Evidence-Based Policy Making: Insights and Policy Recommendations for the Implementation of a Clean Energy Transition in Kenya.

doi:10.21203/rs.3.rs-2449948/v2

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Evidence-Based Policy Making: Insights and Policy Recommendations for the Implementation of a Clean Energy Transition in Kenya.

https://doi.org/10.21203/rs.3.rs-2449948/v2

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With ambitious targets to drastically increase economic activity over the next decade in order to propel itself to become a middle-income country, Kenya’s future is undoubtedly energy intensive. Through the achievement of its bold and aspiring goals, Kenya is poised to become a regional economic giant with the capacity to strengthen its position as a global leader in renewable energy production. However, current energy capacity expansion plans will see Kenya drastically ramp up fossil fuel generation, significantly increasing emissions and regressing progress made towards its climate and renewable energy targets. Therefore, Kenya is at a crucial stage of its national development with critical decisions to make regarding its future energy expansion and production.

The use of energy systems modelling as a method to provide key insights for evidence-based policy making has risen in importance in energy planning globally. Such an approach can provide crucial insights and projections on the impact of potential policy decisions, creating pathways to be adopted within policy. As a result, this study employs long-term energy systems modelling to explore a series of potential future scenarios for Kenya’s power sector, providing insights into their generation, total production, and costs that can assist national policy making. Specifically, this research utilises OSeMOSYS modelling software to produce a Clean Energy Transition scenario (CET) as one possible future for Kenya’s power sector to increase renewable energy production under rapidly intensifying demand. The critical insights gained in this research were employed to suggest seven key policy recommendations for Kenya’s power sector.

Environmental Policy

Energy Engineering

Kenya

Clean Energy Transitions

OSeMOSYS

Modelling

Policy Making

Renewable Energy

With a population of over 50 million, an annual gross domestic product (GDP) of $85 billion USD, and a yearly GDP growth rate of over 5.6% for the past decade, Kenya has become a regional economic leader (USAID and Power Africa, 2019). Kenya has undergone recent changes and developments through its active experience of and recovery from coronavirus, revised energy policy (Republic of Kenya, 2018a), national climate action plan (Kwene et al., 2014; Naess et al., 2015) and Vision 2030 blueprint (Republic of Kenya, 2018b). As a result, Kenya is currently at an exciting and crucial stage of its national development in terms of forging its energy future. The observation that reducing greenhouse gas emissions is the most important challenge to policy makers in their attempts to reduce and respond to climate change (Turton, 2008) remains valid. Globally, over 80% (IEA, 2023) of the total energy supply is derived from fossil fuels, having a wide reaching and damaging impact on the environment, ecosystems, and humans (Rambo, 2013) through their production of greenhouse gases and other pollutants. Although recent international focus has shifted towards renewable energy resources, significant global investment opportunities and policy targets still focus on fossil fuel extraction and production (Helm, 2016). As a result, there is great scope to assess the future role of renewable energy to drive a Kenyan Clean Energy Transition (CET).

Kenya, a lower-middle income regional economic powerhouse, relies primarily on its agriculture, fishing, mining, manufacturing, and energy sectors to drive its economic production (Bryan et al., 2013; Njiru and Letema, 2018). As Kenya’s economy is currently the second largest in eastern Africa ($85bn USD; after Ethiopia) and fifth in sub-Saharan Africa (SSA), the country is seen as a regional economic giant with considerable influence. Over the last decade, GDP has grown at over 5.6% per year, outpacing average population growth of ~2.5%, allowing per capita GDP to rise (AFBD, 2022). Kenya has made ambitious energy statements through its national Vision 2030 development plan, aiming to reach 100% renewable energy generation by the end of this decade (Republic of Kenya, 2018a). Thus, it could lead a wave of successful renewable energy transitions within the region (Myers, 2015).

Kenya has the potential to play an exciting role from its capacity to produce climate compatible economic growth and is widely considered to be a regional leader in its promotion and development of renewable and clean energies (Wolde-Rufael, 2009; Uddin et al., 2013). Kenya’s geographical location presents a wealth of attractive and affordable renewable energy options at its disposal (Ndiritu and Engola, 2020; Oluoch et al., 2021). As outlined by Kiplagat et al. (2012), Kenya is therefore a global leader in renewable energy, with one of the most sustainable power mixes internationally. Coinciding with its grid extension strategies and competitive affordability compared to fossil fuel sources, Kenya is in a prime position to implement a successful and world-leading energy transition (Njoroge et al., 2020). Because of this, Kenya has the potential to spearhead and lead in the implementation of CETs across sub-Saharan Africa (Huho and Kosonei, 2014; Carvallo et al., 2017; Juma and Khademi-Vidra, 2019).

