Proposed Cost Allocation Research Articles

Cooperative-game-based joint planning and cost allocation for multiple park-level integrated energy systems with shared energy storage

Under the carbon-neutrality goal, joint planning along with a fair cost allocation of shared energy storage becomes a promising solution to boosting the economic benefits and energy utilization efficiency of multiple park-level integrated energy systems. Hence, a joint planning and cost allocation method for multiple park-level integrated energy systems with shared energy storage is proposed in this paper to obtain optimal joint planning and cost allocation strategies of park-level integrated energy systems with shared energy storage. First, a joint planning model for park-level integrated energy systems with shared energy storage is established to minimize the total investment and operation costs of the grand cooperative coalition by considering the optimal construction time sequence of devices. Then, an ex-post cost allocation algorithm based on an improved Nucleolus method is proposed to realize a fair cost allocation for the joint planning of park-level integrated energy systems with shared energy storage. Finally, case studies on a grand cooperative coalition with six park-level integrated energy systems are performed for verifying the effectiveness of the proposed method. Simulation results demonstrate that the total investment and operation costs of park-level integrated energy systems are reduced, and the renewable energy consumption levels of park-level integrated energy systems are improved. Besides, the proposed cost allocation algorithm has less computing time, and better coalition rationality and stability compared to other similar algorithms.

Efficient effort equilibrium in cooperation with pairwise cost reduction

There are multiple situations in which bilateral interaction between agents results in considerable cost reductions. The cost reduction that an agent obtains depends on the effort made by other agents. We model this situation as a bi-form game with two states. In the first stage, agents decide how much effort to exert. We model this first stage as a non-cooperative game, in which these efforts will reduce the cost of their partners in the second stage. This second stage is modeled as a cooperative game in which agents reduce each other’s costs as a result of cooperation, so that the total reduction in the cost of each agent in a coalition is the sum of the reductions generated by the rest of the members of that coalition. The proposed cost allocation for the cooperative game in the second stage determines the payoff function of the non-cooperative game in the first stage. Based on this model, we explore the costs, benefits, and challenges associated with setting up a pairwise effort situation. We identify a family of cost allocations with weighted pairwise reductions which are always feasible in the cooperative game and contain the Shapley value. We also identify the cost allocation with weighted pairwise reductions that generate an efficient equilibrium effort level.

Determination and Cost Allocation for Regulation Reserve With Renewables: A Data-Driven Assisted Approach

Proper setting of regulation reserve (RR) requirements is essential for the secure and economic operation of power grids. Currently, the RR requirement is normally determined based on ad-hoc experience or numerical methods that cannot comprehensively consider uncertainties and fluctuation characters. Regarding the increasing penetration of renewables, it becomes an obvious challenge for determining the proper RR requirement and reasonably allocating the RR costs to market participants. To address these issues, a data-driven assisted determination and cost allocation method for RR is proposed. A data-driven method considering fluctuation features is used to predict the RR requirement. To avoid the insufficiency of the RR resulting from prediction error, a compensation strategy based on error decomposition is proposed. Ensemble learning is used to handle the model error. The data error caused by the multiperiod forecast uncertainty of load and renewables is compensated by a computationally tractable chance-constrained optimization problem. To encourage grid-friendly behaviors, a hierarchical method for RR cost allocation is proposed to account for the comprehensive contributions of market participants. Case studies show that compared with existing methods, the proposed RR requirement determination method can achieve a more than 24% improvement in frequency performance without excessive costs. The reasonability of the proposed cost allocation method is also illustrated.

Nucleolus based cost allocation methods for a class of constrained lane covering games

In truckload transportation procurement networks, shippers purchasing the services of truckload carriers seek to form multi-company tours which consist of regularly scheduled shipments with minimal empty truck movements with the aim of getting better rates from the carriers in return. Identifying the minimum cost collaborative solution and sharing the costs in a fair manner are two interrelated and critical tasks for the success of such networks. The restrictions on the tours which can be formed make both of these tasks very challenging. In this paper, we take a cooperative game theory approach and study the resulting constrained lane covering game. We first show the set of conditions which must be satisfied for the game to have a non-empty core. We propose nucleolus based cost allocation methods. We also develop column and row generation methods for solving these mathematical models. We compare our proposed cost allocation models with alternative cost allocation methods and each other using a set of core stability metrics through computational experiments on randomly generated instances from the literature.

