Search

Operation of the production system and of the utility system is commonly optimized separately without feedback between them. This separated planning in general increases total costs. Conceptually, a joint optimization of production and utility system is desirable, but often not possible in practice. We overcome such practical limitations by proposing a repeated Stackelberg game. In the proposed method, the production schedule is determined such that costs for both production and utility system are reduced. For this purpose, price information are passed from the utility system to the production system leading to fast convergence of the repeated Stackelberg game. The proposed repeated Stackelberg game is applied to two literature-based case studies. The proposed method reduces the total costs in one repetition by 9% and 5%. The suggested method provides an effective and practical approach to operate systems with reduced minimal total costs in practice.

Increasing levels of variable renewable energy require additional flexible resources in the global energy system. In countries with energy-intensive industries, flexibility may be increased through industrial demand side management (IDSM). In most studies, the potential of IDSM is estimated from a technical or theoretical viewpoint. However, IDSM capacity is only utilized if the industry finds it profitable, and thus the economic potential should also be assessed. The focus of this paper is on the intra-day IDSM potential of a paper mill site that is active in the Nordic power market. An optimization model is built to estimate the costs that occur when the paper mill executes regulating power bids, if the original production schedule has been optimized against a spot price forecast. The costs are estimated for different sizes of bids and a marginal cost curve is provided for pricing them. Using this marginal cost curve, the market potential of the case mill site is assessed. It is found that this potential is greatly influenced by the costs of executing regulating power bids. The results indicate that transmission system operators and policy makers should account for economic factors when assessing the potential of market based IDSM.

This paper optimizes the design and operation of integrated distributed energy systems of large buildings and light industrial plants. The integration reduces greenhouse gas (GHG) emissions and the annual total cost (ATC) beyond the best possible from individual energy systems and there is a sharp optimum with respect to the size of the confectionary plant, which maximizes the reduction of GHG emissions and minimizes ATC. In contrast to previous studies, the design accounts for plant heating demands at different temperature levels and sets plant production volumes as decision variables. Optimal design, operation, and production schedule have been determined via a mixed-integer nonlinear programming model. Integrated energy systems of two entities (confectionary plant and residential building) have been compared to the non-integrated entities equipped with combined cooling, heating, and power systems. The lowest ATC (−8%) of the integrated system and the maximum GHG reductions (−8.3%) occur at slightly different sizes of the plant. Such reductions require simultaneous optimization of integrated design and operation of energy systems and relative sizes of the confectionary plant and the residential building.

In China, district heating systems are facing a dilemma between rapid growth in demand owing to urbanization and environmental problems related to coal-fired boilers. The utilization of industrial surplus heat has great potential on improving the power of heating systems and reducing coal consumption of boilers. However, few industrial systems are constructed under the consideration of district heating. Some features of the surplus heat, such as the position, grade, and production schedule, are significantly different to traditional heat sources. To recover the surplus heat, retrofits of district heating systems are necessary. In this paper, according to the current situations and the future developments, a scheme is proposed to integrate the surplus heat of two steel plants into a large-scale district heating network. Three sources of surplus heat are involved: slag-flushing water, cooling water, and low-pressure steam. The scheme has been partly applied in a corresponding demonstration project. The actual performance proves the feasibility of the integrated system and implies significant benefits in terms of economic cost, CO 2 emission and pollutant emissions. Furthermore, the potential to extend the scheme in Northern China is also evaluated.

Biofuel is considered a promising alternative to traditional liquid transportation fuels. The large-scale substitution of biofuel can greatly enhance global energy security and mitigate greenhouse gas emissions. One major concern of the broad adoption of biofuel is the intensive energy consumption in biofuel manufacturing. This paper focuses on the energy efficiency improvement of biofuel feedstock preprocessing, a major process of cellulosic biofuel manufacturing. An improved scheme of the feedstock preprocessing considering work-in-process particle separation is introduced to reduce energy waste and improve energy efficiency. A scheduling model based on the improved scheme is also developed to identify an optimal production schedule that can minimize the energy consumption of the feedstock preprocessing under production target constraint. A numerical case study is used to illustrate the effectiveness of the proposed method. The research outcome is expected to improve the energy efficiency and enhance the environmental sustainability of biomass feedstock preprocessing.

New energy vehicles (NEVs) are becoming more and more prevalent for economic and environmental reasons. This paper investigates the issue of the impacts of subsidy policy and dual credit policy on NEVs and conventional vehicles (CVs) production decision from an across-chain perspective, in a co-opetitive context, where exists a CV supply chain and a NEV supply chain with two important schemes involved, i.e., government subsidies and dual credit. While previous literature has discussed government subsidies excessively, they seldom study the role of dual credit policy in promoting NEVs. To examine the differences between two schemes, a mixed integer linear programing (MILP) is utilized to develop a stylized production model for a CV supply chain and NEV supply chain system that incorporating subsidies and dual credit trading simultaneously. Using a Lagrange heuristic algorithm to provide an optimal solution regarding NEV and CV production decision as well as dual-credit trading. Simulations are performed on realistic profiles that show, (i) implementing the dual credit policy increases the profit of NEV supply chain, whereas the profit of CV supply chain and of whole supply chain system decline simultaneously, and the schedule of CVs/NEVs without across-chain cooperation is arranged more evenly than that with across-chain cooperation during the transit period to NEVs. Meanwhile, (ii) under dual credit policy, gradually-decreasing subsidies can partially offset the negative impacts of dual credit policy on the NEV supply chain, the subsidies can only serve as a temporary supplement to profits. In addition, (iii) there exists an optimal NEV credit price p ∗ to maximize the overall profit of the whole system, and a corresponding threshold value of p ∗ for two categories of cars, when above the threshold, the per-CV profit outperforms the per-NEV one and vice versa.

Microgrids usually operate in disparate locations and may not be connected to the national grid. The potential sources of electricity in microgrids are wind farms, solar energy, biomass, tidal energy, among others. However, microgrids that are connected to the national grid are gaining importance, because they can supply electricity to the national grid when they have an excess and buy from it when they are in shortage. Such a symbiotic relationship with the national grid helps reduce investment in storage capacity and minimizes other operational costs. In this work, we develop a mathematical model MILP – (mixed integer linear programming) for scheduling operations in microgrids connected to the national grid. We allow several realistic features such as time constraints for the purchase/sale of power from/to the national grid; round trip efficiency of batteries; hydrogen generation, and limits on storage and retrieval rates from batteries/hydrogen tanks/natural gas tanks. Furthermore, to maintain diversity in the generation of electricity from multiple resources, we develop and impose a novel linear diversity constraint on the production schedule without sacrificing the ease of schedule implementation.