Kenya has several existing policies which relate to its CET and climate change commitments. These Are:

1. African Union Agenda 2063: This states that the expansion of energy systems should be primarily provided by clean and renewable sources to promote energy security and contribute to decarbonisation measures (Tella, 2018; Karuri-Sebina, 2020; Nwozor et al., 2021). Additionally, the blueprint states a target for all nations of achieving a GDP growth of at least 7% annually by 2063 (AU, 2022).

2. Vision 2030: This aims to transform Kenya into an industrialised middle-income economy by 2030 through the core pillars of political, social, and economic advancement.

3. Least Cost Power Development Plan (LCPDP): This identifies three main priorities of: a) increased diversification and supply of domestic energy; b) increased connectivity and affordability of electricity; and c) increased proportion of renewable energy resources and energy efficiency (EE) measures (Republic of Kenya, 2016a). The blueprint outlines a prediction of annual Kenyan GDP growth of 7% until 2020, with a progressive increase to 10% from 2025 (Republic of Kenya, 2018a). The LCPDP models geothermal resources to be the primary least cost source of future power generation and predicts this will account for 26% of all Kenyan production by 2036.

Clean Energy Transitions (CETs)

CETs are widely deemed as essential to ensure developing countries globally can meet national and international climate targets (Ockwell et al., 2021). Rambo (2013) discusses how sustainable economic development through a CET would be primarily achieved by replacing all fossil fuels with renewable and clean energy sources. Such a transition facilitates the promotion of a low carbon economy which not only increases climate resilience, but also enables a program of poverty alleviation (Sovacool et al., 2017). Additionally, scholars have discussed a wealth of benefits from having an efficient energy (EE) system, including lowering consumer bills keeping energy affordable, reducing reliance on fuel imports, softening demand growth, and reducing pressure on existing energy infrastructures (Benromdhane, 2015; Hajek et al., 2019). A recent report by the IEA (2022) found that increasing both energy and material efficiency could help reduce overall energy demand by up to 30%. Further, EE is seen as increasingly vital to curtail the increasing energy demand (up to 30%) expected across the African continent over the next decade (Taliotis et al., 2016), from adding pressure to ageing and overwhelmed transmission and distribution infrastructure (Pan et al., 2020). The Kenyan National Adaption Plan 2015-2030 (2016) therefore highlights the need for an energy transition within the region to increase both the efficiency and reliability of supply to develop the economy both successfully and sustainably.

Renewable energy potential

Kenya has a wealth of diverse renewable sources for possible future utilisation (Irungu et al., 2014). Unique to the eastern African region is the substantial potential geothermal power capacity at over 18 GW (Merem et al., 2019), of which Kenya could account over 50%. This is primarily in the Kenyan Rift Valley and is estimated at around 10 GW (Hughes and Rogei, 2020). Kenya’s energy mix also contains a significant share of hydropower, with a current installed capacity of over 800 MW out of a potential estimated at between 3000 and 6000 MW (Lahmeyer International, 2016). Additionally, Northern Kenya is characterised by particularly strong winds, providing a wealth of wind power potential, which has begun with the development of the Lake Turkana wind farm (Kazimierczuk, 2019; IRENA, 2021a), which has an installed capacity of 25.5 MW of the estimated 4600 MW potential (KNBS, 2018). As of 2021, Kenya had 2865 MW total installed capacity, resulting in total power generation of 58PJ, comprising 41% geothermal, 30% hydro, 16% wind, 10% thermal, and 1% solar with 2% imported (EPRA, 2022). Therefore, a significant percentage of renewable energy sources within the nation remains unexploited.

Previous modelling of Kenyan energy generation and demand

The last decade has seen an increasing number of studies which look to model energy production and demand across the African continent, SSA, or the eastern African region as a whole. Van der Zwaan et al. (2018) applied TIAM-ECN software to model the effects of implementing the Paris Agreement on renewable energy production in SSA from 2010 to 2030. Taliotis et al. (2016) utilised OSeMOSYS to produce TEMBA, an electricity model base for Africa, which models the potential of regional electricity trade across SSA and the regional power pools from 2015 to 2040. Ouedraog (2017) used Low Emissions Analysis Platform (LEAP) software to model various demand scenarios, including renewable energy and EE pathways, across SSA from 2015 to 2040. McCluskey et al. (2022) developed a river basin model (WEAP) to examine varying hydropower production scenarios, including allowing trade across varying SSA power pools.

