Generator scheduling and longer-term planning
Powerop is unit commitment and economic dispatch software developed by Power Optimisation Limited. It combines detailed, accurate modelling of generating plant, battery energy storage systems (BESS) and pumped storage with co-optimisation of energy and reserves.
Powerop has a proprietary multi-phase optimisation method that can reduce typical run times to produce high quality schedules by very significant amounts.
For power system operators, Powerop minimises the overall costs of meeting time-varying forecast demands and reserve requirements by co-optimising unit commitment, economic dispatch and reserve provisions, taking into account the operating constraints on the plant, transmission constraints and the prices quoted by generating companies for their power or the fuel costs and efficiencies of the generating plant.
For generating and energy storage companies operating in a power market, Powerop maximises the profits from their generation and storage portfolios, taking into account market prices for power and reserve, fuel costs and the operating constraints on their plant, and the forecast demands for power from their own customers.
Applications
Powerop can assist with decision making, cost minimisation and profit maximisation for a wide variety of energy market participants including power system operators, generating companies and the owners of BESS and pumped storage.
01 / Power system operators
Optimise unit commitment and economic dispatch together, perform Economic Dispatch with fixed on/off decisions, or identify and optimise any additional commitment of generating plant that is needed for reliability.
System-operator applications →02 / Generating companies
Optimise generation and storage against market prices, electricity contracts and fuel restrictions in markets that permit self-scheduling.
Generator applications →03 / Owners of BESS and pumped storage
Optimise reserve and response commitments of battery energy storage systems (BESS) alongside charging and discharging, allowing for stored-energy and recovery requirements.
Battery storage applications →For longer-term studies, Powerop's Planner option links generator scheduling with fuel, emissions and other resource constraints.
For power system operators
Unit commitment decides which generating units to start up and shut down, and when. Economic dispatch decides the output of each running unit in each scheduling interval. Powerop solves both together in a single optimisation, which improves the quality of the resulting schedules.
By fixing the on/off decisions of the generating units in the input data, Powerop can optimise their power outputs and reserve provision for that particular fixed commitment schedule. The detailed plant, ramping, energy and reserve constraints are imposed when Powerop is run in this mode.
Where generators submit their own schedules to the power system operator, Powerop can identify which additional generating units should be started in advance to minimise costs whenever there is a significant risk that forecast demand and reserve requirements may not otherwise be reliably met.
Start-up notification times can be specified in Powerop's input data for the individual warmth states of the generating units, separately from their subsequent run-up rates. Previously instructed starts can also be represented, so that the commitment schedule takes account of the preparation time needed before synchronisation of the generating units.
These applications use the same detailed modelling of plant behaviour, inter-temporal restrictions and system requirements. Powerop also has features relevant to weakly interconnected and isolated power systems, such as loss-of-infeed reserve requirements and minimum synchronous inertia constraints.
Powerop allows separate reserve requirements for the whole system and for individual transmission zones, including overlapping zones. These requirements can be co-optimised across multiple reserve categories alongside commitment and dispatch.
For each generating unit and reserve category, a piecewise-linear profile can represent how reserve capability varies with power output. This gives system operators the flexibility to model detailed unit characteristics and assess how dispatch decisions affect the reserve available to meet both system-wide and local requirements.
The modelling also distinguishes a genuine capacity derating from an operational restriction on scheduled output that preserves reserve capability. Upward reserve profiles are adjusted when available capacity is reduced.
Powerop's predecessor software was used operationally for unit commitment and dispatch in Northern Ireland for over a decade before the introduction of the all-island Single Electricity Market. Powerop subsequently evolved to support self-scheduling by major generating companies in the British market, as well as production cost modelling and planning studies.
For electricity generating companies
Maximise profits or minimise costs in markets where generators can self-schedule.
Powerop can optimise when units start and stop, their output levels, storage operation and the acceptance and volumes of electricity contracts. The objective can be to maximise profit or minimise scheduling costs, taking account of specified generation costs, fuel and electricity contracts, and relevant penalties.
Generation can be co-optimised with multiple fuel-supply contracts, including take-or-pay terms, daily and hourly limits, transportation costs and the resale of unused gas where permitted.
Its detailed constraints capture the effects of decisions in one period on what can be achieved later, including start-up costs, minimum run times, ramp rates and limited fuel or stored energy. Running-hour restrictions and user-specified ramping costs can also be included.
Powerop can help establish the expected profitability of a power station under forecast market conditions, for example before purchasing it or agreeing a contract for all or part of its capacity.
It can also optimise power contracts alone, without any physical plant, so that a trading organisation can identify the most profitable combination of the available buy and sell contracts. Contracts-only problems are simpler to formulate and usually solve quickly, even with large numbers of contracts.
Powerop has some special options for use by generating companies that are self-scheduling under the British Electricity Trading and Transmission Arrangements (BETTA) in the British electricity market.
