The goal of FLEXGRID is to facilitate energy sector stakeholders (DSOs, TSOs, ESPs and RESPs) to: i) easily and effectively create advanced Energy Services (ESs), ii) interact in a dynamic and efficient way with their environment (electricity grid) and the remaining of the stakeholders, and iii) automate and optimize the planning and the operation of their ESs. In this way, FLEXGRID envisages secure, sustainable, competitive, and affordable ESs. This section clarifies the objectives of FLEXGRID by: i) categorizing them as orthogonally as possible, ii) presenting them accurately, and ii) revealing the interactions among them. In particular, the objectives set by FLEXGRID are:

Objective 1: An Automated Trading Platform (ATP) able to provide as a service the composition and the operation of energy markets

The first objective of FLEXGRID is the development of an advanced ATP that is able to support the optimal and automated planning and operation of the markets, as required by modern stakeholders in order to interact with each other for offering competitive ESs through the advanced flexibility trading: i) in B2B form, between ESPs and DSOs/TSOs, and ii) in B2C form, between EPS and end users. Thus, FLEXGRID will develop:

  1. Innovative liberalized energy market architectures that facilitate mitigation of market power and dispose the advanced features that modern Market Mechanisms are able to offer.

  2. A holistic trading data model and trading service composition able to support advanced and easy flexibility trading, by acting as a language that models flexibility assets and composes flexibility services.

  3. Blockchain-supported trading services for easy and secure service composition and multilateral or P2P trading (participation of more than two trading parties, in contrast to the usual case of bilateral trading).

  4. Advanced B2B market mechanisms that: i) allow DSOs/TSOs to exploit innovative services through a more efficient market clearing algorithm that FLEXGRID will develop in order to reduce the system cost and ii) facilitate ESPs to analyse its data in order to improve their strategies and mitigate their risks.

  5. Advanced Retail Market Mechanisms (B2C) able to harmonize very dynamically the end-user consumption patterns based on the dynamic prices in various markets, not only through the monitoring of the latter, but also through advanced learning algorithms.

  6. A modular by design architecture that ensures compatibility of the proposed ATP platform with the legacy technology of current energy sector stakeholders (e.g., DSO/TSO SCADA systems).

Objective 2: Automated planning of DSO’s/TSO’s ESs

The second objective of FLEXGRID is to automate the planning process of the ESs offered by DSOs/TSOs through the use and evolvement of recent research advances in Optimal Power Flow (OPF) algorithms. In more detail, the objective here is to seek a trade-off between the minimization of CAPEX in the design of the electricity grid and the maximization of network robustness for obtaining competitive and secure electricity grids. The proposed FLEXGRID platform will provide services such as:

  1. Efficient, accurate and dynamic Advanced Distribution Monitoring (ADMo) able to: i) inform DSOs/TSOs on the monitoring architecture that they have to develop and ii) intelligently exploit monitoring output towards OPF and market clearing algorithms.

  2. Optimal ESS sizing and siting (which may be under the ownership/management of the DSO/TSO or of external stakeholders/ESPs that interact with DSO/TSO through FLEXGRID’s ATP) through the use of advanced algorithms that take into account the history and prediction of: i) the RES Production Curves (RPCs) and their location, ii) the Aggregated ECCs (AECCs) and the flexibility levels of the participating consumers for a given network location, iii) the underlying network topology, and iv) the local flexibility market prices, and their predictions and accuracy levels.

  3. Algorithms able to determine market power mitigation aware network upgrades (e.g., capacity and/or security/fault tolerance upgrades) in electricity grid through the quantification of the relationship between CAPEX increase (investments for upgrades and changes) and OPEX reduction (expenses in the flexibility markets) that these modifications and upgrades will cause. Thus, ESPs become more competitive and sustainable and ESs for end users will have lower cost.

  4. Fault tolerance services through algorithms able to intelligently process the dynamic input from the ADMo and derive conclusions and actions to be taken to address network faults, problems and events. These types of services will be integrated with dynamic markets towards disaster management.

Objective 3: Optimal operation of DSO’s/TSO’s ESs

The third objective of FLEXGRID is the optimal operation of the electricity grids in terms of low cost and high stability (tolerance/robustness to the very dynamic and distributed RES production). In particular, electricity grid aware, dynamic management of: i) the DSO’s/TSO’s flexibility assets and ii) ESPs flexibility assets is targeted through FLEXGRID’s ATP platform (Objective 1). In order to achieve this, FLEXIGRID will develop:

  1. Innovative Market Clearing (MC)/OPF algorithms that allow the operation of the electricity grid in a broader area (increase market freedom), thus reducing the cost of energy services.