Various studies have also looked at national level modelling of Kenya’s energy sector in some capacity. Irungu et al. (2014) used a bottom-up approach with LEAP software to model various mid-term development pathways from 2013 to 2030 and the subsequent connected greenhouse gas (GHG) emissions through business as usual (BAU), natural gas, and renewables scenarios. Similarly, Kehbila et al. (2021) used LEAP to model potential GHG mitigation scenarios in Kenya from 2010 to 2040, including the African Union Agenda 2063, UN SDGs 2030, and full exploitation of renewables. Carvallo et al. (2017) utilised the bottom-up model SWITCH-Kenya to assess mid-term low-carbon pathways from 2020 to 2035, including varying geothermal capacity, coal power generation, and carbon emission tax scenarios. Lahmeyer International (2013) employed LIPS-XP to evaluate the differing cost of universal electrification across Kenya under different mid-term economic growth scenarios from 2015 to 2035. Such Kenyan studies have focused on select mid-term scenarios which apply specific portfolios in isolation, such as electrification, hydropower, or increased demand. Consequently, there is scope for research which brings together Kenya’s various energy targets to inform policy which take into consideration both renewable energy expansion and increased demand. This Paper will utilise energy systems modelling to produce key insights and policy recommendations for the implementation of a clean energy transition within Kenya.

Energy systems modelling was employed to produce evidence-based policy recommendations (Niet et al., 2021) based on insights gained from scenario resolutions. Energy system modelling has developed rapidly over the past decade as a powerful approach to produce quantitative evidence and support energy planning, providing insights regarding energy production and sustainable development at local to global scales (Howells et al., 2011). OSeMOSYS software is used due to the ease with which high quality and accessible technical data can be produced based on established scenarios (Welsch et al., 2012). OSeMOSYS uses a bottom-up, linear optimisation to generate the least cost optimal solutions to meet a pre-determined energy demand under defined constraints (Gardumi et al., 2018). Within the model, technologies are defined by specified parameters such as cost (capital investments, fuel costs, and variable costs), the operational life of various types of generating plant, and current installed capability (residual capacity). The research employs the CCG SAND interface, a spreadsheet-based software, to increase the accessibility of the OSeMOSYS system. OSeMOSYS is also used within this study due to its open source free and accessible nature (Ramos et al., 2022) and ability to facilitate capacity-building and enable future application by researchers and policy makers in resource-limited nations (Loffler et al., 2017). Scenarios utilise the Kenya low-cost energy “starter data kit” produced by Climate Compatible Growth (CCG) (Allington et al., 2021) as a base file in which more current and nationally produced data were updated and added manually. Both current and potential energy plants and commodities are included within the model, as shown in the reference energy system (Figure 1).

2.1 Current power system data

Data for the total power generation mix from 2015 to 2021 were collected from the Kenyan Energy and Petroleum Regulatory Authority (EPRA, 2019; 2022). Additionally, the total installed capacity from 2015 to 2050 was added, utilising residual capacity parameters for current power plants, allowing for decommissioning based on power production start dates and estimates of plant operational life. All power plant types are modelled as a single technology with existing power plants combined and represented as one resource type. The starter data kit capital costs for power generation technologies have been updated using current and national data sets (USAID, 2019; EPRA, 2020a). This takes into consideration international predictions of a future reduction in renewable energy production prices (IRENA 2021a; EPRA, 2020b). Additionally, the total maximum energy potential per source within Kenya was added as a constraint, preventing the model from depleting more resources than exist within the region (Mukasa et al., 2015).

Main Modelling Assumptions

Assumptions are included within the model to account for the limited availability of national datasets. Certain technologies, such as the fossil fuel plants, are defined by global and regional average costs as opposed to nationally specific values due to a lack of accessible data for Kenya. Additionally, annual demand growth rates are projected, taking into consideration previous trends and future plans. This model does not include energy technologies beyond the power sector such as clean cooking, transport, and batteries or the potential for integration of such sources in the future. Alongside this, as modelled technologies are simplified significantly to single categorisations, such as geothermal (PWRGEO), individual nuances and variations within resource type cannot be accounted for. The business as usual (BAU) energy demand for Kenya to 2050 was taken from the results of early TEMBA projections (Taliotis et al., 2016). TEMBA, a model of African electricity supply, looks to the potential for power trade within Africa to address electrification and increased demand. Finally, within this research time scales are defined as short (up to 5 years), mid (10-20 years) and long (20+ years) term. Despite these assumptions, the model is still able to provide critical in-depth insights into Kenya’s energy system under varying scenarios to inform policy recommendations. Additionally, this research can serve as a building block to develop a more detailed and comprehensive model of Kenya’s energy sector in the future where such assumptions can be tested and varied.

Modelled Scenarios

Six scenarios were modelled for Kenya’s power system to explore the impacts of increased renewable production, EE measures, and increased demand on the BAU baseline resolutions. Table 1 outlines the constraints applied in each of the produced scenarios.

