Optimal Scheduling Strategies of Distributed Energy Storage Aggregator in Energy and Reserve Markets Considering Wind Power Uncertainties

Zengqiang Mi, Yulong Jia, Junjie Wang, Xiaoming Zheng
2018 Energies  
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
more » ... 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. Energies 2018, 11, 1242 2 of 17 systems' aggregation information and it would be difficult to manage. The distributed energy storage aggregator (DESA) [5] adopts advanced communication and control technologies to aggregate and control DES systems in the distribution network. In this way, it can form a large-energy and high-power schedulable resource pool. This resource pool could provide reserve capacity and participate in the energy market on multiple time scales, and the DESA is helpful for quickly maintaining the stability of system frequency, voltage, and the rest of ancillary services. DESAs will play an important role in the power system. They do not replace existing components of the electricity value chain but rather allow the existing ones to do their job better and cheaper [6] . On the one hand, the optimized operation of DES systems mainly enables them to provide voltage support, reduce distribution losses, increase capacity support, buffer variable wind and solar energy, and reduce expansion investment in the distribution network [7] . On the other hand, DESAs have the advantages of reducing transmission congestion, curtailing renewable energy, and deferring transmission in investment for transmission system operators (TSOs). Moreover, DESAs could play an important role in price arbitrage, fast regulation, spinning reserve, power quality, and black start for independent system operators (ISOs). DESA represents a new tool (management strategies, control and optimization algorithms), which is valuable for guaranteeing system stability, reducing system cost, and increasing customer profit. The focus of this paper is to define the features of the DESA and model its strategic behavior in the wholesale market considering wind power uncertainties. In this paper, DESA is designed as a flexibility manager and a balance responsible party. A good overview on the planning and operation of DES in a distribution network can be found in [8, 9] . In [10], a new method for optimal integration of DES at minimum cost is proposed. The optimal method allows DES to provide voltage support, delay network upgrade, and offer aggregation resources to TSOs. In [11] , an algorithm and optimization participation strategies are presented that allow aggregators to cooperatively control such DES systems in accordance with electricity market rules and interactive strategies. In [12], a comprehensive planning framework for ascertaining the most cost-effective siting and sizing of DES to maximize the benefits in the distribution network is designed. A strategy for optimal integration of DES systems to improve the load hosting ability is presented in [13] . The strategy model considered two primary factors-Distribution Network Operator (DNO) cost and DES cycling cost-to offer three services-voltage regulation, peak shaving, and loss reduction. In [14] , a comprehensive optimal allocation model of DES considering operation strategy is presented. The problems of optimal capacity and sizing of DES are solved by minimum cost of DES operation and investment. In [15] , an effective method is proposed that allocate DES systems for spinning reserve or frequency regulation to improve system reliability. Research on interactive modes and operational strategies of different types of aggregators to participate in the electricity market and ancillary services have also been proposed in the literature. A bidding strategy is proposed in [16] for electric vehicle (EV) aggregators to maximize their profits by trading energy and regulation reserves in the electricity market. The EV aggregator is the required mediator between a large number of EVs and power system operators and could provide some services to power systems. Thermostatically controlled load (TCL) aggregators are introduced in [17,18]. They could provide load following services and regulation reserves in the power system. In [19], a day-ahead dispatch framework for virtual power plants (VPPs) in joint energy and regulation reserve market considering the penalty cost of CO 2 emissions is presented. 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. A bilevel optimization model of distribution companies in the wholesale reserve market is proposed in [21] . In the proposed model, the distribution company and independent system operator are modeled in the lower-level and upper-level problem, respectively. Energy storage systems (ESSs) that integrate renewable energy resources to provide arbitrage and ancillary services are introduced in [22] [23] [24] . 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
doi:10.3390/en11051242 fatcat:oiu3lbl7q5f3rnfsqgsbg6x7q4