Companies using Powerop under BETTA schedule their generating units against half-hourly 'Net Contract Positions' in MegaWatt Hours (MWh). Powerop can model general market prices for electricity, and can also be used to model individual 'buy' and 'sell' contracts for electricity with their particular characteristics and prices (see the section on electricity contracts below). This provides guidance to the electricity company as to which contracts to accept and at what volumes, in order to maximise profits, whilst taking into account the knock-on effects of accepting those contracts on the outputs of the physical generating units, including the effects of ramp rates.
Powerop has an option to calculate the minute-by-minute output profiles for each generating unit for the 'physical notifications' that are required under the BETTA rules. These output profiles satisfy the constraints on the generating units, whilst minimising imbalances between the total integrated output profiles and the Net Contract Positions. The Powerop study period can be up to several days long, with half-hourly time intervals. Longer-term studies are possible using Powerop's Planner option.
For BESS owners and operators of power systems with BESS
Powerop optimises BESS charging and discharging alongside reserve and frequency-response commitments, accounting for power limits, losses, stored energy and service-delivery requirements.
There are special options in Powerop for use by BESS owners in Britain who would like to maximise profits from BESS, taking into account the particular requirements of the British electricity market. These are described in a brochure that can be viewed below.
Longer-term planning
Powerop's Planner option automates linked short-term scheduling runs over longer study periods, such as a year.
Planner allocates limited resources, including fuel supplies, emissions allowances, running hours and permitted start-ups, across the study period and passes those allocations to the short-term runs. It takes account of specified maintenance outages and can model random generating-unit breakdowns probabilistically.
Overlaps between successive cases preserve scheduling continuity and help avoid artificial shut-downs and restarts at case boundaries. The results are collated automatically, so longer-term studies retain Powerop's detailed representation of short-term commitment and dispatch.
Explore the planning and resource constraints →Why Powerop
Powerop uses a proprietary multi-phase version of the Mixed Integer Linear Programming (MILP) method, developed by Power Optimisation. It finds high-quality feasible schedules significantly faster than a conventional single-phase MILP formulation, so that large problems, with many generating units and complex operating constraints, can be solved within practical run times for operational use. The method is designed to scale efficiently as the number of generating units and constraints increases. Because no prior assumptions are made about the nature of the solution, it is robust to changes in operating conditions and relative fuel costs.
Powerop models thermal generating plant, pumped storage and BESS in detail within an integrated commitment, dispatch and reserve optimisation. This can include warmth-dependent start-up costs and run-up profiles, ramp rates that vary by power-output range, usable generation below MSG during start-up, CCGT configurations, pumping/generating restrictions, and BESS service and energy-recovery requirements.
Schedules optimised in this way can reduce fuel, start-up and reserve costs, or increase portfolio profit, compared with manual scheduling or simple merit-order methods. The size of the benefit depends on the system, its constraints and the data supplied.
Detailed reserve characteristics for individual units can be combined with multiple system-wide and zonal reserve requirements.
A standard MILP option is also available for comparison. Adjustable solution effort, parallel processing and optional moving-horizon processing provide further ways to balance run time and solution quality, depending on the study. The software can be adapted as requirements change.
Powerop's schedules satisfy all the defined constraints, provided the data are self-consistent. If they are not, and no feasible solution exists, lower-priority constraints are relaxed automatically according to user-specified priorities and penalties, so that a usable schedule is still produced, with any violations shown in the results. This is particularly important for operational use, where imperfect forecasts or data inconsistencies can occasionally make the problem infeasible.
Powerop has been developed by an expert team of consultants with a wealth of experience in the electricity generation industry.
Deployment and integration
Powerop runs on Windows. Its Excel workbook interface provides a convenient way to configure studies and review results, and is recommended for an initial evaluation.
The optimisation engine can alternatively communicate with customer-developed software through simple text files, allowing it to be integrated into an existing scheduling or optimisation workflow.
Detailed cost breakdowns, constraint margins and violation penalties help explain the calculated schedule. Results workbooks retain the input data and report validation messages, warnings and errors for review.
Discuss integration with your systems →Technical capabilities
Powerop can minimise scheduling costs or maximise profit from generation and electricity contracts, taking account of the specified fuel, start-up and shut-down costs, generation-dependent costs, contract terms and penalties. The user can select a scheduling-interval duration of 5, 10, 15, 30, 60, 120 or 240 minutes for each study. A one-minute option is also available for small investigative studies. Longer-term studies can use Powerop's Planner option to link shorter operational studies and allocate limited resources across the full study period.
Expand the topics relevant to your system or portfolio. Model settings and constraint priorities determine which requirements apply in a particular study.
Powerop can be used for Economic Dispatch by fixing the on/off decisions of the generating units in the input data. It then optimises power outputs and reserve provision for that commitment schedule, using the applicable plant and system constraints, including ramp rates, energy limits and system-wide or zonal reserve requirements.
This allows the same detailed plant and reserve models to be used for either integrated unit commitment and dispatch, or dispatch with a specified commitment schedule.