1. Business as Usual: The BAU model is used as a baseline energy system framework from Kenya to different the different scenarios. Constraints were included to produce the energy generation shares seen in Kenya from 2015 to 2021. No new investments into EE were considered and demand levels were kept as outlined in the TEMBA model. Policies such as the LCPDP and Vision 2030 are not achieved within this scenario. No new investments are included from 2015 to 2021.

2. Vision 2030: The Vision 2030 scenario follows a future where 100% renewable energy production by 2030 is achieved. The model assumes no new investments in fossil fuels, nuclear power, or energy efficiency (EE). The share of total demand to be met by each source is constrained with upper limits to guarantee the system is realistic and operational under a high proportion of renewable energy sources.

3. Vision 2030 & EE: The Vision 2030 & EE scenario follows the 100% renewable energy mix by 2030 as seen in the previous scenario. Additionally, the model sees a gradual increase in EE investments from 2022 to reach 25% of the total demand from 2030.

4. Increased Demand (LCPDP): This scenario involves a future where a revised 100% electrification target, as highlighted in the LCPDP targets, is achieved by 2025 (given the halt in progress following the COVID-19 pandemic). This is combined with a gradual increase in energy demand from 2022 to align with a 10% annual GDP growth from 2030. The model assumes no investments in EE or nuclear energy after 2021. The share of total demand to be met by each source is constrained with upper limits to ensure viability and energy diversity.

5. LCPDP & Vision 2030: This scenario involves a combination of the Vision 2030 and LCPDP scenarios, combining the targets set by both Vision 2030 and the LCPDP. Energy demand is gradually increased to achieve 100% electrification by 2025 and 10% annual GDP growth by 2030. Upper constraints are applied to all fossil fuels to achieve 100% renewable generation by 2030. Additionally, the model assumes no new investments in fossil fuels, nuclear power, or EE.

6. Clean Energy Transitions (CET): This scenario produces the prospect of achieving both Vision 2030 and LCPDP alongside increased EE measures. In addition to the constraints observed in the previous scenario, a minimum investment into EE technologies is gradually added annually from 2022 to meet 25% of Kenya’s energy demand from 2030.

Technologies	Percentage Share (%)
Biomass Power Plant	30
Geothermal Power Plant	40
Solar PV (Utility)	15
Onshore Wind	15
Offshore Wind	10
Utility Scale PV with 2-hour storage	15
Onshore Wind Power Plant with Storage	25

Table 1: Maximum generation share constraints added to the total technology annual activity upper limit for each technology to produce a realistic and diverse energy mix.

Scenario resolutions provide six key takeaway points: (1) in the mid-term, geothermal and hydropower remain the most important technologies for a clean power system; (2) in the long-term, wind power will overtake hydropower in the energy mix; (3) a 100% renewable power system by 2030 is realistic under all scenarios; (4) a 100% renewable power sector without EE investments at current demand projections will be more expensive; (5) adoption of EE measures significantly reduces overall consumption rates; and (6) under all high renewable scenarios, flexible technologies and technologies with storage become increasingly important to counter the intermittency of renewable resources.

Power Generation

Figure 2 demonstrates the annual power generation for the six scenarios individually. Across all scenarios, 2030 energy mixes show a least-cost future where Kenya’s power sector is either 100%, 99%, or 94% fully renewable (Figure 3). Despite no fossil fuel constraints, from 2022 the LCPDP energy mix consists almost entirely of renewable energy at 98.6%, until 2040 when combined cycle gas turbines (CCGT) are ramped up and 2050 when simple cycle combustion turbines (SCGT) are introduced. Across all but the LCPDP scenario, in 2030, geothermal energy comprises the largest source of power, hydropower energy the second and wind energy the third main source of power. Surprisingly, despite the BAU scenario containing no upper constraints on renewable production, the energy mixes across all the five other scenarios remain similar, relying on geothermal, hydro, wind, and solar power. Where the four renewable scenarios supplement the remaining generation through biofuels, the BAU scenario relies on small percentages of biofuels, oil fired gas turbines, and CCGT. Interestingly the LCPDP scenario produces a slightly different order in its 2030 generation mix compared to the other five, with hydropower producing the most energy, closely followed by geothermal and wind. Consequently, the scenarios demonstrate how the least-cost resolutions for 2030 under both current and a projected demand increase produce a 94–99% renewable mix, and under a similar energy mix a 100% clean energy generation can be achieved.

