Optimal Power Management Strategy for Energy Storage with Stochastic Loads

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs

Economic evaluation of installation of standalone wind farm and Wind+CAES system for the new regulating tariffs for renewables in Egypt

Compressed Air Energy Storage (CAES) is widely recognized as a viable solution for large-scale grid integrated renewable energy systems in terms of load levelling to solve/minimize the intermittency effect of renewable energy systems especially with increased penetration of renewables to the grid. This study assesses the economic value of adding compressed air energy storage (CAES) plant to a renewable energy system and how this impacts the overall financial appeal of the system at hand, taking Egyptian grid as a case in point. Numerical modelling using MATLAB was performed to analyse the benefits of adding a CAES system to planned wind farms in Egypt by 2020 for both load-levelling as well as optimizing economic benefit. The results show that the addition of a CAES system would increase the profitability for the new Tariff for wind systems set by the Egyptian government with a NPV of $306m compared to a NPV of$207m of a stand-alone wind system at the end of 25 years of operation. Also, the economic benefits increase if the government provides subsidies for new installations of renewable energy systems, or by lowering the interest rates

Assessing the economics of large Energy Storage Plants with an optimisation methodology

Power plants, such as wind farms, that harvest renewable energy are increasing their share of the energy portfolio in several countries, including the United Kingdom. Their inability to match demand power profiles is stimulating an increasing need for large ESP (Energy Storage Plants), capable of balancing their instability and shifting power produced during low demand to peak periods. This paper presents and applies an innovative methodology to assess the economics of ESP utilising UK electricity price data, resulting in three key findings. Firstly the paper provides a methodology to assess the trade-off “reserve capacity vs. profitability” and the possibility of establishing the “optimum size capacity”. The optimal reserve size capacity maximizing the NPV (Net Present Value) is smaller than the optimum size capacity minimizing the subsidies. This is not an optimal result since it complicates the incentive scheme to align investors and policy makers' interests. Secondly, without subsidies, none of the existing ESP technologies are economically sustainable. However, subsidies are a relatively small percentage of the average price of electricity in UK. Thirdly, the possibility of operating ESP as both as a reserve and do price arbitrage was identified as a mean of decreasing subsidies for the ESP technologies