Energy
Energy policy, Efficiency measurement

Multi-aspect efficiency measurement of multi-objective energy
planning model dealing with uncertainties
Department of Information and Physical Sciences, Graduate School of Information Science and Technology
Professor Hiroshi Morita

https://researchmap.jp/read0042934

Postdoctoral Researcher Sudlop Ratanakuakangwan

https://researchmap.jp/ratanakuakangwan_sud

Abstract
This study proposes a framework that combines the concepts ofa multi-objective optimization model and efficiency measurement
to determine the most efficient energy mix considering the multi-dimensional aspects of energy requirements and various uncertainty
scenarios. Various multi-objective functions are appended to theproposed optimization model to meet requirements related to energy need, cost, environmental impact, security, social impact, andsocial benefit. A slacks-based measure methodology is applied todetermine the best energy mix from the alternatives produced by
the appended model. The energy efficiency of each energy mix
is measured from the linear combination of its defined inputs andoutputs. The outputs to be maximized include total generated electricity, direct employment, and percentage of generated electricity
from renewable energy, while the inputs to be minimized consist of
total economic cost, carbon dioxide emission, total social cost, andpower-plant-type dependence score.

Energy▍ Background & Results
To demonstrate the applicability of the proposed model, a casestudy of Thailand’s power development plan is featured. Various
types of power plants, both fossil fuel-fired and renewable energy-driven are considered in the empirical analysis. The model
results showed the range of optimal energy mixes corresponding
to the different energy policies and scenarios of uncertainty. The
inability to determine in the first-stage efficiency measurement thebest energy mix from the marginal differences of efficiency scores
between the various energy mixes means that a second-stage
group-separated efficiency measurement would be necessary. The
subsequent group-separated efficiency measurement grouped bydemand scenario showed that the lexicographical ordering that prioritized environment first, followed by social damage and then cost(designated as ESC), had the highest weighted-average efficiency
score for all demand scenarios. The results show that the proposed

method can contribute significant improvements, including a reduction in total emissions and in the power-plant-type dependence
score (by 31.41% and 25.59%, respectively). It also increases
total employment and the proportion of generated electricity fromrenewable energy plants (by 25.73% and 47.39%, respectively),with marginal tradeoffs of total costs and total social costs (which
increase by 8.94% and 13.89%, respectively).

▍ Significance of the research and Future perspective
The study established that to effectively implement the proposedmodel, the various choices of the multi-objective function are to
be generated first, allowing the two-stage efficiency measurement
method to then determine the best of the optimal energy mixes
from all the possible first-stage results. Quantitative results from themodel could help policy makers efficiently determine an appropriate energy policy—one that maximizes the satisfaction of multiple
requirements, under a given set of constraints and scenarios ofuncertainty.

Figure 1. Optimal energy mixes of the seven energy policies under the scenariosof uncertainty.

Figure 2. Efficiency score variation separated by demand scenario.

P a t e n t
Tr e a t i s e

Ratanakuakangwan, S; Morita, H. Multi-aspect efficiency measurement of multi-objective energy planning model dealing with uncertainties.
Applied Energy 2022, 313:118883. doi: 10.1016/j.apenergy.2022.118883

URL
K e y w o r d multi-objective optimization, efficiency measurement, energy planning, optimal energy mix; slacks-based measure