When looking at longer-term projections, the mix of energy produced by 2050 varies greatly depending on the scenario (Figure 4). The 2050 BAU power mix becomes 18% fossil fuels, despite geothermal remaining the largest source of power. Similarly, the share of energy generated by fossil fuels under the LCPDP scenario increases to 61%, with geothermal production reducing drastically. As a result, despite renewable capital costs decreasing annually, the model still finds fossil fuels to be the most cost-efficient solution in the long term. In the generation mixes under both the Vision 2030 and the Vision 2030 & EE scenarios, wind power overtakes geothermal to become the primary source of energy, with wind sitting at 39.5% and 40.3% respectively, compared to 35.6% and 38.9% for geothermal energy. In the LCPDP & Vision 2030 and CET scenarios, geothermal energy remains the primary resource, with wind and solar energy overtaking hydropower in relation to percentage share.

Power Production

Figure 5 compares the total power production totals across all six scenarios in 2050, with Figure 6 demonstrating the differences across each scenario compared to a BAU scenario. The rapid increase in power generation from the BAU, Vision 2030, and Vision 2030 & EE scenarios to the LCPDP, LCPDP & Vision 2030, and CET scenarios is due primarily to the rise in demand associated with both universal electrification and annual GDP growth. Alongside this, the rise could also be a result of the increased levels of wind and solar power production associated with greater development of renewable energy systems. The intermittent nature of such technologies means a larger amount of power production, with appropriate storage facilities, is needed to account for the times when solar and wind power cannot be generated.

Despite this, power production decreases by 8.2% in 2050 under the CET scenario compared to LCPDP & Vision 2030 with no EE investments. Similarly, energy production decreases 9.5% in 2050 from the Vision 2030 compared to the Vision 2030 & EE scenario. EE measures can therefore be used to reduce consumption rates, providing a successful way to manage increasing energy demand. Consequently, the CET and Vision 2030 & EE scenarios show how a fully renewable power system can be achieved through primarily geothermal, hydro, and wind power in 2030, altering to geothermal, wind, and solar by 2050. Such generation suggests that geothermal resources will provide a stable and reliable source of energy, with the flexibility to meet demand in periods when these inherently intermittent resources are unreliable or unavailable (Matek, 2015). However, system flexibility, optimal EE impact, and the associated costs of such variables are not assessed within the scope of this research, and should be examined further.

Total Costs and Capital Investment

Figure 7 shows the overall total system costs, and Figure 8 the variation compared to BAU, for all six scenarios. Overall, there is a $74.6bn difference between the scenarios, and LCPDP & Vision 2030 and CET result in the highest overall system costs (at $287.9bn and 289.2bn respectively). Despite investments under the CET model into EE, the LCPDP & Vision 2030 is the cheapest scenario of the two. Regardless, both scenarios are significantly more expensive than the LCPDP with no fossil fuel constraints. At a total system cost of $276.3 billion, the LCPDP is $11.6 and $12.9 billion cheaper than the LCPDP & Vision 2030 and CET respectively. Consequently, the fully renewable, increased demand scenarios will see a significant increase in costs. Additionally, the BAU remains the cheapest scenario, reaching a total cost of $214.7 billion, with an additional increase of $9.5 billion to reach a fully renewable system through the Vision 2030 scenario. Despite the increased cost of the CET relative to the LCPDP & Vision 2030, investment into efficiency in the Vision 2030 & EE reduces overall system costs to $221.8 billion, a $2.4 billion saving.

Comparison to existing policy

Both the existing LCPDP and the LCPDP modelled within this study identified geothermal power as the least cost resource to adopt to meet Kenya’s increased demand over the mid-term. The current LCPDP (Republic of Kenya, 2018b) for 2037 predicts an energy mix of 26.7% geothermal, 17.9% hydro, 19.5% coal, 8.6% solar, 8.5% wind and 7.6% natural gas. Results from the LCPDP model for 2037 in the current research varied greatly, consisting of 34% geothermal, 28% wind, 25.9% hydro, 9.5% solar and 2% natural gas. Consequently, the overall fossil fuel generation mix in 2037 varies from 27.1% in the current plan to just 2% from this research. The current plan does, however, acknowledge the increasing role of wind and solar, also reflected in this research.

Additionally, the current LCPDP provides a mid-term projection (to 2037) of Kenya’s energy sector, identifying geothermal and hydropower as the two most significant and cost-optimal renewable resources to meet increased demand. However, through extending the modelling period, this study’s LCPDP projected energy mix changes significantly after 2037. This study instead finds that relying primarily on geothermal and hydro power is not a cost-optimal energy mix for Kenya. Instead, from 2037, wind power, mainly through onshore wind technologies with storage, is the second most cost-efficient resource in all scenarios which meet the 100% renewable 2030 target. Despite hydropower producing a substantial proportion (25.9%) of the energy generation mix in 2037, this falls significantly to just 7% by 2050. The increasing role of wind power, and reduction in the importance of hydropower, is seen in all modelled scenarios bar the BAU. As a result, these modelled scenarios highlight the potential for changes in cost-optimal investment choices when looking at a long term, as opposed to short- and mid-term period.

