Energy storage has the potential to provide multiple services to several sectors in electricity industry and thus support activities related to generation, network and system operation. Hence aggregating the value delivered by storage to these sectors is paramount for promoting its efficient deployment in the near future, which will provide the level of flexibility needed to deal with the envisaged high renewables share and the increase in peak demand driven by transport and heating electrification. In this context, we develop a Mixed Integer Linear Programming (MILP) model to schedule operation of distributed storage by coordinating provision of a range of system services which are rewarded at different market prices. The model maximises distributed storage's net profit while providing distribution network congestion management, energy price arbitrage and various reserve and frequency regulation services through both active and reactive power control. We demonstrate benefits associated with the coordination of these services and its impacts on commercial strategies to determine optimal multi-service portfolios in the long term. We also demonstrate the value of reactive power control to support not only distribution network congestion management, but also efficient trading of energy and balancing services which are usually treated through active power-only control.In addition, we use the model to price the service of distribution network congestion management and propose an efficient investment policy to upgrade distribution network capacity in the presence of distributed storage. Finally, several case studies under current market conditions in Great Britain (GB) demonstrate that distributed storage revenues associated with frequency control services are significantly more profitable.

Abstract-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 (DNO). Through various case studies based on the Great Britain (GB) system, we demonstrate that although operational policies focused on battery damage reduction will lead to a revenue loss in the shortterm, 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.Index Terms-Distributed energy storage, multi-service portfolios, degradation, temperature control, power system economics. I. NOMENCLATURE A. Parameters

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Decarbonisation of the electricity system requires significant and continued investment in low-carbon energy sources and electrification of the heat and transport sectors. With diminishing output and shorter operating hours of conventional large-scale fossil fuel generators, there is a growing need and opportunity for other emerging technologies to provide flexibility in the context of grid support, balancing, security services, and investment options to support a cost-effective transition to a lower-carbon energy system. This article summarises the key findings from a range of studies investigating the potential benefits and challenges associated with the future low-carbon energy system. The key challenges associated with balancing local, national and regional objectives to minimise the overall cost of decarbonising the future energy system are also discussed. Furthermore, the paper highlights the importance of cross-energy vector flexibility, and coordination across electricity, heat, and gas systems which is critical for shaping the future low-carbon energy systems. Although most of the case studies presented in this article are based on the UK, and to some extent the EU decarbonisation pathways, the overall conclusions regarding the value of flexibility are relevant for the global energy transition.

Abstract-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.Index Terms-Electricity markets, energy storage, market power, mathematical program with equilibrium constraints. NOMENCLATURE A. Indices and SetsIndex of time periods running from 1 to Index of producers running from 1 to Index of generation blocks running from 1 to Index of demand blocks running from 1 to B. Parameters Length of market horizon (hours),