Roberto Moreira

Effect of Battery Degradation on Multi-Service Portfolios of Energy Storage

In an electricity market environment, energy storage plant owners are remunerated for the provision of services to multiple electricity sectors. Some of these services, however, may accelerate battery aging and degradation and hence this needs to be properly balanced against associated services remunerations. In this framework, we propose a combined economic-degradation model to quantify effects of operational policies (mainly focused on constraining State of Charge -SOC- to prescribed levels in order to reduce effects of aging) on gross revenue, multi-service portfolios, degradation and lifespan of distributed energy storage plants that can provide multiple services to energy and balancing market participants and Distribution Network Operators. Through various case studies based on the Great Britain system, we demonstrate that although operational policies focused on battery damage reduction will lead to a revenue loss in the short-term, such loss can be more than compensated by long-term revenues due to a lengthier battery lifespan. We also demonstrate that operational policies to reduce battery degradation mainly affect services related to the energy (rather than balancing) market, which represents a smaller proportion of the overall revenue streams of a distributed storage plant. The model is also used to study effects of ambient temperature fluctuations.

Opportunities for Energy Storage: Assessing Whole-System Economic Benefits of Energy Storage in Future Electricity Systems

Any Cost-effective transition toward low-carbon electricity supply will necessitate improved system flexibility to address the challenges of increased balancing requirements and degradation in asset use. Energy storage (ES) represents a flexible option that can bring significant, fundamental economic benefits to various areas in the electric power sector, including reduced investment requirements for generation, transmission, and distribution infrastructure as well as reduced system operation and balancing costs. The additional flexibility offered by ES could also significantly reduce the requirement for investment in low-carbon generation capacity while achieving the established carbon intensity targets. Moreover, ES may present significant option value, as it can provide flexibility for dealing with uncertainty in future system development.

Synergies and conflicts among energy storage services

Energy storage can provide services to several sectors in electricity industry, including generation, transmission and distribution and support a cost-effective transition to a low carbon electricity industry. Sharing storage plants energy and power capacity for multiple services portfolios leads to conflicting or synergic interactions among services. In this context, the proposed methodology determines interactions among services for distributed energy storage plants, including energy arbitrage, peak demand shaving and various balancing services, and assesses the impact that such interactions have on storage plant remunerability in a multiple service business model framework for distributed energy storage. We demonstrate that services interact differently depending on markets and system operating conditions. We also find that correlation between energy market and local system conditions is important to determine whether energy arbitrage conflicts with further services.

Optimal multi-service business models for electric vehicles

Realizing the significant potential of electric vehicles (EV) in emerging low-carbon power systems requires the development of suitable business models for EV owners and aggregators. Previous works have focused on silo analyses of single service business models which neglect the full economic potential of EV flexibility. This paper addresses this challenge by developing a novel modeling framework for optimizing the provision of multiple inter-dependent services by an EV aggregator, to determine the business portfolio maximizing the overall revenue. Case studies in the context of the UK system quantify the overall cost and revenue achieved through participation of an EV aggregator in multiple market segments and analyze the interdependencies between the provisions of multiple services. A range of sensitivity analyses also analyze the impact of different EV operating policies and parameters on the overall cost and revenue as well as the optimum portfolio of provided services.

Strategic capacity withholding by energy storage in electricity markets

Although previous work has demonstrated the ability of large energy storage (ES) units to exercise market power by withholding their capacity, it has adopted modeling approaches exhibiting certain limitations and has not analyzed the dependency of the extent of exercised market power on ES operating properties. In this paper, the decision making process of strategic ES is modeled through a bi-level optimization problem; the upper level determines the optimal extent of capacity withholding at different time periods, maximizing the ES profit, while the lower level represents endogenously the market clearing process. This problem is solved after converting it to a Mathematical Program with Equilibrium Constraints (MPEC) and linearizing the latter through suitable techniques. Case studies on a test market quantitatively analyze the extent of capacity withholding and its impact on ES profit and social welfare for different scenarios regarding the power and energy capacity of ES.