A game-theoretic multi-stakeholder model for cost allocation in urban consolidation centres

Recently, many European local authorities have set up Urban Consolidation Centres (UCC) for dealing with challenges arising from the environmental and social impacts of logistical activities in urban contexts through shipment synchronisation and carrier coordination policies. However, the number of successful UCC projects led by local authorities in Europe is low, with most of the UCCs failing to achieve financial sustainability after the initial experimental phase, which is often heavily supported by public funds. In order to propose mechanisms that could favour the economic and financial sustainability of UCC systems, this research develops an adaptation of game-theoretic approaches to the problems of responsibility and cost allocation among stakeholders participating in a UCC delivery network. A solution based on the Shapley Value concept is employed to derive cost allocations; applications of the model to a real-world scenario are evaluated. An extensive sensitivity analysis shows that the proposed cost allocation rules can provide alternative arrangements, based on extended responsibility concepts, which can alleviate the burden on local authorities for the set up of UCCs. As such, results provide useful policy and practice implications on how to safeguard UCCs’ viability under different scenarios, including the outsourcing of the last-mile deliveries.

A cost allocation model based on the combination of data envelopment analysis and Shannon entropy (case study: branches of the central post of Isfahan)

The method used for allocation of costs in this study has several stages. In stage 1, various types of data envelopment analysis (DEA) models were used to assess the efficiency of decision-making units (DMUs), including constant return to scale and variable return to scale with a variety of input and output types in radial and non-radial states. In stage 2, Shannon entropy method was used to combine the obtained efficiencies for each decision making unit. In stage 3, the allocation of costs was done based on the combined efficiency number for each unit obtained in phase 2. The proposed cost allocation model was then implemented in an example and its fairness was compared with similar methods using the Gini coefficient method. Finally, the proposed model was investigated in Central Post of Isfahan.

Optimal Resource Procurement and the Price of Causality

In this article, we study the problem of procuring diverse resources in a forward market to cover a set <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf E}$</tex-math></inline-formula> of uncertain demand signals <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf e}$</tex-math></inline-formula> . We consider two scenarios: 1) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf e}$</tex-math></inline-formula> is revealed all at once by an oracle and 2) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\bf e}$</tex-math></inline-formula> reveals itself causally. Each scenario induces an optimal procurement cost. The ratio between these two costs is defined as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">price of causality</i> . It captures the additional cost of not knowing the future values of the uncertain demand signal. We consider two application contexts: Procuring energy reserves from a forward capacity market, and purchasing virtual machine instances from a cloud service. An upper bound on the price of causality is obtained, and the exact price of causality is computed for some special cases. The algorithmic basis for all these computations is set containment linear programming. A mechanism is proposed to allocate the procurement cost to consumers who in aggregate produce the demand signal. We show that the proposed cost allocation is fair, budget-balanced, and respects the cost causation principle. The results are validated through numerical simulations.

Cost Allocation Model for Net-Zero Energy Buildings under Community-Based Reward Penalty Mechanism

Abstract The introduction of financial incentives for net-zero energy building/community (ZEB/ZEC) is a potential strategy that facilitates the development of sustainable buildings. In this study, a reward-penalty mechanism (RPM) is firstly proposed for a community that aims to achieve the target of annual zero energy balance. In order to investigate the cost allocated for each building in the community, a cost allocation model by considering the load of these buildings and the levels of zero energy building achieved is further proposed, based on which four typical types of the model is selected and investigated. The economic performance of a building under the four types of allocation model is then compared for a community that consists of 20 family houses in Ireland. By considering the possible ZEB level ranges in each building, two Cases are conducted (Case 1 – the range is between 0.0 and 1.0; Case 2 – the range is between 0.5 and 1.0). The results show that the 1st model is the simplest one that allocates cost evenly. By contrast, the cost of a building depends on its load in the 2nd model and depends on the ZEB level it achieved in the 3rd model, while it considers the two factors evenly in the 4th model. The proposed cost allocation model is expected to provide a basic guide for the designers of financial incentives as well as experts in the fields of net-zero energy buildings.

