MOHRES evaluates a hybrid renewable energy system against a wide range of traditional and new performance measures related to (i) cost/profit, (ii) reliability, and (iii) environmental impact:
The new reliability measures ‘Blackout Duration’ and ‘Mean Time Between Failures’ provide the end-user/customer a tangible means for understanding the reliability of the system.
|Traditional vs New Reliability Measures|| Traditional reliability measures
Not tangible to the end-user/customer
| New reliability measures|
Understandable by the end-user/customer
|Example:||The system has a total yearly unmet load of 480 kWh
(End-user/customer: What does it exactly mean? How good/bad is this?)
|System with total yearly downtime duration of 650 hours, average downtime duration of 2 hours, no downtime duration lasts more than 4 hours, and the average frequency of downtimes is 3 days.|
MOHRES, besides traditional deterministic analysis, conducts nondeterministic analysis to predict the performance of a HRES accurately.
LCE = 112.5 c/kWh @ Level of Confidence 90%
|Deterministic vs Nondeterministic Analysis||Deterministic||Nondeterministic|
|Example:|| Return of investment in 4 to 6 years
(Inaccurate & misleading losing trust of customer)
| Return of investment in 5 years and 10 months @ a level of confidence of 90% |
(Accurate, understandable by the end-user/customer)
MOHRES, where applicable, finds the best planned load for industrial applications with flexible loading.
Flexible Plannable Load for Industrial Applications
MOHRES employs a variety of single and multiobjective, heuristic and metaheuristic optimisation techniques, specially developed for HRES design space.
Pareto Front Multiobjective Optimisation
MOHRES conducts integrated configuration and size optimisation. Some possible HRES configurations with wind turbine, PV panel, battery bank, diesel generator and fuel cell/electrolyser:
|Traditional Approach||Integrated configuration and size optimisation (MOHRES)|
|Find the optimum component size for each possible configuration and then compare all optimum solutions against each other to find the best configuration. This can lead to solving 20 optimisation problems for a generic wind turbine, PV panel, battery bank, diesel generator and fuel cell/electrolyser system.||Integrate the configuration optimisation and size optimisation together and conduct only one optimisation problem to find the best configuration and the best size of components for that configuration.|
MOHRES employs a flexible problem formulation which allows conducting retrofitting of existing systems and defining energy transition scenarios.
MOHRES brings system operation & control into size optimisation by the inclusion of Dispatch Strategy at the design stage. This allows finding superior solutions compared to those obtained using traditional optimisation formulation:
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