Is total system cost minimization fair to all the actors of an energy system? Not according to game theory

Organisations attempt to contribute their share towards fighting the climate crisis by trying to reduce their emission of greenhouse gases effectively towards net zero. An instrument to guide their reduction efforts is internal carbon pricing. Next to choosing the right pricing tool, defining the exact value of an internal carbon price, especially against the background of potential regulatory external carbon prices, and assessing its impact on business units’ energy systems poses a challenge for organisations. The academic literature has so far not examined the impact differences of an internal carbon price across different countries, which this paper addresses by using an optimisation model. First, it analyses the energy system cost increase of a real-world facility based on an internal carbon price compared to a potential regulatory carbon price within a country. Second, we evaluate the energy system cost increase based on an internal carbon price across different countries. The results show that with regard to internal carbon prices the additional total system cost compared to potential external carbon prices stays within 9%, 15%, and 59% for Germany, Japan, and the United Kingdom, respectively. The increase in the energy system cost in each country varies between 3% and 93%. For all countries, the cost differences can be reduced by allowing the installation of renewables. The integration of renewables via energy storage and power-to-heat technologies depends on the renewable potentials and the availability of carbon capture and storage. If organisations do not account for these differences, it might raise the disapproval of internal carbon prices within the organisation.

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Welfare effects of technology-based climate policies in liberalized electricity markets: seeing beyond total system cost

Swiss Journal of Economics and Statistics ◽

10.1186/s41937-019-0039-1 ◽

2019 ◽

Vol 155 (1) ◽

Author(s):

Sophie Maire ◽

Philippe Thalmann ◽

Frank Vöhringer

Keyword(s):

Electricity Markets ◽

Electricity Market ◽

Power Plants ◽

Energy System ◽

Reference Scenario ◽

Total System ◽

Modeling Framework ◽

System Cost ◽

Energy System Model ◽

Policy Scenario

Abstract This paper is a contribution to assessing the Swiss energy transition, with an emphasis on the consequences of decommissioning the nuclear power plants for the electricity market and the whole economy. We expect that increased renewable generation and demand-side policies of the type already envisioned will not suffice to close the supply gap, so that Switzerland will have to rely on more imports of electricity, moving away from the export surpluses realized almost every year since 1910. As this reference scenario is contrary to desired energy security, a policy scenario is proposed in which net electricity trade is constrained to balance over the year and the supply gap is closed by relaxing the existing restrictions on gas-fired power plants. One constraint replaces another one, so that the impacts are not obvious. Furthermore, the prices of electricity and natural gas evolve quite differently through time and depend on climate and energy policy. We use a modeling framework coupling a detailed representation of electricity generation and an encompassing representation of the macro-economy to compare these scenarios in terms of both total system cost and welfare. Both indicators favor the reference scenario without gas-fired power plants in spite of its higher marginal costs for electricity. The welfare loss of the policy scenario is small, though, much smaller than the increase in total system cost. This shows that a coupled bottom-up top-down modeling framework assessing the welfare effect of policies can yield very different results from those of an energy system model assessing their impact on total system cost.

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How to Reach the New Green Deal Targets: Analysing the Necessary Burden Sharing within the EU Using a Multi-Model Approach

Energies ◽

10.3390/en14237971 ◽

2021 ◽

Vol 14 (23) ◽

pp. 7971

Author(s):

Felix Kattelmann ◽

Jonathan Siegle ◽

Roland Cunha Montenegro ◽

Vera Sehn ◽

Markus Blesl ◽

...

Keyword(s):