Powerop can model the operation of thermal, hydro-electric and renewable generating units and electricity contracts with other companies. Thermal generating units can include coal-fired, oil-fired, gas-fired and nuclear-powered steam turbines, and combustion turbines burning distillate (which are often called gas turbines). Thermal units can also include dual-fired generating units, which can use one of two alternative fuel types. Powerop can model and optimise the use of mixtures of different fuels and/or gas contracts in the same generating unit or group of units. The hydro-electric units can include conventional hydro units and Pumped Storage units. Gas-fired units and hydro-electric units are treated as energy-limited plant. Energy storage units, such as Battery Energy Storage Systems (BESS) and pumped storage, can be modelled and their operation optimised. Upper or lower energy limits may also be applied to other types of generating units and may be used, for example, to represent limited fuel supplies or 'take or pay contracts'. Renewable generation, such as wind farms and solar power, can be modelled as pseudo-generating units with zero fuel costs and time-varying availabilities, which might represent the forecast total wind power or solar power in a particular region.
An electricity contract with another company can be modelled in Powerop as a pseudo-generating unit or as a 'demand' unit. This option offers all the features described above, for example ramp rates, energy limits, and minimum on and off times, which can be useful if the electricity contract contains such features.
Powerop also has an option for the direct modelling of the electricity contracts which are offered on power exchanges or by electricity brokers. Electricity contracts (also known as power contracts) may be of type 'buy' or 'sell'. Electricity contracts may optionally be grouped, so that if one contract in a group is accepted then all the other contracts in that group must be accepted. This direct modelling of electricity contracts allows Powerop to consider a much larger number of such contracts than if they were modelled as pseudo-generating units. This provides guidance to the electricity company as to which contracts to accept and at what volumes, in order to maximise profits, whilst taking into account the knock-on effects of accepting those contracts on the outputs of the physical generating units, including the effects of ramp rates.
Powerop is able to use pseudo-generating units to model different modes of operation of generating plant, with logical constraints defined by the user preventing simultaneous operation of any incompatible modes. For example, the user might define different pseudo-generating units in Powerop's input data for the following modes of operation of a Combined Cycle Gas Turbine (CCGT) power station that has two gas turbines and one steam turbine: Mode A is Gas Turbine 1 operating in 'open-cycle mode', Mode B is Gas Turbine 2 operating in 'open-cycle mode', Mode C is Gas Turbine 1 operating in 'combined-cycle mode' with the Steam Turbine, Mode D is Gas Turbine 2 operating in 'combined-cycle mode' with the Steam Turbine, and Mode E is Gas Turbines 1 and 2 operating together in 'combined-cycle mode' with the Steam Turbine. The thermal efficiencies, ramp rates and other data items of these modes will not all be the same. This can be modelled by Powerop using pseudo-generating units and appropriate logical constraints specified by the user.
Logical constraints can also specify minimum or maximum numbers of operating units in a group, dependencies between units, and minimum scheduled synchronous inertia. Constraints can distinguish units producing any non-zero output from those at or above MSG.
Enhanced logical constraints can link operating decisions in consecutive scheduling intervals to restrict transitions between configurations, for example requiring an appropriate preceding operating mode before another mode can run.
When performing a planning study over a period of, say, one year, some considerations apply over all or most of the year, rather than at one particular time. Such issues include:
Running-hour limits can be applied to individual units or specified groups over defined periods, alongside emissions, energy and start-up restrictions. Planner allocates relevant longer-term resources across its linked short-term studies.
Powerop can account for the notice needed between issuing a start-up instruction and synchronising a generating unit. Notification times can be specified by warmth state, separately from the subsequent run-up to MSG.
The schedule posting time and any previously instructed starts can be represented, so that a schedule takes account of which starts remain achievable. This option is particularly relevant to operational commitment and RUC.
Fuel procurement and use can be co-optimised with generation. Multiple buy, sell and buy-only contracts can supply one or more generating units, with restrictions on which contracts can supply which units.
The same contract formulation can represent other fuels with similar supply restrictions.
Powerop distinguishes an actual reduction in available capacity from an operational restriction on scheduled output. A capacity derating affects both generation and upward reserve capability; an operational reduction can hold a unit below its available output while preserving its reserve capability.
Where a unit uses a piecewise-linear upward reserve profile, Powerop adjusts that profile when availability is reduced, following the profile rules described in the User Guide, which is available on request.
The Run Time Multiplier adjusts the solution effort to suit the required balance between run time and solution quality. The number of parallel threads used can also be selected.
An optional moving-horizon algorithm can be useful for some studies that are too large for an effective direct solution. It retains the problem data while progressively advancing the range over which decisions are made. Benefits depend on the data set; more threads or moving-horizon processing do not invariably shorten elapsed run time.
For longer planning studies, Planner solves overlapping shorter cases and allocates relevant resources across the full study period.
Results workbooks include detailed generation, reserve, storage, fuel and contract results, together with cost breakdowns. Transmission-group and logical-constraint results show their limits, calculated values, margins and any violation penalties.
Data-validation messages, warnings and errors are reported separately. This helps users assess a schedule and investigate conflicting data or requirements. Input data are retained with the study results.
If a requirement of your system isn't covered here, please ask, as it may already be available or be straightforward to add.
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