Abstract
With continuous technological improvement and economic development of energy storage, distributed energy storage (DES) will be widely connected to the distribution network. If fragmented DES systems are aggregated to form a distributed energy storage aggregator (DESA), the DESA will have great potential to participate in the day-ahead energy and reserve market and the balancing market. The DESA could act as a mediator between the market and DES consumers, enabling beneficial coordination for DES owners and power systems. This paper presents a bilevel optimization model for DESAs in the energy and reserve market under wind power uncertainties. In the lower-level problem, generating companies, wind power plants (WPP), and DESAs are optimized for scheduling day-ahead (DA) energy and the reserve market. In the upper-level problem, operational strategies for DES systems and DESAs are designed to deal with wind power uncertainties in the balancing market. The DESA splits its resources between the energy and reserve markets so that it can reduce total power system consumption, and mutual profit for the system and end customers is achieved. This model is formulated as a mixed-integer linear programming (MILP) program, which can be solved with commercial software. The validity of the bilevel optimization model is verified by the eight-node test transmission system and IEEE-33 bus distribution system.
Highlights
With the increase of electric vehicles and distributed power generation connected to the distribution network, the distribution system operator (DSO) needs more high-quality demand-side resources
The major contributions of this paper are as follows: (1) We propose a new bilevel optimization model for distributed energy storage aggregator (DESA) taking part in the day-ahead energy and reserve markets and the balancing market; (2) we establish an effective and extensible model of DESA aggregation considering the operational constraints of distributed energy storage (DES) in distribution network; and (3) we contrast optimal strategies of DESA in different uncertain scenarios with wind power participation
In order to examine the effectiveness of the proposed optimization model, an eight-bus test system and IEEE-33 bus distribution network test system are examined
Summary
With the increase of electric vehicles and distributed power generation (distributed photovoltaic, wind power generation, combined heat-cold power units) connected to the distribution network, the distribution system operator (DSO) needs more high-quality demand-side resources. In [20], a cost model of load curtailment for different services is proposed, allowing the demand response aggregator and generation company to participate in/schedule the energy and reserve (ancillary) market. ESSs can participate in both the energy and reserve markets, because they can reduce power system operation cost and improve system stability These different types of aggregators are able to purchase cheaper energy, provide ancillary services more economically, and reduce carbon more effectively than traditional generation sources. The major contributions of this paper are as follows: (1) We propose a new bilevel optimization model for DESAs taking part in the day-ahead energy and reserve markets and the balancing market; (2) we establish an effective and extensible model of DESA aggregation considering the operational constraints of DES in distribution network; and (3) we contrast optimal strategies of DESA in different uncertain scenarios with wind power participation.
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