charging and discharging of battery energy storage (BES). Utilization of day-ahead, hour-ahead, and spot price markets provides the scheduling systems a precise image of the load on the grid.…”

Optimal Power Flow in Islanded Microgrids Using a Simple Distributed Algorithm

“…The optimized solution using the proposed DOPF is compared to a centralized OPF solution using GSO algorithm as described in [9]. Since the solution of the DOPF is approximated, the attained solution is close to the optimal, but not the optimal.…”

“…OPF is essentially a tertiary level optimal operation issue in electric power systems and the latter has been for a long time a concern of many researchers. For this purpose, many optimization techniques have been used, such as "the steepest descent" method [6], particle swarm optimization method [7], Glow-worm Swarm Optimization (GSO) method [8] fuzzy rules method [9,10], dynamic programming [11], global optimization [12,13] and so forth. In addition, optimization problems have been solved considering the presence of energy storage systems, which are critical in islanded MGs systems [10,[14][15][16][17][18][19].…”