Data analysis of battery storage systems

Battery energy storage systems can assist distribution network operators (DNOs) to face the challenges raised by the substantial increase in distributed renewable generation. A challenge is that these resources are intermittent and often ‘invisible‘ to the DNO. If not monitored, the aggregate size of small embedded generation resources can cause thermal wearing of distribution assets and voltage excursions, especially in sunny/windy periods with insufficient local demand. Several developers of energy storage solutions, with technologies such as lithium-ion (Li-ion) batteries, offer their products to address peak shaving, frequency and voltage control needs within the network. Once deployed within the energy network batteries experience capacity degradation with usage, these companies will need to incorporate methods from prognostics and health management (PHM) in order to better manage their products. The main deliverable of this project

Game-theoretic modeling of curtailment rules and network investments with distributed generation

Renewable energy has achieved high penetration rates in many areas, leading to curtailment, especially if existing network infrastructure is insufficient and energy generated cannot be exported. In this context, Distribution Network Operators (DNOs) face a significant knowledge gap about how to implement curtailment rules that achieve desired operational objectives, but at the same time minimise disruption and economic losses for renewable generators. In this work, we study the properties of sev

Efficient methods for approximating the Shapley value for asset sharing in energy communities

With the emergence of energy communities, where a number of prosumers invest in shared generation and storage, the issue of fair allocation of benefits is increasingly important. The Shapley value has attracted increasing interest for redistribution in energy settings — however, computing it exactly is intractable beyond a few dozen prosumers. In this paper, we first conduct a systematic review of the literature on the use of Shapley value in energy-related applications, as well as efforts to compute or approximate it. Next, we formalise the main methods for approximating the Shapley value in community energy settings, and propose a new one, which we call the stratified expected value approximation. To compare the performance of these methods, we design a novel method for exact Shapley value computation, which can be applied to communities of up to several hundred agents by clustering the prosumers into a smaller number of demand profiles. We perform a large-scale experimental comparison of the proposed methods, for communities of up to 200 prosumers, using large-scale, publicly available data from two large-scale energy trials in the UK (UKERC Energy Data Centre, 2017, UK Power Networks Innovation, 2021). Our analysis shows that, as the number of agents in the community increases, the relative difference to the exact Shapley value converges to under 1% for all the approximation methods considered. In particular, for most experimental scenarios, we show that there is no statistical difference between the newly proposed stratified expected value method and the existing state-of- the-art method that uses adaptive sampling (O’Brien et al., 2015), although the cost of computation for large communities is an order of magnitude lower

Real-time control of distributed batteries with blockchain-enabled market export commitments

Recent years have seen a surge of interest in distributed residential batteries for households with renewable generation. Yet, assuring battery assets are profitable for their owners requires a complex optimisation of the battery asset and additional revenue sources, such as novel ways to access wholesale energy markets. In this paper, we propose a framework in which wholesale market bids are placed on forward energy markets by an aggregator of distributed residential batteries that are controlled in real time by a novel Home Energy Management System (HEMS) control algorithm to meet the market commitments, while maximising local self-consumption. The proposed framework consists of three stages. In the first stage, an optimal day-ahead or intra-day scheduling of the aggregated storage assets is computed centrally. For the second stage, a bidding strategy is developed for wholesale energy markets. Finally, in the third stage, a novel HEMS real-time control algorithm based on a smart contract allows coordination of residential batteries to meet the market commitments and maximise self-consumption of local production. Using a case study provided by a large UK-based energy demonstrator, we apply the framework to an aggregator with 70 residential batteries. Experimental analysis is done using real per minute data for demand and production. Results indicate that the proposed approach increases the aggregator’s revenues by 35% compared to a case without residential flexibility, and increases the self-consumption rate of the households by a factor of two. The robustness of the results to uncertainty, forecast errors and to communication latency is also demonstrated

A multi-sectoral approach to modelling community energy demand of the built environment

