KIWI POWER LTD

CHALLENGE: Demand response (DR) is central to the successful evolution of a new low carbon electricity system in order to deliver grid flexibility & stability, however it is progressing slowly in the EU due to technological barriers which prevent widespread uptake: high in cost hardware (€4.000 - €6.000); not specifically designed for DR → lack critical functionality (e.g. wireless communication, integration of renewables); & not sufficiently open for wider industry participation. PROPOSED SOLUTION: To address the need for innovations that overcome principal barriers to DR, this project seeks to advance KPLs Energy Management Platform, KEMP, from a prototype demonstrated in a relevant environment (TRL6) to complete & qualified commercial prototype (TRL8). KEMP is a low cost, automated ancillary services platform which consists of: [1] Unique hardware: multi-asset control; first platform to integrate renewable assets; wireless communication between assets → reduced installation cost; & sec. by sec. meter readings – requirement for Frequency Response programmes. [2] Innovative software: cloud based – for greater scalability; flexibility & remote monitoring, forecasting model - for integration of renewables; & optimisation engine - to max. revenues. END USERS: [1] Initial target = large scale commercial & industrial (C&I) orgs with high MW capacity (>1MW) e.g. financial, telecoms, hospitals, hotels etc. Asset types: DRUPS systems & HVAC. [2] Secondary target = SMEs with low MW capacity (50kW< capacity < 1MW) incl. Water Pump Stations, Small Data Centres, Retail Stores. Asset types: Variable Speed Motors, HVAC, UPS systems etc. STUDY OBJECTIVES: tech validation, market analysis, economic & business assessment, operational capacity analysis. Activities will be delivered within a 4 month period, & result in a comprehensive feasibility report detailing the next steps towards development & commercialisation, forming the basis of the SMEI Phase II Business Plan.

Peak electricity demand is becoming an increasingly significant problem for UK networks as it causes imbalances between demand and supply with negative impacts on system costs and the environment. The residential sector is responsible for about one third of overall electricity demand (DECC, 2013). During peak demand, electricity prices in wholesale markets could fluctuate from less than 0.04 Euros/kWh to as much as 0.35 Euros/kWh (Torriti, 2015). In the future the peak problem is expected to worsen due to the integration of intermittent renewables in the supply mix as well as high penetration of electric vehicles and electric heat pumps. Understanding what constitutes peaks and identifying areas of effective load shifting intervention becomes vital to the balancing of demand and supply of electricity. Whilst there is information about the aggregate level of consumption of electricity, little is known about residential peak demand and what levels of flexibility might be available. REDPeak will fill this gap. The overall aim of REDPeak is to analyse the variation in sequences of activities taking place at times of peak electricity demand with a view to identify clusters of users which might provide flexibility for peak shifting intervention. The project will analyse 10-minute resolution time use activity data from the UK Office for National Statistics Time Use Survey with a view to derive information about occupancy and synchronisation of activities. Markov chains will be used to model load profiles in combination with appliance-specific parameter data. Since Markov chains have proven effective at generating electricity load profiles except for peak times, REDPeak will develop Hybrid Monte Carlo modelling to account for demand moving in larger steps during peak periods. Sequence analysis will be used to mine activities at periods of peak electricity demand. REDPeak will cluster respondents according to sequences of activities and analyse to what extent appliance-specific control variables explain activities at specific times of the day. Three datasets will be used for direct validation between metered data and time use data. Findings on sequence analysis will feed into algorithms for automated demand management or Demand Side Response.

