• Energy Research

Most of the studies encompassing dynamic simulations of multi-storey buildings account only for a few selected zones, to simplify, decrease simulation run-time and to reduce the complexity of the ‘to be simulated’ model. This conventional method neglects the opportunity to see the interaction between different zones as it relates to whole building performance. This paper presents fifteen individual cases of dynamic simulations of a six-storey office building with 160 zones. The energy performance analysis was conducted for three climate zones including Helsinki in Finland, London in the United Kingdom and Bucharest in Romania. For each location, the following three cases were simulated: (i) building as usual simulated according to valid national building codes; (ii) Energy-efficient (EE) case with selected necessary parameters enhanced to reduce total delivered energy demand; and (iii) nZEB case representing partial enhancement of the EE case based on the parametric analysis. The results of nZEB indicate that for Helsinki, it is possible to reduce the space-heating load by 86%, electricity consumed by lighting, appliance, and HVAC by 32%. For London, the heating load is reduced by 95%, cooling load is slightly increased, and electricity demand is decreased by 33%. For Bucharest, 92% of energy in heating can be saved, cooling energy demand was reduced by 60% and electricity consumption by 34%. Based on the nZEB cases for each location, alternative heating and cooling choices of a radiant floor panel system and radiant ceiling panel system were explored. There are small differences in absolute consumption demand for heating, cooling, and electricity for three cases in each location. The specific energy/m2 for heating remained nearly the same in all systems for all three cases in each location. Alternative choices for heating and cooling by using Radiant Ceiling Panel (RCP) and Radiant Floor Panel (RFP) were investigated for all final nZEB cases. Marginal difference in heating energy required for space heating can be seen for London nZEB IHC and London nZEB RCP of 0.8 kWh/m2/year and for Bucharest nZEB IHC and Bucharest nZEB RCP case of 1.3 kWh/m2/year. RFP has the availability of large surface area for heat exchange and can provide heating at a low temperature and cooling at high temperature, but requires supporting air based cooling during the humid season. For RCP, the limited temperature exchange surface may increase the airflow rate, but supplies it at a lower temperature for the same load.

This study proposes to use gas-fired boilers as peak shaving heat sources in heating substations due to their capability to increase the reliability, flexibility and heat capacity without the need to change the district heating network (DHN). However, the design and operational requirements with different connection modes for this kind of DH system are still not clear. This paper presents a systematic study on this kind of DH system, analyzes the connection modes of series and parallel connections between the gas-fired boilers and the heat exchangers. For each connection mode, we figured out the thermal balances and obtained the design and operational parameters including the supply temperatures of the heat exchangers, gas-fired boilers and their variations under different network temperature levels and the base load ratios (β). Under the series connection mode, the design supply temperature of the heat exchangers has no relation with the design peak shaving flow ratio (ω′); it decreases linearly along with smaller β, and the decreasing slope is higher with bigger temperature difference (Δt) of the DHN. However, the design supply temperatures of gas-fired boilers increase linearly when β and/or ω′ are smaller, and the increasing speed is proportional to Δt. For the parallel connection mode, the design supply temperatures of the heat exchangers and gas-fired boilers are all affected by β, ω′ and Δt. The former decreases when β and/or ω′ are smaller, while the latter increases at the same time. Finally, the design peak shaving flow ratio ω′ are determined for the peak boilers with series and parallel connection modes. The study provides a theoretical basis for the design and operation of the DH system with peak heating boilers in substations in order to reach a lower investment and higher efficiency.

Abstract The EU emissions trading scheme (ETS) taking effect in 2005 covers CO2 emissions from specific large-scale industrial activities and combustion installations. A large number of existing and potential future combined heat and power (CHP) installations are subject to ETS and targeted for emissions reduction. CHP production is an important technology for efficient and clean provision of energy because of its superior carbon efficiency. The proper planning of emissions trading can help its potential into full play, making it become a true “winning technology” under ETS. Fuel mix or fuel switch will be the reasonable choices for fossil fuel based CHP producers to achieve their emissions targets at the lowest possible cost. In this paper we formulate CO2 emissions trading planning of a CHP producer as a multi-period stochastic optimization problem and propose a stochastic simulation and coordination approach for considering the risk attitude of the producer, penalty for excessive emissions, and the confidence interval for emission estimates. In test runs with a realistic CHP production model, the proposed solution approach demonstrates good trading efficiency in terms of profit-to-turnover ratio. Considering the confidence interval for emission estimates can help the producer to reduce the transaction costs in emissions trading. Comparisons between fuel switch and fuel mix strategies show that fuel mix can provide good tradeoff between profit-making and emissions reduction.