This paper examines the major challenges associated with evaluating energy demand in the residential building sector in an integrated energy system modelling environment. Three established modelling fields are examined to generate a framework for assessing the impact of energy policy: energy system models, building stock models and dynamic building simulation. A set of profound challenges emerge when attempting to integrate such models, due to distinct differences in their intended applications, operational scales, formulations and computational implementations. Detailed discussions are provided on the integration of temporally refined energy demand, based on thermodynamic processes and socio-technical effects which may stem from new policy. A detailed framework is discussed for generating aggregate residential demands, in terms of space heating demand, domestic hot water demand, and lighting, appliance and consumer electronics demand. The framework incorporates a pathway for interpreting the effects of changes in household behaviour resulting from prospective policy measures. When long-term planning exercises are carried out using this framework, the cyclic effects between behavioural change and policy implementation are also considered. This work focused specifically on the United Kingdom energy system, however parallels can be drawn with other countries, in particular those with a mature privatised system, dominated by space heating concerns

Consider ethical and social challenges in smart grid research

Artificial intelligence and machine learning are increasingly seen as key technologies for building more decentralized and resilient energy grids. However, researchers must consider the ethical and social implications of these developments

Emerging business models in local energy markets: A systematic review of peer-to-peer, community self-consumption, and transactive energy models

The emergence of peer-to-peer, collective or community self-consumption, and transactive energy concepts gives rise to new configurations of business models for local energy trading among a variety of actors. Much attention has been paid in the academic literature to the transition of the underlying energy system with its macroeconomic market framework. However, fewer contributions focus on the microeconomic aspects of the broad set of involved actors. Even though specific case studies highlight single business models, a comprehensive analysis of emerging business models for the entire set of actors is missing. Following this research gap, this paper conducts a systematic literature review of 135 peer-reviewed journal articles to examine business models of actors operating in local energy markets. From 221 businesses in the reviewed literature, nine macro-actor categories are identified. For each type of market actor, a business model archetype is determined and characterised using the business model canvas. The key elements of each business model archetype are discussed, and areas are highlighted where further research is needed. Finally, this paper outlines the differences of business models for their presence in the three local energy market models. Focusing on the identified customers and partner relationships, this study highlights the key actors per market model and the character of the interactions between market participants

a systematic review of peer-to-peer, community self-consumption, and transactive energy models

Schwidtal, J. M., Piccini, P., Troncia, M., Chitchyan, R., Montakhabi, M., Francis, C., Gorbatcheva, A., Capper, T., Mustafa, M. A., Andoni, M., Robu, V., Bahloul, M., Scott, I. J., Mbavarira, T., España, J. M. E., & Kiesling, L. (2023). Emerging business models in local energy markets: a systematic review of peer-to-peer, community self-consumption, and transactive energy models. Renewable and Sustainable Energy Reviews, 179(June), 1-48. [113273]. https://doi.org/10.1016/j.rser.2023.113273 -- This publication is part of the work of the Global Observatory on Peer-to-Peer, Community Self-Consumption and Transactive Energy Models (GO-P2P), a task of the User-Centred Energy Systems Technology Collaboration Programme (Users TCP), under the auspices of the International Energy Agency. GO-P2P benefits from the support of Australia, Belgium, Ireland, Italy, the Netherlands, Switzerland, the United Kingdom and United States. GO-P2P is also supported by the EPSRC EnergyREV project EnergyREV (EP/S031863/1).The emergence of peer-to-peer, collective or community self-consumption, and transactive energy concepts gives rise to new configurations of business models for local energy trading among a variety of actors. Much attention has been paid in the academic literature to the transition of the underlying energy system with its macroeconomic market framework. However, fewer contributions focus on the microeconomic aspects of the broad set of involved actors. Even though specific case studies highlight single business models, a comprehensive analysis of emerging business models for the entire set of actors is missing. Following this research gap, this paper conducts a systematic literature review of 135 peer-reviewed journal articles to examine business models of actors operating in local energy markets. From 221 businesses in the reviewed literature, nine macro-actor categories are identified. For each type of market actor, a business model archetype is determined and characterised using the business model canvas. The key elements of each business model archetype are discussed, and areas are highlighted where further research is needed. Finally, this paper outlines the differences of business models for their presence in the three local energy market models. Focusing on the identified customers and partner relationships, this study highlights the key actors per market model and the character of the interactions between market participants.preprintauthorsversionpublishe