Policy Recommendations

The Clean Energy Transition (CET) is a long-term scenario which would allow Kenya to reach climate compatible economic growth alongside SDG 7 and their Nationally Determined Contributions (NDCs), Vision 2030, and LCPDP goals. The implementation of a CET will be extremely beneficial by reducing environmental damage, boosting the economy through job creation, lowering power demand, and relieving pressure on energy transmission and distribution (Okeyo and Ragui, 2017; Zalengera et al., 2020; Musah et al., 2021). Onekon and Kipchirchir (2016) highlight how a green economy in Kenya would allow the nation not only to achieve increased GDP, but also lower poverty levels and unemployment, creating up to 300,000 jobs across the next five years. Similarly, the IEA (2022) have predicted there could be a 75% increase in electricity demand across Africa by the end of the decade to meet increased electrification and economic production, highlighting a need to curtail growing demand.

Optimal EE penetration levels to reduce overall system costs could be found through additional research beyond this paper. To implement a CET within Kenya, seven key policy recommendations should be adopted with immediate effect: (1) no new fossil fuel investments and a cost-optimal phase out to achieve a 100% renewable power system by 2030; (2) updated LCPDP which integrates and aligns with all other climate and energy targets including Vision 2030 goals; (3) creation of a long-term power plan which outlines and implements a shift from significant hydropower generation to wind; (4) penetration of high EE technologies and investments into the power sector; (5) secure long-term investments into infrastructure and power generation in order to ensure a shift in focus to renewable energy and EE; (6) ensuring a focus in development and installation of geothermal and renewable energies (with storage) in order to account for energy production intermittencies; and (7) improvements in the power transmission and distribution grids and networks.

Potential for a 100% Renewable Power Sector in Kenya

All modelled scenarios show that an energy system that has a high proportion of renewable sources by 2030 is both possible and realistic for Kenya. Even when no constraints are added, renewable energy technologies within Kenya are cost-optimal, and a 100% renewable power sector should therefore be pursued and integrated into all national energy policies. Renewable technology costs are decreasing with further technological developments and improvements, and this will continue in the coming years (IEA, 2022). Thus 100% renewable energy investment and production must be prioritised within energy policy and future power development plans, supported by clear and measurable targets. Such a target should include mandatory 100% clean energy generation from 2030, with a primary baseload consisting mainly of geothermal and hydropower energy, with a smaller reliance on wind (at a cost-optimal rate of 34%, 30%, and 12% of the total energy mix). This should be developed with the intention to continue primary geothermal production alongside increased wind and solar power, reducing hydropower production in the longer term (at a modelled cost-efficient mix of 39% geothermal, 34% wind, and 13% solar).

Updated Least Cost Power Development Plan (LCPDP) for Kenya

Future LCPDP revisions should prioritise the integration and harmonisation of all existing cross-sector policies and targets, including (but not limited to) the Vision 2030 plan, SDG 7, and Kenya’s NDCs. The current LCPDP contains no fossil fuel constraints, resulting in a recommendation of increased non-renewable production, including the extraction and production of Kenyan coal for the first time in the eastern African region. This will see a significant increase in GHG emissions, contradicting the targets of Vision 2030, SDG 7, and Kenya’s NDC. Additionally, Kenya’s unique position as a current regional, continental, and international leader in renewable energy production will be lost, with the potential capacity to become a regional exporter of renewable electricity significantly reduced. Additionally, even in the event of political opposition or long-term barriers to the implementation of 100% renewable energy commitments, the least-cost solution should be updated to the 98% renewable generation mix as suggested in this study. Consequently, this research recommends that the LCPDP should be reviewed, and crucially fossil fuel production and use should be phased-out.

Long-Term Power Plan for Kenya

Government recommended long-term energy policies would help promote private sector investment into renewable technologies through increasing stakeholder confidence, increasing private sector involvement, and reducing pressure on the Kenyan government to drive the renewable energy transition (Diaz et al., 2017; Kim, 2019). Currently Kenya lacks a long-term nationally integrated renewable energy expansion plan, which severely inhibits the country’s ability to fully realise a CET within its power sectors. By extending the modelling and planning to a longer-term period of 2050, this study finds that the cost-optimal renewable energy resource mix changes after 2037, highlighting the need to look to long-term priorities alongside short and mid-term goals. Additionally, policy implementations should include compulsory social, economic, and environmental impact assessments, and capacity building programmes should be prioritised to guarantee rural communities benefit from associated job opportunities. Care and consideration should be prioritised when planning solar and wind expansion projects to avoid social harms or negatively impacting citizens residing within affected areas (Njiru and Letema, 2018; Osiolo, 2021).

