In the electricity market, wholesale energy prices depend on the balance between energy production and load demand. In the last few years, electricity market has become more and more flexible as many utilities have started to replace the fixed retail prices schemes with prices changing during the day. Dynamic pricing, also known as Real-Time Pricing (RTP), reflects the trend of the wholesale market and allows to reduce the volatility of the wholesale prices, also contributing to a reduction of demand peaks. Electricity customers take advantage of dynamic pricing by shifting their consumption according to the real-time prices or by using Battery Energy Storage Systems (BESS) to shift electricity consumption. As a result, storing electricity in off-peak periods allows customers to lower electricity rates during on-peak periods.\ud
This paper describes the application to a medium-scale public facility of a simple BESS operating strategy which aims to maximize the saving for the end-user. The operating strategy is able to identify, for each daily period, the charging and discharging hours, relying only on the hourly spot market price profile (day-ahead electricity prices) and may be applied to all kinds of BESS. The experimental evaluation uses a Lithium-ion (Li-ion) storage system and results highlight how the power profile of the public facility changes as a result of the proposed charging strateg
The energy market has changed radically over the last decade, mainly due to an increased penetration of renewable energies. Now the end users have directly access to the energy market and can actively take part to the electricity market. Electricity customers can indeed modify their behavior through Demand Response, namely by means of pricing strategies that support a change in the end-users habits. This can be accomplished through a 'loads aggregator', a third party that collects the requests and signals for Active Demand-based services coming from the markets and the different actors of energy market. This paper describes a simulation framework to generate the simulated optimal behavior of the electrical users. Based on a given real-time pricing curves the simulator evaluates the power consumption hour by hour if the user behaves according to what the price curve and thus the loads aggregator suggests. A case study shows the advantages/disadvantages of the proposed pricing approach and the limits of the simulator
The paper deals with the calculation of the optimal working point of a distribution system, equipped with several distributed generators, able to operate also autonomously, i.e. disconnected from the main grid. When connected to the main grid, it appears in general convenient to assign the slack bus role to the bus that represents such a connection. The problem becomes more complex when maximum power transfer constraints through the connection must be taken into account. The adequate slack bus treatment is even more important when the optimal operating condition must refer to the condition subsequent to an intentional or unintentional disconnection from the main grid. The paper presents an analysis of different approaches and their comparison with the help of the computation results relevant to a typical test distribution network.
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