Optimising power and wheeling allocations, and reducing cost

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The Trade Optimiser efficiently allocates power from Independent Power Producers (IPPs) to consumers by optimising end-of-month or end-of-balancing period wheeling allocations.

It considers customer requirements, tariffs, and dynamic load profiles, aiming to minimise inefficiencies and maximise objectives, such as reducing cost or maximising profit. The optimiser utilises a linear optimisation algorithm to generate schedules detailing percentage allocations for each customer, which are integrated into the ETS Scheduler for physical settlement.

The Trade Optimiser, a powerful suite of software tools and algorithms, is customised and configured for a client to assist trading/wheeling participants (traders) to efficiently allocate power between power producers (e.g. IPPs) and power consumers.

Its goal is to optimise end-of-month or end-of-balancing period wheeling allocations, aiming to maximise an objective function while minimising inefficiencies such as oversupply. The optimiser considers various complexities, including customer requirements, diverse customer tariffs, and dynamic load profiles of generators and customers.

ABOUT

The optimiser produces schedules that specify the percentage allocations from each supplier and the percentage allocations to each customer. By doing so, it optimises the distribution of energy from suppliers to different consumers, considering a range of contract conditions, rates, and constraints. The optimisation process aims to achieve different objectives, such as minimising expenditure, maximising profit, or maximising customer savings.

Multi-dimensional visualisations, including Pareto front visualisations, assist in decision-making when there are competing objectives and trade-offs to consider.

The Optimal Wheeling Allocator (OWA) optimisation process takes place after all metering data has been collected. Individual customer pricing and constraints, as defined by their respective contracts, are inputted into the optimiser. Additionally, data on the Wholesale Electricity Pricing System (WEPS), other tariffs, and rebate information are also included in the optimisation process.

The optimiser accommodates the variations in wheeling frameworks implemented by different municipalities. It employs a linear optimisation algorithm to maximise various objective functions, such as cost reduction and rebate maximisation.

The output of the optimiser consists of schedules that specify the percentage allocations for each customer. These schedules are then integrated into the ETS Scheduler, allowing them to be incorporated into the physical settlement process.

DETAILS

Features

Efficient Power Allocation
Advanced algorithms and optimisation techniques for efficient power allocation from IPPs to consumers.
End-of-month/End-of-balancing Period Optimisation
Optimisation specifically tailored for end-of-month or end-of-balancing periods to minimise oversupply and undersupply, and to maximise delivery efficiency.
Customer Requirement Management
Captures and manages customer-specific load profiles, diverse tariffs, pricing constraints, and individual contract details.
Objective Function Optimisation
Ability to optimise various objective functions such as cost reduction, profit maximisation, or customer savings.
Multi-dimensional Visualisations
Intuitive visualisations, including Pareto front visualisations, for informed decision-making with multiple competing objectives.
Metering Data Integration
Seamlessly integrates with metering data sources for accurate input in the optimisation process.
Wholesale Electricity Pricing System Integration
Integrates with Wholesale Electricity Pricing System (WEPS) and other tariff data sources for incorporating wholesale pricing information.
Wheeling Framework Flexibility
Adapts to accommodate variations in wheeling frameworks implemented by different municipalities.
Linear Optimisation Algorithm
Uses advanced and efficient linear optimisation algorithms to maximise objective functions such as cost reduction and rebate maximisation.
Schedule Generation and Integration
Generates schedules specifying percentage allocations and seamless integration with the ETS Scheduler for accurate energy distribution and physical settlement.
FEATURES

Benefits

  • Cost reduction and improved profitability through efficient power allocation and elimination of oversupply.
  • Maximisation of objectives (e.g. expenditure reduction, profit increase, customer savings) by optimising energy distribution based on contract conditions, rates, and constraints.
  • Enhanced decision-making with multi-dimensional visualisations, facilitating trade-off navigation and improved allocation processes.
  • Streamlined physical settlement process and accurate energy distribution by seamlessly integrating optimiser schedules with the ETS Scheduler.
BENEFITS

Examples of Output

  • Percentage Savings per Customer

    The Trade Optimiser allocates power according to different objective functions.

  • Pre-wheeling vs. Post-wheeling Cost

    Comparison between pre-wheeling cost per KWh and post-wheeling after optimisation.

Find out how Enerweb can help you optimise
power and wheeling allocations, and improve profitability.

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