  2. Scalable and Multi period MC/OPF algorithms with low computational overhead that can make efficient use of internal and external flexibility assets (exploitable through ATP) whose management spans across multiple time periods regarding: i) DSM (load shifts) and ii) ESS for higher RES exploitation.

  3. Robust MC/OPF algorithms able to address the inaccuracy of market, RES and AECC forecasters that multi-period OPF introduces based on recent advances in robust and stochastic optimization.

  4. Dynamic interaction with DSM and ESS systems, directly or through ATP, by using advanced optimization algorithms that take into account the historical data as well as the predictions on: i) the RES Production Curves (RPCs) given their corresponding location, ii) the Aggregated ECCs (AECCs) and the flexibility levels of the participating consumers at a given network location, iii) the underlying network topology, and iv) the local (e.g. ATP) market prices.

Objective 4: Automated Planning of ESP’s BMs (assets and policy)

The fourth objective relates to the development of models for the automation of the planning of the services offered by ESPs. As described earlier, ESPs are private companies, energy cooperatives, or public organizations that: a) buy energy from the wholesale market and/or P2P markets, b) are DSM capable (having their own portfolio of end users/customers and selling energy through their participation in retail markets), c) dispose or manage ESS, d) participate in flexibility markets in order to deliver competitive and profitable energy services, e) possibly combine these services with other revenue sources. In more detail, FLEXGRID will offer to ESPs services such as:

  1. Exploitation in the BMs of ESPs of innovative FLEXGRID’s Market Clearing algorithms and data model, which improve market freedom and reduce market power. In this way, investments are incentivized and the cost of ESs becomes more competitive.

  2. Optimal ESS sizing and siting according to: i) the estimated prices in energy markets, ii) the estimated ECCs and flexibility levels of their consumers, iii) the underlying topology of the electricity grids, and iv) the interaction with DSOs/TSOs.

  3. Planning of interaction policy with energy markets and innovative MC (wholesale market, ancillary services market, retail market) towards the maximization of stacked revenues and the design of more competitive ESs.

  4. Design of dynamic ESP’s retail market scheme (DSM scheme) able to incentivize and treat consumers (distributed flexibility asset owners) in a fair way, according to the flexibility levels (changes in their ECC) they exhibit. Through these models, ESPs will provide competitive services (attractive to end users) and will dynamically maximize the stacked revenues derived from their participation in all energy markets.

Objective 5: Optimal operation of ESP’s BMs

The fifth objective is the mathematical modelling of the dynamic optimization process of the ESP’s services. FLEXGRID will minimize the OPEX of the offered services by developing:

  1. AI technologies in order to deliver accurate and dynamic forecasters to estimate: i) the RES production, ii) the behaviour (price trends) of modern electricity markets (day ahead and real time) and iii) the accuracy level of the forecasts to be exploited in automated policy enforcers (optimize interactions and plan/operate assets according to high-level rules, such as minimum/average profit maximization, etc.).

  2. Efficient and stable interaction with other stakeholders (B2B interactions) and energy markets by considering price makers (participants of high enough size to have an impact on market prices) and not price takers (advanced MPEC/EPEC algorithms which enhance market equilibrium points with attributes that constitute energy markets more open and efficient).

  3. Models that provide the dynamic co-optimization of ESS and DSM systems in order to reveal the added value of the interaction between these two flexibility asset types.

  4. Dynamic tuning of the parameters of the DSM scheme according to: i) the forecasted prices in energy markets, ii) the energy available in the ESS systems, and iii) the dynamic flexibility levels of participating users.

Objective 6: Services to RES Producers (RESPs)

The sixth objective of FLEXGRID is the provision of services to RES producers. In this way, RESPs will be able to plan and operate efficiently their services according to the environment they operate in (local markets). More specifically, FLEXGRID will develop:

  1. Advanced RES forecasting tools that provide dynamic estimates of: i) the RES Production Curves (RPCs) based on historical and other data for a specific location and ii) the accuracy of the prediction. These forecasts will help hedge the risks and allow the sustainable commercial exploitation of the energy produced by RES.

