Market Power With Combined Heat and Power Production in the Nordic Energy System

Virasjoki, Vilma; Siddiqui, Afzal S.; Zakeri, Behnam; Salo, Ahti

doi:10.1109/tpwrs.2018.2811959

Cited by 32 publications

(24 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where a i and b i are intercept and slope of the bid function of unit i; N and L are the number of units and transmission lines; P d is the total load; P i , P i,min and P i,max are the generations of unit i, lower and upper generation limits, respectively; c l,i is the line flow distribution factor of line l due to the generation of unit i; a l and a l are the lower and upper limits derived from the maximum line flow l. The transmission lines constraints are expressed as restrictions on the weighted sum of the production of units [24]. The LMPs and the dispatch of the generators are calculated by solving the market problem (1). The Lagrangian method is employed to solve the optimization problem (1) [24,30].…”

Section: Market Structurementioning

confidence: 99%

See 1 more Smart Citation

Locational marginal price share: a new structural market power index

Hajiabadi

Samadi

2019

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

Market power is known as the ability of units and generation companies (GenCos) to change electricity price profitably. As cleared in the definition, locational marginal price (LMP) is the most important key in market power evaluation. Therefore, the main objective of the paper is to analyze market power of units and GenCos based on their abilities to change electricity price. At the first step, using Karush-Kuhn-Tucker (KKT) conditions of Lagrangian method, LMP is decomposed into four main components. These components indicate the share of each unit at the LMP of each bus. These values are calculated by the proposed analytical method, and cannot be obtained using simulation methods. At the second step, ''unit-based LMP_S'' index, which indicates the contribution factor of each unit at LMP of each bus, is proposed as a new structural market power index. This index is also used as an effective tool to determine the most profitable coalition between two units. Using that, the market operator can predict highly potential collusions. Moreover, ''GenCosbased LMP_S'' index is proposed. Using this effective tool, the contribution of each GenCo, which owns multiple units in various buses, at the LMP of each bus is discovered. The proposed market power indices are calculated on the IEEE 24-bus test system and compared with some conventional structural market power indices. Incremental profits of units due to change of unit's strategies verify the accuracy of proposed method.

show abstract

Section: Market Structurementioning

confidence: 99%

“…Market power is the ability of a generation company (GenCo) to increase the electricity price profitably [1,2]. Therefore, the main issue in market power studies is analyzing the electricity price to determine the effective factors to change it.…”

Section: Introductionmentioning

confidence: 99%

Locational marginal price share: a new structural market power index

Hajiabadi

Samadi

2019

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

show abstract

“…Such systems have become more popular, especially with the growing installed capacity of combined heat and power (CHP) plants. For instance, Denmark and Finland, supply 75% of their district heating with CHP [1]. One explanation of the growing adoption of CHP technology is that it has the advantage of combining the generation of heat and electricity within a single process, which leads to higher overall efficiency [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…Power generation from CHP plants for district heating is often considered as incidental since CHP are most of the time operated to supply heat and hot water first [4,5], although associated electricity generation can represent a significant share of the district supply. Using the example of Denmark, CHP power generation has represented 50% of the national electricity production [1]. At the scale of the European Union, CHP plants have supplied around 15% of the electricity demand, a share that is expected to increase to 22-25% by 2030 [6].…”

Section: Introductionmentioning

confidence: 99%

Complementarity between Combined Heat and Power Systems, Solar PV and Hydropower at a District Level: Sensitivity to Climate Characteristics along an Alpine Transect

et al. 2020

View full text Add to dashboard Cite

Combined heat and power systems (CHP) produce heat and electricity simultaneously. Their resulting high efficiency makes them more attractive from the energy managers’ perspective than other conventional thermal systems. Although heat is a by-product of the electricity generation process, system operators usually operate CHP systems to satisfy heat demand. Electricity generation from CHP is thus driven by the heat demand, which follows the variability of seasonal temperature, and thus is not always correlated with the fluctuation of electricity demand. Consequently, from the perspective of the electricity grid operator, CHP systems can be seen as a non-controllable energy source similar to other renewable energy sources such as solar, wind or hydro. In this study, we investigate how ‘non-controllable’ electricity generation from CHP systems combines with ‘non-controllable’ electricity generation from solar photovoltaic panels (PV) and run-of-the river (RoR) hydropower at a district level. Only these three energy sources are considered within a 100% renewable mix scenario. Energy mixes with different shares of CHP, solar and RoR are evaluated regarding their contribution to total energy supply and their capacity to reduce generation variability. This analysis is carried out over an ensemble of seventeen catchments in North Eastern Italy located along a climate transect ranging from high elevation and snow dominated head-water catchments to rain-fed and wet basins at lower elevations. Results show that at a district scale, integration of CHP systems with solar photovoltaic and RoR hydropower leads to higher demand satisfaction and lower variability of the electricity balance. Results also show that including CHP in the energy mix modifies the optimal relative share between solar and RoR power generation. Results are consistent across the climate transect. For some districts, using the electricity from CHP might also be a better solution than building energy storage for solar PV.

show abstract

“…For example, inadequate representation of variability in power system modelling will have consequences for a holistic approach to smart energy systems . Likewise, the coupling of the power system with district heating in terms of integrating VRES is important for the Nordic region (Virasjoki et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Policy implications of downscaling the time dimension in power system planning models to represent variability in renewable output

Reichenberg

Siddiqui

Wogrin

2018

Energy

View full text Add to dashboard Cite

Due to computational constraints, power system planning models are typically unable to incorporate full annual temporal resolution. In order to represent the increased variability induced by large amounts of variable renewable energy sources, two methods are investigated to reduce the time dimension: the integral approach (using typical hours based on demand and renewable output) and the representative days method (using typical days to capture annual variability). These two approaches are tested with a benchmark implementation that incorporates full time representation in order identify their suitability for assessing power systems with high renewable penetration. The integral method predicts renewable representation, it may be more applicable to one-node models, while the representative days method is suitable for multi-regional models. In order to assess power systems with increasing renewable policy targets, models should be designed to handle at least the 160 time steps needed to provide results that do not systematically overestimate the renewable capacity share.

show abstract

Market Power With Combined Heat and Power Production in the Nordic Energy System

Cited by 32 publications

References 31 publications

Locational marginal price share: a new structural market power index

Locational marginal price share: a new structural market power index

Complementarity between Combined Heat and Power Systems, Solar PV and Hydropower at a District Level: Sensitivity to Climate Characteristics along an Alpine Transect

Policy implications of downscaling the time dimension in power system planning models to represent variability in renewable output

Contact Info

Product

Resources

About