A novel IoT, DERMS and Blockchain-based Transactive Energy Software Solution for Smart Energy Grids
Future Smart Grid Challenges, faced by power system operators (ISO/IESO), power utilities (PU) and local distribution companies (LDC), include integrating, monitoring/predicting, controlling and trading with thousands of Renewable Energy Source (DER) assets within MV/LV distribution grids.The I-EMS Group team is providing a total solution including four computational modules to:
1. Predict the solar PV output profile (24 hours ahead) for any location, generator size and technology in north America.
2. Predict feeder level load profile (24 hours ahead) for any location and feeder capacity size in north America.
3. Simulate and optimize the distribution network based on the predicted PV and Load profiles (our DERMS App).
4. Trade with selected (and optimally scheduled DER assets and flexible loads) in the local grid by means of a secure, safe and reliable Blockchain based Transactive Energy App.
Integrating, Monitoring & Predicting, Controlling and Trading with thousands of Renewable Energy Source (DER) assets and flexible loads (as demand response participants) in Smart Energy Grids are going to be serious challenges to ISO/IESO, RTO, PU and LDC companies in a near future. New computational tools and software platforms are needed to mitigate the above-mentioned challenges for the MV/LV distribution network operators.
Traditional vs. Smart Energy Grids
Smart Energy Grids’ main features:
– Cost Efficient
– Resilient (with Self-Healing capability)
– Two-way Communication & Control (Electricity and Information)
– Secure (Physical & Cyber)
– Interoperable with IT/ICT networks
Tools and functions needed for Optimal Operation of Smart Grids
– Controllable Loads
– Distributed Energy Resources (DER)
– Energy Storage Systems
– Smart Relays, Circuit Breakers, Switches, …
Data Mining/Analytics and Machine Learning for:
– Network’s Situation Awareness & Topology Estimation
– Load Forecast
– DER Forecast (i.e. PV and Wind generators’ output forecasts)
DER & Demand Response (DR) Assets; Voltage Regulators & Switched Cap Banks; Breakers, Switches and Fuses for Economic Dispatch, Network Loss Minimization, Peak-shaving, Load Transfer, Power Factor improvement and Volt-Var Optimization (VVO).
IoT, Machine Learning, DERMS and Blockchain for Energy Intelligence
IoT could be utilized for measurement, data storage, communication and device control.
Machine Learning could be utilized for Predictive Analytics and Data Mining.
DERMS could be utilized for optimal scheduling of DER, DR (Demand Response) and DA (Distribution Automation) assets in the network to satisfy DSO’s operational objectives.
Blockchain-based Transactive Energy could be utilized for efficient and fair trading of Energy & Ancillary Services among DSO, Prosumers and Consumers of Electric Energy.
The I-EMS DERMS App features:
– Load/PV/Wind Predictor Module
– Network Contingency Detection Module
– Overloaded Assets Indicator (for Contingency conditions)
– Optimal Power Flow (OPF) Solver Module
– GUI Module (for DSO to see the OPF outcomes for normal and contingency network conditions up to 24 hours ahead)
– Optimal DER and DR schedules for the next 24 hours of network operation based on the OPF objective function.
The I-EMS Transactive Energy Market (TEM) App: – A private Blockchain SaaS
– DSO as the TE Market Operator
– DER and DR asset owners as TE Market Participants
– DSO offers to buy Energy, Reserve or Reliability services from respective DER and DR assets
– DSO’s offer/counter-offer signal includes: [DER/DR ID, kWh, $/kWh, Date, Start hour, Stop hour]
– DER/DR’s bid/counter-bid signal includes: [DER/DR ID, kWh, $/kWh, Date, Start hour, Stop hour]
– DSO’s [kWh, $/kWh] offers are based on DERMS OPF outputs
– DER/DR’s [kWh, $/kWh] bids are based on availability and marginal cost of generation (or marginal loss of energy conservation)
– Smart Contract rules are set by DSO based on its needs for cost-effective network operations and planning.
I-EMS’ BC2E App unique features:– Smart contract logical structure for efficient and fair trading of energy and ancillary services among prosumers, consumers and the DSO.
– Optimal bidding/offering strategies by software agents for the consumer/prosumer members of the BC2E App (based on demand/supply function optimization and learning the monetary value of DER/DR assets to the DSO during normal and contingency network conditions).
– Market based control of energy prices in the bulk generation/transmission system via DER/DR optimal dispatching for energy (or ancillary services) in distribution power network.
Proposed Transactive Energy & Reserve Market Model