NOVICE will develop and demonstrate a new business model in building renovation to better monetize energy efficiency by consolidating services and subsequent revenue streams from both energy savings and demand response. In order to do so NOVICE introduces new actors (aggregators) in building energy upgrade projects and fosters their collaboration with ESCOs, financing institutions, facilities management companies, engineering consultants to facilitate the roll out of the dual (grid services and energy efficiency) energy services model. The main business bond to be forged between ESCOs and Aggregators through NOVICE will allow their seamless collaboration in exploiting economies of scope and scale along with risk sharing on implementing building energy renovations. That business relationship will take the form of a MoU and will result in the composition of a new enhanced EPC template that can deliver the successful deployment of the dual energy services scheme in building renovation. The enhanced EPC template and the overall dual energy services scheme will be scrutinized by a financing institution to assess its bankability and identify the appropriate financing mechanisms for initiating and rolling out investments under that scheme. NOVICE throughout its duration targets to trigger the initiation of more than 20.8 m EUR of investments in building renovation based on the dual energy services model that will result in primary energy savings of more than 25.2 GWh/year. To achieve that target NOVICE brings together a highly experienced consortium that consists of stakeholders from the entire value chain (research institutions, technology vendors, engineering consultants and facilitators, Aggregators, ESCOs, Financing institutions, Facilities Management companies) of building renovation. Strong participation of SMEs (6 out 9 partners) demonstrate the commercial exploitation potential of the NOVICE outputs and supports the successful rollout of the NOVICE business model.

Smart automated Demand Response (DR) represents a valid alternative to grid reinforement for electricity Distribution System Operators (DSOs) to procure in a cost-effective way the necessary flexibility for integrating larger shares of intermittent RESs, while not compromising security of supply and network reliability. However DR potential has been exploited so far to a very limited extent due to a number of technological, regulatory, economic barriers. To cope with these challenges, eDREAM will develop and make available a novel near real time DR scalable secure blockchain-driven technological and business framework aimed to optimize aggregated system services flexibility provisioning to DSOs. The project will research and develop tools and services for: i) optimal DR system design, which includes early detection of flexibility potential via multimodal fusion of aerial, LIDAR and thermal imaging, end users profiling and segmentation by leveraging on big data clustering and large data sets visual interactive exploration and DR optimization services for energy end users; ii) optimal DSO-driven Demand Response management, including novel applications of blockchain decentralized ledger for secure data handling, market-based microgrid control and near real time closed loop DR verification aimed to improve system observability and enable fair DR financial settlement. Novel flexibility market and services/products design, as well as cooperative DSO-aggregator business models enabled by incentive sharing will validate the eDREAM DR technical concept from the economic perspective. The eDREAM technologies will be extensively validated in a lab-based pilot (Greece), followed by two field pilots, a C&I VPP-based optimal aggregated flexibility management in UK and a mixed stationary and movable (EVs) loads flexibility microgrid-level optimized flexibility management in Italy.

DELTA proposes a DR management platform that distributes parts of the Aggregator’s intelligence into lower layers of a novel architecture, based on VPP principles, in order to establish a more easily manageable & computationally efficient DR solution, ultimately aiming to introduce scalability & adaptiveness into the Aggregator’s DR toolkits; the DELTA engine will be able to adopt & integrate multiple strategies & policies provided from its energy market stakeholders, making it authentically modular & future-proof. DELTA will also deliver a fully autonomous architectural design, enabling end-users to escape the hassle of responding to complex price/incentive-based signals, while facilitating active, aware & engaged prosumers, based on innovative award schemes, a social collaboration platform & enhanced DR visualisation. Provision of full-scale market & grid services will be made possible by delivering explicit & implicit-based DR elasticity services, while pushing current market regulatory limitations so that they can be surpassed, and satisfying potential grid constraints related to flexibility activation through Multi-Factor Forecasting and Deep Reinforcement Learning Profiling. Furthermore, DELTA will propose & implement novel multi-agent based, self-learning energy matchmaking algorithms to enable aggregation, segmentation & coordination of several diverse supply & demand clusters, designed end-to-end using well-known, open protocols (i.e. OpenADR), for increasing interoperability. DELTA will set the milestone for data security in future DR applications by not only implementing novel block-chain methods & authentication mechanisms, but also by making use of Smart Contracts which would further secure & facilitate Aggregators-to-Prosumers transactions. Two pilots in UK & Cyprus will realise the DELTA concept, covering a wide variety of residential/tertiary loads (>11GWh), RES generation (>14GWh) & energy storage systems (>9MWh) (average annual measurements).