Power Distribution Optimization Based on Demand Respond with Improved Multi-Objective Algorithm in Power System Planning

In this article, a novel dynamic economic load dispatch with emission based on a multi-objective model (MODEED) considering demand side management (DSM) is presented. Moreover, the investigation and evaluation of impacts of DSM for the next day are considered. In other words, the aim of economical load dispatch is the suitable and optimized planning for all power units considering different linear and non-linear constrains for power system and generators. In this model, different constrains such as losses of transformation network, impacts of valve-point, ramp-up and ramp-down, the balance of production and demand, the prohibited areas, and the limitations of production are considered as an optimization problem. The proposed model is solved by a novel modified multi-objective artificial bee colony algorithm (MOABC). In order to analyze the effects of DSM on the supply side, the proposed MODEED is evaluated on different scenarios with or without DSM. Indeed, the proposed MOABC algorithm tries to find an optimal solution for the existence function by assistance of crowding distance and Pareto theory. Crowding distance is a suitable criterion to estimate Pareto solutions. The proposed model is carried out on a six-unit test system, and the obtained numerical analyses are compared with the obtained results of other optimization methods. The obtained results of simulations that have been provided in the last section demonstrate the higher efficiency of the proposed optimization algorithm based on Pareto criterion. The main benefits of this algorithm are its fast convergence and searching based on circle movement. In addition, it is obvious from the obtained results that the proposed MODEED with DSM can present benefits for all consumers and generation companies.

What’s in, what’s out? Towards a rigorous definition of the boundaries of benefit-cost analysis

Benefit-cost analysis (BCA) is typically defined as an implementation of the potential Pareto criterion, which requires inclusion of any impact for which individuals have willingness to pay (WTP). This definition is incompatible with the exclusion of impacts such as rights and distributional concerns, for which individuals do have WTP. I propose a new definition: BCA should include only impacts for which consumer sovereignty should govern. This is because WTP implicitly preserves consumer sovereignty, and is thus only appropriate for ‘sovereignty-warranting’ impacts. I compare the high cost of including non-sovereignty-warranting impacts to the relatively low cost of excluding sovereignty-warranting impacts.

Two-Population Coevolutionary Algorithm with Dynamic Learning Strategy for Many-Objective Optimization

Due to the complexity of many-objective optimization problems, the existing many-objective optimization algorithms cannot solve all the problems well, especially those with complex Pareto front. In order to solve the shortcomings of existing algorithms, this paper proposes a coevolutionary algorithm based on dynamic learning strategy. Evolution is realized mainly through the use of Pareto criterion and non-Pareto criterion, respectively, for two populations, and information exchange between two populations is used to better explore the whole objective space. The dynamic learning strategy acts on the non-Pareto evolutionary to improve the convergence and diversity. Besides, a dynamic convergence factor is proposed, which can be changed according to the evolutionary state of the two populations. Through these effective heuristic strategies, the proposed algorithm can maintain the convergence and diversity of the final solution set. The proposed algorithm is compared with five state-of-the-art algorithms and two weight-sum based algorithms on a many-objective test suite, and the results are measured by inverted generational distance and hypervolume performance indicators. The experimental results show that, compared with the other five state-of-the-art algorithms, the proposed algorithm achieved the optimal performance in 47 of the 90 cases evaluated by the two indicators. When the proposed algorithm is compared with the weight-sum based algorithms, 83 out of 90 examples achieve the optimal performance.

Application of V. Pareto’s economic efficiency criterion in Russian judicial practice

The purpose of the research is to justify the productivity of the application of one of the two most common criteria of economic efficiency (V. Pareto principle) in Russian judicial practice. Justification is carried out by identifying the content of the Pareto criterion, assessing examples of its application by Russian courts and determining the conditions and limitations of such application. The methodological basis of work was the formal-legal method, which allowed to analyze the texts of judicial decisions on the use by the court of normative economic analysis of law; the comparative method, which was used to compare the theoretical foundations and practical features of the criterion of economic efficiency by the Russian judiciary. The results of the research were the author’s conclusions about the applicability of the Pareto criterion in the Russian reality and the formulation of the most likely areas of its use by the courts. Law as an object of scientific knowledge cannot be studied in isolation from its social, cultural, political and economic assumptions, as it is a central tool by which the state affects the economic well-being of society. To improve the practice of using this tool, it seems necessary to evaluate it from the standpoint of economic efficiency. In this regard, the further vector of evolution of Russian law will be more and more active use of methodological developments of economic theory, the application of the economic analysis of law developed in the United States in law enforcement practice. This leads to the need for interdisciplinary research on the conceptual and practical problems of using this direction in Russia. The novelty of the research lies in a comprehensive approach, to the problem of applicability of normative economic analysis of law in the judicial practice of the Russian Federation.

Non-selfish behaviour: Are social preferences or social norms revealed in distribution decisions?

People frequently behave non-selfishly in situations where they can reduce their own payoff to help others. It is typically assumed that such pro-social behaviour arises because people are motivated by a social preference. An alternative explanation is that they follow a social norm. We test with two survey experiments (N=2,408) which of these two explanations can better explain decisions people make in a simple distribution game under three different elicitation mechanisms. Unlike previous studies, we elicit preferences and perceived social norms directly for each subject. We find that i) norm-following better explains people’s distributive choices compared to social preferences and ii) lack of confidence in one’s social preference –itself explained by weaker social identification— predicts norm-following. Our findings imply that the Pareto criterion has weaker (than previously thought) foundations for welfare evaluations, but this effect may be attenuated in societies with stronger social identification. Perhaps unexpectedly, but unsurprisingly given i) above, we find that different mechanisms for eliciting social preferences have no effect on distribution decisions.

On a Theorem due to Alan D. Taylor about Aggregation of Preferences

In this paper, we show that there does not exist any triple acyclic preference aggregation rule that satisfies Majority property, weak Pareto criterion and a version of a property due to Alan Taylor. We also show that there are non-dictatorial preference aggregation rules and in particular non-dictatorial social welfare functions which satisfy the weak Pareto criterion and Taylor’s Independence of Irrelevant Alternatives. Further, we are able to obtain analogous results for preference aggregation functionals by suitably adjusting the desired properties to fit into a framework which uses individual utility functions rather than individual preference orderings. Our final result is a modest generalisation of Sen’s version of Arrow’s impossibility theorem which is shown to hold under our mild domain restriction. JEL: D71