Energy Efficiency (EE) Integration

The potential of, and need for, energy efficiency in Kenya’s power sector to meet future demand levels is high. Without EE measures, the 7-10% increase in energy demand from a rising GDP would be unrealistic, resulting in a minimum $61.6 billion increase in overall system costs, as seen in the LCPDP results. This highlights the critical need to make EE a national priority if Kenya is to reach climate compatible economic development. Current policies such as the Vision 2030 and LCPDP, which both outline EE as a key component of Kenya’s future power sector, must be brought together to enforce clear and measurable short-, mid- and long-term targets. Furthermore, additional regulation should be adopted which implements minimum energy performance standards for all appliances and technologies nationally, to curtail unnecessary energy losses (Sonnenschein et al., 2019). Further studies should investigate increased EE investments to produce cost-optimal and realistic integration levels for Kenya’s power sector. As a result, this study recommends further research into EE technologies within Kenya to elucidate the most realistic and economical level of investment needed to reduce total overall system costs.

Secure Long-Term Investments

This research shows how an energy system based on a high contribution of renewable sources by 2030 is realistic for Kenya and could propel the nation forward as a regional leader in renewable production through spearheading sub-Saharan Africa (SSA) CETs. However, capital funds and financing for such a power sector development remains a key barrier to Kenya’s realisation of its clearly immense potential. This study recommends the implementation of further policies, alongside the CET, to aid in nurturing such a development, through prioritising and encouraging greater private investment (Schwerhoff and Sy, 2017). Increased private financing can be encouraged within Kenya through the adoption of renewable energy auctions, feed-in tariffs, renewable energy portfolio standards, and tax exemptions (Atalay et al., 2017; Mabea, 2020). The renewable energy market within Kenya should also be opened up to encourage international investment and development in both renewable energy technologies and EE (Mazzucato and Semieniuk, 2018). Additionally, public–private partnerships will become key to overcoming economic and social barriers to renewable energy expansion across the region (Sergi et al., 2019). Making sure such measures are implemented into written policy and widely enforced will stimulate wider investment. This would lead to increased competition and eventually reduce both electricity and manufacturing costs, helping to address national energy poverty and further promote Kenya’s economic development (Moreno et al., 2012).

Overcoming Intermittent technologies: geothermal power

To ensure a stable and secure supply of energy, Kenya should prioritise the overcoming of barriers associated with intermittent renewable energy production by developing geothermal power. This is a controllable technology with the capability to run constantly, and ramp up production at any given point, to make up for variability in other renewable energy resources (Matek, 2015). A move to renewable energy technologies with storage in the long term, such as onshore wind and solar PV, should also be prioritised to overcome issues associated with meeting demand when supply is intermittent and unreliable (Kandasamy et al., 2017). Installation costs for such technologies have already fallen rapidly over the last few decades and are expected to fall further in coming years (Suberu et al., 2014; Child et al., 2018). As a result, long-term capacity expansion planning in Kenya should project a shift in the coming decades to a significant increase in technologies with additional storage capabilities.

Grid Improvements

In order to meet increased demand, renewable expansion, and energy efficiency installation optimally, Kenya’s ageing transmission lines and energy grid require drastic improvements and substantial investment. Increased spending on enhancing Kenya’s transmission and distribution is needed to improve, or replace, the current inefficient infrastructure, drastically reducing electricity losses during transmission (Surana and Jordaan, 2019). This is vital for a future power system which is predicted to increase in demand between 5-10% annually by 2030 (AFDB, 2022). As a result, Kenya should prioritise transmission and distribution enhancement alongside increased energy production to prevent unnecessary losses through an inefficient network. Further, with the potential to transform into a regional exporter of clean power, a strong grid network with the capacity to interconnect with neighbouring power markets is critical (Remy and Chattopadhyay, 2020). Additionally, energy storage is poised to play an integral role in Kenya’s future power sector, and such technologies will require developments and improvements to the grid storage capacity (Kalair et al., 2021). Thus, significant national energy budget spending should be allocated to facilitate future grid and storage development.