Cost Allocation Mechanism Design for Urban Utility Tunnel Construction Based on Cooperative Game and Resource Dependence Theory

The urban utility tunnel presents solutions for the sustainable development of urban underground space, and is an important carrier of power distribution network and integrated energy systems. Considering the high investment cost of utility tunnels and the limitations of traditional cost sharing methods (i.e., spatial proportional method, direct-laying cost method and benefit-based proportional method), it is of great significance to establish a fair and practical cost sharing mechanism. First, an improved Shapley value-based spatial proportional method is proposed. A comprehensive decision-making mechanism for utility tunnel construction cost allocation is established by using the improved spatial proportion, the life-cycle direct-laying cost proportion, and the benefit proportion of pipeline companies as the cost allocation indexes. The resource dependence theory is introduced to quantify the bargaining power of each pipeline company in the negotiation of the cost allocation. The weights of the cost allocation indexes in the comprehensive decision-making model are optimized with the objective of maximizing the overall satisfaction of the pipeline companies. Simulations based on the data of utility tunnel pilots in China illustrate that the proposed cost allocation mechanism has the highest overall satisfaction and is more acceptable and more feasible than the traditional cost allocation methods. For power companies, the cost of laying power cables can be significantly reduced by utility tunnels, and laying 10 kV power cables has been shown to have higher economic benefits.

Cost allocation for rural electrification using game theory: A case of distributed generation in rural India

This paper deals with an economic aspect of distributed generation systems which rural energy cooperatives may mainly support, since they can effectively coordinate the different stakeholders within an energy access initiative. Members of a rural energy cooperative would share the costs of deploying a distributed generation system, so that each of them can benefit from it. To minimise the overall investment cost, such a cooperative must consider both technical sizing and cost allocation among its members. For the latter, an important issue to take into account is the so-called willingness-to-pay. For obtaining the design of the distributed generation system we propose to use facility location covering (FALCO) models. The solution of the FALCO model provides both the structure of the distributed generation system and the investment cost to be covered by the members of the cooperative. We take advantage of the structure of the primal and dual optimal solutions of the FALCO model to endogenously determine the minimum and maximum willingness-to-pay of the cooperative members and then to apply rationing techniques to obtain the final allocation of costs to each member. Thus, our approach optimises the generator locations and minimises the total system cost, while assigning to each member at least her minimum willingness-to-pay. From our point of view, this method may help the beneficiaries to accept the investment cost allocation. Finally, a case study based on real data from a rural village in Maharashtra, where a group of farmers wanting to buy and share an energy system to pump water for irrigating their fields, is used to illustrate the working of the proposed cost allocation methodology.

Circuit-theory-based method for transmission fixed cost allocation based on game-theory rationalized sharing of mutual-terms

This paper proposes a new method to allocate the transmission fixed costs among the network participants in a pool-based electricity market. The allocation process relies on the circuit laws, utilizes the modified impedance matrix and is performed in two individual steps for the generators and loads. To determine the partial branch power flows due to the participants, the equal sharing principle is used and validated by the Shapley and Aumann-Shapley values as two preferred game-theoretic solutions. The proposed approach is also applied to determine the generators’ contributions into the loads, and a new concept, named circuit-theory-based equivalent bilateral exchange (EBE), is introduced. Using the proposed method, fairly stable tariffs are provided for the participants. Cross-subsidies are reduced and a fair competition is made by the proposed method due to the counter-flows being alleviated compared with the well-known Z-bus method. Numerical results are reported and discussed to validate the proposed cost allocation method. Comparative analysis reveals that the method satisfies all conditions desired in a fair and efficient cost allocation method. Finally, the developed technique has been implemented successfully on the 2383-bus Polish power system to emphasize that the method is applicable to very large systems.

Cost Sharing for Capacity Transfer in Cooperating Queueing Systems

We study the problem where independent operators of queueing systems cooperate to generate a win–win solution through capacity transfer among each other. We consider two types of costs: the congestion cost in the queueing system and the capacity transfer cost, and two types of queueing systems: M/ M/1 and M/ M/ s. Service rates are considered to be capacities in M/ M/1 and are assumed to be continuous, while numbers of servers are capacities in M/ M/ s. For the capacity transfer problem in M/ M/1, we formulate it as a convex optimization problem and identify a cost‐sharing scheme which belongs to the core of the corresponding cooperative game. The special case with no transfer cost is also discussed. For the capacity transfer problem in M/ M/ s, we formulate it as a nonlinear integer optimization problem, which we refer to as the server transfer problem. We first develop a marginal analysis algorithm to solve this problem when the unit transfer costs are equal among agents, and then propose a cost‐sharing rule which is shown to be in the core of the corresponding game. For the more general case with unequal unit transfer costs, we first show that the core of the corresponding game is non‐empty. Then, we propose a greedy heuristic to find approximate solutions and design cost allocations rules for the corresponding game. Finally, we conduct numerical studies to evaluate the performance of the proposed greedy heuristic and the proposed cost allocation rules, and examine the value of capacity transfer.