This study is about multicriteria decision aiding (MCDA) for the green airports program of the Moroccan Airport Authority ONDA. The goal of the program is to develop significant amounts of renewable power at airports. In particular, ONDA wants to select airports at which large solar and wind power parks should be built. Multiple criteria, including economy, technical feasibility, and environmental concerns, must be considered simultaneously. In this study, we apply Stochastic Multicriteria Acceptability Analysis (SMAA) for ranking the candidates to be developed into green airports. The analysis is conducted in phases with different sets of criteria. This study is the first application of MCDA for developing large-scale renewable energy production at airports. As a theoretical novelty, the pairwise winning indices of SMAA are used to form stochastic partial and complete rankings of the alternatives. Based on the results, two alternatives obtain the best and second-best rank in every model, and one alternative is always last, while the ranks of the remaining alternatives vary depending on the set of criteria.

Funding Information: This study was supported by academy research fellow funding from Research Council of Finland (Funding No. 334205 and 358055 ). Publisher Copyright: © 2023 The Authors Optimizing district heating (DH) systems in a holistic manner is often impeded by the computational complexities associated with network modeling. This study introduces a novel, efficient and theoretically accurate method for dynamic thermal modelling of DH pipes. The approach is to track water frontiers traveling along the pipe using discrete event simulation (DES) paradigm. As the DES method is based on variable time steps, the computational effort is significantly reduced compared to earlier methods. The proposed model can compute outlet water temperature, temperature profile along the pipe, and heat loss based on variable inlet temperature and flow rate. The DES model was validated by comparison with real measurements of a long DH pipe. Four variants of the model with different temperature profile assumptions and interpolation methods were compared. Numerical results show that the DES model can accurately predict outlet water temperature with a maximum discrepancy of 0.52 °C. The mean error of simulated outlet temperature was −0.01 ± 0.02 °C. Average computation time for 24-h simulation was 59 μs. Overall, this study shows that the DES method is appropriate for variable time step simulation for DH pipe, potentially, for network simulation. Our study may also inspire variable time step implementation in other energy applications. Peer reviewed

Abstract The electricity market has changed rapidly in the Northern European countries. Harmonisation of the legislation and trading methods widens the market area outside national limits. Vertical integration among electricity companies is changing the traditional structure of the inner market. Successful business in this new, more volatile market requires sophisticated techniques for identifying new market opportunities and managing the increased risks. We study the new market from the perspectives of regional distributors and power pools. We analyse the trading possibilities and profitability of different kinds of power pools, when a spot market and several new contract structures are available along with existing capacity-based long-term contracts. Different policies for allocating the common benefits of a power pool among its members are compared and a new booking algorithm for balance settlement is introduced. To analyse the operation of different kinds of pools, we use simulation and optimisation techniques.

Abstract The European electricity market has been deregulated recently. This means that energy companies must optimise power generation considering the rapidly fluctuating price on the spot market. Optimisation has also become more difficult. New production technologies, such as gas turbines (GT), combined heat and power generation (CHP), and combined steam and gas cycles (CSG) require non-convex models. Risk analysis through stochastic simulation requires solving a large number of models rapidly. These factors have created a need for more versatile and efficient decision-support tools for energy companies. We formulate the decision-problem of a power company as a large mixed integer programming (MIP) model. To make the model manageable we compose the model hierarchically from modular components. To speed up the optimisation procedure, we decompose the problem into hourly sub-problems, and develop a customised Branch-and-Bound algorithm for solving the sub-problems efficiently. We demonstrate the use of the model with a real-life application.

Abstract This paper addresses the unit commitment in multi-period combined heat and power (CHP) production planning, considering the possibility to trade power on the spot market. In CHP plants (units), generation of heat and power follows joint characteristics, which means that production planning for both heat and power must be done in coordination. We present an improved unit decommitment (IUD) algorithm that starts with an improved initial solution with less heat surplus so that the relative cost-efficiency of the plants can be determined more accurately. Then the subsequent decommitment procedures can decommit (switch off) the least cost-efficient plants properly. The improved initial solution for the committed plants is generated by a heuristic procedure. The heuristic procedure utilizes both the Lagrangian relaxation principle that relaxes the system-wide (heat and power) demand constraints and a linear relaxation of the ON/OFF states of the plants. We compare the IUD algorithm with realistic test data against a generic unit decommitment (UD) algorithm. Numerical results show that IUD is an overall improvement of UD. The solution quality of IUD is better than that of UD for almost all of tested cases. The maximum improvement is 11.3% and the maximum degradation is only 0.04% (only two sub-cases out of 216 sub-cases) with an average improvement of 0.3–0.5% for different planning horizons. Moreover, IUD is more efficient (1.1–3 times faster on average) than UD.