Future Research Recommendations

Flexibility is key to the integration of more renewable energy resources into generation mixes, given the variability and intermittency of renewable sources (Republic of Kenya, 2016b; IEA, 2022). Further studies should assess the flexibility within Kenya’s power sector, using software such as FlexTool to evaluate how realistic the least-cost generation mixes are (Makolo et al., 2021). Additionally, the distribution of renewable energy resources across SSA determines how favourable conditions are for the success of regional power pools in providing an integrated electricity market and will play a key role in accelerating CETs regionally (Remy and Chattopadhyay, 2020; McCluskey et al., 2022). Future research should examine scenarios of increased energy imports and exports for Kenya, assessing the impact this has on power generation and system costs. As the scope of this study was confined purely to Kenya’s power sector, there is scope to assess the wider energy sector through, for example examining clean cooking (Clemens et al., 2018) and EV penetration in the transport sector (Bugaje et al., 2021). Finally, agriculture remains Kenya’s biggest economic driver, taking up half of all land allocation and contributing up to 35% of Kenya’s GDP (AFDB, 2022). The interaction of increased land-intensive renewable technologies such as onshore wind and solar PV farms, compared to alternative renewable resources (Sayed et al., 2021; Rahman et al., 2022), could be assessed through the exploration of CLEWs modelling (Ramos et al., 2021).

Due to Kenya’s fast-growing population (~2% per year) and rapid economic expansion, energy consumption levels are increasing rapidly and are predicted to rise further in the coming decades. Kenya’s mission to become a middle-income country and regional economic leader by the end of this decade means it is set to become one of the most energy intensive countries in Sub-Saharan Africa. Therefore, Kenya must be prepared to satisfy an ever-increasing energy demand in the long term. The projections of rapidly growing energy demand could be met through ramping up fossil fuel production, tapping into national coal reserves for the first time in the region’s history, as outlined within the current Least Cost Power Development Plan. However, a Kenyan power sector reliant on fossil fuel production will: (1) reduce national energy security; (2) regress Kenya’s position as a regional and international renewable energy producer; (3) halt Kenya’s progress towards climate and renewable energy targets; and (4) increase emissions of carbon and other pollutants contributing to global warming and decreasing local and regional air quality, causing negative impacts on the health and well-being of its own and other citizens. An alternative scenario to increasing fossil fuel production would be the implementation of a clean energy transition (CET), a solution where the power sector is formed of ~100% renewable energy generation, and energy efficiency (EE) technologies are effectively employed to reduce energy production levels needed to meet increased demand, lowering overall system costs by 2030. This provides Kenya an exciting opportunity to transform its power sector, fulfilling the Vision 2030 goal of reaching middle income economic status, alongside becoming a regional and international leader in renewable energy production. The introduction of a CET would allow Kenya to pursue a world-leading agenda on clean and renewable energy production, harnessing its wealth of renewable resource potential, and solidifying its position in both the Sub-Saharan region, and the global sphere, by spearheading a wave of energy transitions.

This study shows how a high renewable system is cost-optimal as soon as 2030, in line with Vision 2030 targets. Additionally, EE investments will be needed in the long term to curtail the significant increase in demand associated with increased GDP and population growth and reduce overall system costs. With the successful implementation of a long-term CET, by 2050, Kenya future power mix should consist primarily of 39% geothermal power, closely followed by 34% wind and 13% solar power. Investment into storage technologies for intermittent renewable energy supply is key for a long-term high renewable energy system. The CET will require significant changes, addressed primarily through the formal adoption of a long-term energy plan which includes fundamental policy changes and quantifiable goals to aid in the implementation of such a transition. This study therefore highlights the scope and potential for a CET for Kenya’s power sector. Further studies should assess the flexibility of such a system, examining the energy system beyond purely the power sector to explore clean cooking and transport for example, and the impacts that policy decisions will have on wider climate, land, and water systems.

Declaration of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

Acknowledgements

This material has been produced under the Climate Compatible Growth (CCG) programme, which brings together leading research organisations and is led out of the STEER centre, Loughborough University. CCG is funded by FCDO from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies. This work was developed with the Energy Transition Council (ETC), which assisted in identifying needed research areas and connected to relevant stakeholders for a discussion on essential aspects of this research. This paper was edited by Simon Patterson (CCG, Loughborough University).

U4RIA Compliance

This work follows the U4RIA guidelines (source) which provide a set of high-level goals relating to conducting energy system analyses in countries. This paper was carried out involving stakeholders in the development of models, assumptions, scenarios and results (Ubuntu/Community). The authors ensure that all data, source code and results can be easily found, accessed, downloaded and viewed (retrievability), licensed for reuse (reusability), and that the modelling process can be repeated in an automatic way (repeatability). The authors provide complete metadata for reconstructing the modelling process (reconstructability), ensuring the transfer of data, assumptions and results to other projects, analyses and models (interoperability), and facilitating peer-review through transparency (auditability).

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AppendixRunningtheScenarios.docx
Appendix: Re-running the Scenarios
RerunningtheAnalysis.docx
Appendix: Re-running the Analysis

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Evidence-Based Policy Making: Insights and Policy Recommendations for the Implementation of a Clean Energy Transition in Kenya.

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