Supply Chain Coordination Under Service Level Constraint and Controllable Lead Time

This paper investigates the coordination issue in a decentralized supply chain having a vendor and a buyer for a defective product. The authors develop two inventory models with controllable lead time under service level constraint. The first one is propose under decentralized mode based on the Stackelberg model, the other one is propose under centralized mode of the integrated supply chain. Ordering cost reduction is also including as a decision variable along with shipping quantity, lead time and number of shipments. Computational findings using the software Matlab 7.0 are provided to find the optimal solution. The results of numerical examples show that centralized mode is better than that of decentralized mode, and to induce both vendor and buyer for coordination, proposed cost allocation model is effective. The authors also numerically investigate the effects of backorder parameter on the optimal solutions. Benefit of ordering cost reduction in both models is also provided.

A More Fair Power Flow Based Transmission Cost Allocation Scheme Considering Maximum Line Loading for N-1 Security

This paper proposes an efficient approach to transmission fixed cost allocation in a pool based electricity market that takes into consideration N-1 secure annual system operation. The optimal capacity of a transmission facility is defined as the maximum power flow the facility may face under a contingency situation for a certain system snapshot. In this pricing approach, for each time interval, the largest optimal capacity of a transmission facility is calculated for all N-1 conditions considering a security constrained optimal power flow. Charges for each facility are based on the facility usage of the largest optimal capacity for all time intervals during one or more years. Network usage is determined by generalized distribution factors and three variations of the MW-Mile method for pricing counter-flows are investigated for the proposed cost allocation method. The three proposed pricing methods are applied to the IEEE 24-bus reliability test system and compared with other pricing methods.

Allocating the cost of empty railcar miles in a dynamic railroad network

In a multi-level railcar system, the formation of coalitions among railcar companies can potentially lead to a reduction in the total empty mile cost, an important part of the variable cost of the railcar system. In order to maintain a sustainable coalition, it is important to ensure that the costs incurred in the coalition will be fairly allocated to participating companies in the coalition. This paper proposes a cost allocation scheme based on game theory that allocates the cost of empty car miles to participating companies in a coalition for a railcar system. The method can ensure fairness and enhance stability of a coalition since it explicitly considers the level of contribution from each company in the coalition. The properties important for fairness in cost allocation and stability for the coalition are discussed. We have also demonstrated in the paper that the proposed cost allocation scheme can be coupled with a generalised optimisation model for empty car distribution in a dynamic railroad network.

Property appraisal in high-rises: A cooperative game theory approach

The construction of the higher stories in a building is utterly contingent upon the construction of the lower ones, while the construction of lower stories does not require the construction of the higher ones. This rationale underlies our adoption of a cooperative game theory methodology for examining the value of units based on the cost approach of land appraisal. Particularly, we propose the Shapley value solution to examine the allocation of the land and construction cost among the stories of the building. We explore the allocation mechanism and derive several closed-form properties by which the value pattern of stories in a building is rationalized. The proposed cost allocation may, among other things, generate values when comparable market prices are unobservable (consistent with the cost approach); may be used by courts in order to compute compensations in cases of disputes regarding expansions and redevelopments of existing structures among co-owners; and may determine the rent cost allocation in an organization with several profit centers located on different floors of a building.

Em busca da eficiência no transporte terceirizado: estrutura de custos, parcerias e eliminação de desperdícios

O objetivo deste artigo é apresentar um modelo racional para custeio de transporte como elemento fundamental ao bom funcionamento de parcerias entre embarcadores e transportadoras numa cadeia de suprimentos. A aplicação deste modelo a situações reais traz à tona uma série de informações importantes, a principal delas é o fato que o atual sistema de custeio utilizado pela maioria das empresas brasileiras causa sérias distorções em termos de custos, quando se consideram rotas curtas e rotas longas, subavaliando as primeiras e super-avaliando as últimas. Estas distorções estão vinculadas à elevada ineficiência no transporte de mercadorias, sobretudo nas operações de carregamento e descarregamento, cujos tempos médios excedem seis horas. Dentro deste escopo são definidos o conceito de parceria, suas implicações organizacionais e suas conseqüências imediatas, como por exemplo, o envolvimento de ambas as partes num programa de qualidade e produtividade do transporte. A adoção deste programa, paralelamente ao acordo quanto a um sistema de custeio de frete com as transportadoras que garantam um nível mínimo de retorno sobre seu investimento, tornam mais claras, e facilmente mensuráveis, as oportunidades para exploração de ganhos conjuntos dentro de um ambiente de parceria. Finalmente, são descritas as três causas básicas que levam a ineficiência das operações de carregamento e descarregamento no Brasil: organizacionais, tecnológicas e procedimentos.