The continuous development of Electricity Storage Systems (ESS) technologies has made them interesting choices in the utility scale electricity market. Renewable sources intermittency, load management and power quality are the major purposes of ESS investment in grids. Their primary goal is to technically find the best solution for those problems, while the economic profits pass through that. However, in the increasingly competitive market environments, ESS would possibly be able to be operated simply to maximise profits for the investor, without aiming in a specific technical problem solution. In that sense, ESS follow the simple guideline oftrading wholesale electricity; purchasing cheap and selling expensive electricity. Another characteristic of today's electricity markets is that the load pattern becomes more erratic, having higher peaks and the load factor ofthe generation and grid falls. Utilities use Demand-Side Management (DSM) to control the demand. One of the features of this control is the peak shaving and shifting of load to off-peak hours. This research optimises the operation ofESS; it identifies the best combination ofcharging and discharging operations (duration and timing within a management period) aiming in maximisation of profits, in two options of management periods; one-day and three-day. Three very important elements of the analysis is the extent in which the profitability ofESS is affected by the existence ofDSM programmes in the market, whether the ESS can be granted with emissions allowances and up to which installed capacity of ESS in the electricity network the profits are positive. For this purpose, a dynamic optimisation model has been built, which incorporates a deterministic model as a real case of application with specific values of parameters. The dynamic modelling assesses the point where the investments in power capacity of ESS show their maximum achieved profits per installed MW, in combinations of four main options: DSM, NoDSM, 24h and 72h management period. The deterministic model aims at the optimisation ofthe allocation ofthe charge and discharge operations, simulating a real situation with specific data and parameters. The results show that DSM programmes can have substantial impacts on net revenues and profits achieved by ESS, but not such, on variable costs and revenues. Profitability falls and amongst the storage technologies tested, only those with high electrical round trip efficiency and low replacement costs can be viable investment options. So, the extent of DSM application in the market can influence storage profitability in a variable way. High capital costs and low efficiencies are the first factors to work prohibitively, alongside with DSM, to the profitability ofESS. Investigation of extending the management period from one to three days, has given higher net revenues with relatively smaller increase of discharged electricity. The indirect emissions d'le to the charging operation of the ESS depend on the primary source of energy used to generate the electricity which was stored and therefore, the ESS cannot be granted of emissions allowances in the way they are considered in this research. However, if there are bilateral trading agreements between renewable energy generators and the operators of the ESS, then the avoided emissions of ESS would be positive and the profitability would grow from the participation in the ETS. In the case that the regulations could recognise some economic benefits for ESS (like they do for renewable sources) they could stand more easily and quickly in the competitive electricity market. Funding opportunities for covering the capital cost and special rates for selling electricity to the network and for providing ancillary services can be some of them.
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