Emission Trading ◽

Energy System ◽

Burden Sharing ◽

Total System ◽

The European Union ◽

System Perspective ◽

Energy System Model ◽

Eu Member States ◽

Computational General Equilibrium ◽

The Eu

The Green Deal of the European Union defines extremely ambitious climate targets for 2030 (−55% emissions compared to 1990) and 2050 (−100%), which go far beyond the current goals that the EU member states have agreed on thus far. The question of which sectors contribute how much has already been discussed, but is far from decided, while the question of which countries shoulder how much of the tightened reduction targets has hardly been discussed. We want to contribute significantly to answering these policy questions by analysing the necessary burden sharing within the EU from both an energy system and an overall macroeconomic perspective. For this purpose, we use the energy system model TIMES PanEU and the computational general equilibrium model NEWAGE. Our results show that excessively strong targets for the Emission Trading System (ETS) in 2030 are not system-optimal for achieving the 55% overall target, reductions should be made in such a way that an emissions budget ratio of 39 (ETS sector) to 61 (Non-ETS sector) results. Economically weaker regions would have to reduce their CO2 emissions until 2030 by up to 33% on top of the currently decided targets in the Effort Sharing Regulation, which leads to higher energy system costs as well as losses in gross domestic product (GDP). Depending on the policy scenario applied, GDP losses in the range of −0.79% and −1.95% relative to baseline can be found for single EU regions. In the long-term, an equally strict mitigation regime for all countries in 2050 is not optimal from a system perspective; total system costs would be higher by 1.5%. Instead, some countries should generate negative net emissions to compensate for non-mitigable residual emissions from other countries.

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Optimum sizing and simulation of hybrid renewable energy system for remote area

Energy & Environment ◽

10.1177/0958305x211030112 ◽

2021 ◽

pp. 0958305X2110301

Author(s):

Animesh Masih ◽

HK Verma

Keyword(s):

Renewable Energy ◽

Reliability Index ◽

Energy System ◽

Energy Resources ◽

Total System ◽

Renewable Energy Resources ◽

Optimal Sizing ◽

Remote Areas ◽

Grasshopper Optimization Algorithm ◽

Hybrid Renewable Energy

In current scenario, people tend to move towards outskirts and like to settle in places that are close to nature. But, due to urban lifestyle and to fulfill the basic needs, demand of electricity remains the same as in urban areas. This demand of electricity can be only fulfilled by using hybrid renewable energy resources, which is easily available in outskirts. Renewable energy resources are unreliable and more expensive. Researchers are working to make, it more reliable and economic in terms of utilization. This article proposes a metaheuristic grasshopper optimization algorithm (GOA) for the optimal sizing of hybrid PV/wind/battery energy system located in remote areas. The proposed algorithm finds the optimal sizing and configuration of remote village load demand that includes house electricity and agriculture. The optimization problem is solved by minimization of total system cost at a desirable level of loss of power supply’s reliability index (LPSRI). The results of GOA are compared with particle swarm optimization (PSO), genetic algorithm (GA) and hybrid optimization of multiple energy resources (HOMER) software. In addition, results are also validated by modeling and simulation of the hybrid energy system and its configurations at different weather conditions-based results. Hybrid PV/wind/battery is found as an optimal system at remote areas and sizing are[Formula: see text] with cost of energy (COE) (0.3473$/kWh) and loss of power supplies reliability index (LPSRI) (0%). It is clear from the results that GOA based methods are more efficient for selection of optimal energy system configuration as compared to others algorithms.

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Optimizing total system cost by balancing unit cost against real cost

Sealing Technology ◽

10.1016/s1350-4789(07)70237-4 ◽

2007 ◽

Vol 2007 (5) ◽

pp. 11-13 ◽

Cited By ~ 3

Author(s):

Johan François

Keyword(s):

Unit Cost ◽

Total System ◽

System Cost ◽

Real Cost

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Mississippi County Community College Solar Photovoltaic Total Energy Project

Volume 2: Solar Energy ◽

10.1115/79-sol-13 ◽

1979 ◽

Author(s):

E. M. Henry

Keyword(s):

Community College ◽

Energy Demand ◽

Storage System ◽

Vital Signs ◽

Electrical Energy ◽

Redox System ◽

Energy System ◽

Energy Storage System ◽

Total System ◽

Efficient Operation

Mississippi County Community College at Blytheville, Arkansas, will derive its total electrical and thermal energy demand from an actively cooled photovoltaic energy system being developed under the management of TEAM, Inc. of Springfield, Virginia. The facility has a design peak electrical requirement for 240 kw to be supplied by a 26-sun concentrating collector field that fully tracks E-W. A 2.4 megawatt-hour electrical energy storage system under consideration is an iron redox system using FeCl2 electrolyte and pressure-molded carbon/PVC electrodes. The power conditioning system will include a 300-kw solid-state inverter to furnish 480-v, three-phase, 60-Hz ac to the College, and appropriate switching to acquire utility company power in emergencies. Process control includes the capability to gather vital signs on the collectors, thermal loop, electrical storage and building demands, and to provide closed-loop tracking and all control signals for energy efficient operation of the total system.

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