  2. Planning services that optimize the RES compositions (in terms of RES location, and quantity for each type in the mixture) and the ESS according to: i) RES forecasting algorithms, ii) available CAPEX and iii) the history and predictions of the prices in energy markets.

  3. Dynamic ESS and energy trading scheduling services, which include: i) dynamic management of ESS systems (charge/discharge schedulers of the ESS managed by RESPs) and ii) schedulers that determine how RESPs will interact with the (day ahead and real-time) markets. The goal here is to increase RESP’s assets “dispatchability rate” in order to efficiently participate in multiple energy markets in the future.

Objective 7: A modular, configurable, customizable, open, and extendable S/W platform

The proposed cloud-based FLEXGRID S/W platform will be designed and developed so that it is:

  1. Modular, meaning that there will be well-designed technical APIs allowing the low-level flexibility assets to be automatically transformed into trading assets (middle level) and ultimately give rise to novel flexibility services (upper level).

  2. Configurable, in the sense that the data exchange modelling will be abstract enough to facilitate the easy integration of the proposed FLEXGRID platform with the existing legacy technology of energy sector stakeholders (e.g. DSO/TSO management systems) following the well-established standardization efforts.

  3. Customizable, meaning that the individual S/W toolkits (cf. middle level) will provide a wide variety of options for each stakeholder to run various types of exhaustive “what-if” scenarios with respect to many differentiated business cases. This feature is expected to boost the FLEXGRID’s exploitation activities.

  4. Open, in terms of being able to deliver Energy Information Distribution as a Service (EIDaaS) to 3rd parties, facilitate cross-border collaborations among stakeholders from different EU member states and generally disseminate the project’s foreground knowledge via a clear data management plan.

  5. Extendable, in terms of being able to facilitate the creation, composition and trading of many more advanced energy meta-services in the future. The APIs will be rich and flexible enough to allow future platforms to be integrated and avoid vendor lock in.

Last, but not least, the platform will respect the privacy and the anonymity of the participating users/stakeholders, while their unreserved consent will always be a prerequisite.

Objective 8: Pilots with existing and prestigious stakeholders in Energy Sector

FLEXGRID will conduct a wide range of pilots in order to evaluate the aforementioned services and evolve its platform empirically through the feedback obtained from real stakeholders. In more detail, the pilots planned by FLEXGRID involve:

  • HOPS (Croatian TSO), which will provide information and infrastructure related to the electricity grid’s topology and dynamic conditions. In addition, HOPS will evaluate FLEXGRID innovative algorithms relevant with market operation/participation in existing balancing and ancillary services that it currently operates (ESS use in high RES penetration scenarios).

  • NPC (in cooperation with its mother company Nord Pool), which will provide real data from the current Nord Pool market’s operation (i.e., day-ahead, intraday, balance/reserve market prices etc.) and innovative BMs for ancillary services based on the current practice and experience in this area.

  • NODES, which is a joint venture between Agder Energi and Nord Pool with progressive and existing services that include flexibility provision. NODES will provide data from its interaction with prestigious Demand Response aggregators and innovative BMs towards this goal. In addition, NODES will evaluate FLEXGRID’s market place in the environments where it already operates.

  • UCY, which disposes an experimentation framework that includes: 300 houses (end users with smart meters) and ESS systems (shared and individually controlled). Through this pilot, FLEXIGRID’S AI algorithms for DSM will be trained using real-user feedback on consumption preferences, comfort levels and intrusiveness.

  • Electricity Authority Cyprus (EAC) (see section 4.6/ letter of intent), which will provide a real use case and real data towards the generation of a flexibility aggregation market. EAC will advise FLEXGRID’s consortium on the real and existing challenges from the DSO’s point of view (e.g., market and OPF requirements, type of interaction, etc.).

  • WEMAG, which (as a progressive ESP) will provide BMs and real data from progressive ancillary services that involve large scale ESS systems and require close interaction between ESPs and DSOs/TSOs. In cooperation with bnNETZE, WEMAG will evaluate in a real business environment the advanced and rich interaction between ESP and DSO/TSO that FLEXGRID’s architecture proposes.

  • AIT will be responsible for the evaluation of FLEXGRID’s frequency control algorithms, by exploiting its existing connections with TSOs, and of voltage control algorithms, by exploiting its existing connections with DSOs.